Drift Detection and Localization.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "from tqdm import tqdm\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams[\"font.size\"] = 16\n",
    "import seaborn as sns\n",
    "sns.set_style(\"white\")\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "# My packages\n",
    "from source import parse_mxml as pm\n",
    "from source import log_representation as lr\n",
    "from source import plots as plts\n",
    "from source import drift_detection as dd\n",
    "from source import drift_localization as dl\n",
    "from source import offline_streaming_clustering as off_sc\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "import random\n",
    "random.seed(42)\n",
    "\n",
    "import os\n",
    "import glob\n",
    "\n",
    "import gc\n",
    "gc.enable()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def insensitive_glob(pattern):\n",
    "    def either(c):\n",
    "        return '[%s%s]' % (c.lower(), c.upper()) if c.isalpha() else c\n",
    "    return glob.glob(''.join(map(either, pattern)))\n",
    "\n",
    "def if_any(string, lista):\n",
    "    for l in lista:\n",
    "        if l in string:\n",
    "            return True\n",
    "    return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "logs = insensitive_glob(\"../process_mining_datasets/*/*k.MXML\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "logs = [x for x in logs if \"2.5\" not in x]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read and Prep log file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'..\\\\process_mining_datasets\\\\cb\\\\cb5k.mxml'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Example\n",
    "logs[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "log_read = pm.all_prep(logs[1])\n",
    "tokens = lr.get_traces_as_tokens(log_read)\n",
    "y_true = list(range(int(len(tokens)/10), len(tokens), int(len(tokens)/10)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vector space representations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "activity_binary = lr.get_binary_representation(tokens)\n",
    "transitions_binary = lr.get_binary_transitions_representation(tokens)\n",
    "activity_frequency = lr.get_frequency_representation(tokens)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trace Clustering - Transitions Binary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "run_df = off_sc.run_offline_clustering_window(\n",
    "    KMeans(n_clusters=3, random_state=42),\n",
    "    125,\n",
    "    transitions_binary,\n",
    "    sliding_window=False,\n",
    "    sliding_step=1\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Features from the evolution of trace clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_df['avg_dist_between_centroids'].plot(figsize=(16,4), c='red')\n",
    "plts.plot_drift_vertical_lines(len(activity_binary), label=\"True drift\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_df['avg_dist_intra_cluster'].plot(figsize=(16,4), c='red')\n",
    "plts.plot_drift_vertical_lines(len(activity_binary), label=\"True drift\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trace Clustering - Activity Binary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "clustering_window_size = 125\n",
    "\n",
    "run_df = off_sc.run_offline_clustering_window(\n",
    "    KMeans(n_clusters=3, random_state=42),\n",
    "    clustering_window_size,\n",
    "    activity_binary,\n",
    "    sliding_window=False,\n",
    "    sliding_step=1\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Features from the evolution of trace clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_df['avg_dist_between_centroids'].plot(figsize=(16,4))\n",
    "plts.plot_drift_vertical_lines(len(activity_binary), label=\"True drift\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_df['Silhouette'].plot(figsize=(16,4))\n",
    "plts.plot_drift_vertical_lines(len(activity_binary), label=\"True drift\")\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drift Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "drifts, info = dd.detect_concept_drift(\n",
    "    run_df,\n",
    "    'avg_dist_between_centroids',\n",
    "    rolling_window=2,\n",
    "    std_tolerance=2.5,\n",
    "    min_tol=0.03\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Precision': 1.0,\n",
       " 'Recall': 1.0,\n",
       " 'F1': 1.0,\n",
       " 'Delay': 125.0,\n",
       " 'Correct_Predictions': [1, 1, 1, 1, 1, 1, 1, 1, 1],\n",
       " 'Support': 9,\n",
       " 'Drifts_Found': [625, 1125, 1625, 2125, 2625, 3125, 3625, 4125, 4625],\n",
       " 'Resp': [500, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500]}"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd.get_metrics(drifts, y_true, window_size=clustering_window_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plts.plot_deteccao_drift(\n",
    "    run_df,\n",
    "    'avg_dist_between_centroids',\n",
    "    drifts,\n",
    "    y_true,\n",
    "    info['means'],\n",
    "    info['lowers'],\n",
    "    info['uppers'],\n",
    "    save_png=\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Drift Localization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Check_if_home_insurance_quote_is_requested</th>\n",
       "      <td>0.291847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prepare_acceptance_pack</th>\n",
       "      <td>0.291847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Send_acceptance_pack</th>\n",
       "      <td>0.055744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Send_home_insurance_quote</th>\n",
       "      <td>0.055744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Return_application_back_to_applicant</th>\n",
       "      <td>0.006408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Receive_updated_application</th>\n",
       "      <td>0.006408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Appraise_property</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_received</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reject_application</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan_application_rejected</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_canceled</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Approve_application</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_approved</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check_credit_history</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check__application__form_completeness</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cancel_application</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assess_loan_risk</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assess_eligibility</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Verify_repayment_agreement</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   0\n",
       "Check_if_home_insurance_quote_is_requested  0.291847\n",
       "Prepare_acceptance_pack                     0.291847\n",
       "Send_acceptance_pack                        0.055744\n",
       "Send_home_insurance_quote                   0.055744\n",
       "Return_application_back_to_applicant        0.006408\n",
       "Receive_updated_application                 0.006408\n",
       "Appraise_property                           0.000000\n",
       "Loan__application_received                  0.000000\n",
       "Reject_application                          0.000000\n",
       "Loan_application_rejected                   0.000000\n",
       "Loan__application_canceled                  0.000000\n",
       "Approve_application                         0.000000\n",
       "Loan__application_approved                  0.000000\n",
       "Check_credit_history                        0.000000\n",
       "Check__application__form_completeness       0.000000\n",
       "Cancel_application                          0.000000\n",
       "Assess_loan_risk                            0.000000\n",
       "Assess_eligibility                          0.000000\n",
       "Verify_repayment_agreement                  0.000000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dl.localize_drift(\n",
    "    run_df.centroids.loc[500], \n",
    "    run_df.centroids.loc[625], \n",
    "    activity_binary.columns\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>drift_at_625</th>\n",
       "      <th>drift_at_1125</th>\n",
       "      <th>drift_at_1625</th>\n",
       "      <th>drift_at_2125</th>\n",
       "      <th>drift_at_2625</th>\n",
       "      <th>drift_at_3125</th>\n",
       "      <th>drift_at_3625</th>\n",
       "      <th>drift_at_4125</th>\n",
       "      <th>drift_at_4625</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Check_if_home_insurance_quote_is_requested</th>\n",
       "      <td>0.291847</td>\n",
       "      <td>0.178800</td>\n",
       "      <td>0.162058</td>\n",
       "      <td>0.106056</td>\n",
       "      <td>0.117309</td>\n",
       "      <td>0.118831</td>\n",
       "      <td>0.194832</td>\n",
       "      <td>0.190859</td>\n",
       "      <td>0.144066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prepare_acceptance_pack</th>\n",
       "      <td>0.291847</td>\n",
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       "      <td>0.190859</td>\n",
       "      <td>0.144066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Send_acceptance_pack</th>\n",
       "      <td>0.055744</td>\n",
       "      <td>0.009371</td>\n",
       "      <td>0.008542</td>\n",
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       "      <td>0.009032</td>\n",
       "      <td>0.002299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Send_home_insurance_quote</th>\n",
       "      <td>0.055744</td>\n",
       "      <td>0.009371</td>\n",
       "      <td>0.008542</td>\n",
       "      <td>0.027757</td>\n",
       "      <td>0.005993</td>\n",
       "      <td>0.009591</td>\n",
       "      <td>0.007875</td>\n",
       "      <td>0.009032</td>\n",
       "      <td>0.002299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Return_application_back_to_applicant</th>\n",
       "      <td>0.006408</td>\n",
       "      <td>0.020518</td>\n",
       "      <td>0.011018</td>\n",
       "      <td>0.005978</td>\n",
       "      <td>0.003944</td>\n",
       "      <td>0.003094</td>\n",
       "      <td>0.006355</td>\n",
       "      <td>0.009204</td>\n",
       "      <td>0.002468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Receive_updated_application</th>\n",
       "      <td>0.006408</td>\n",
       "      <td>0.020518</td>\n",
       "      <td>0.011018</td>\n",
       "      <td>0.005978</td>\n",
       "      <td>0.003944</td>\n",
       "      <td>0.003094</td>\n",
       "      <td>0.006355</td>\n",
       "      <td>0.009204</td>\n",
       "      <td>0.002468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Appraise_property</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_received</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reject_application</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan_application_rejected</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_canceled</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Approve_application</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_approved</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check_credit_history</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check__application__form_completeness</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cancel_application</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assess_loan_risk</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Verify_repayment_agreement</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            drift_at_625  drift_at_1125  \\\n",
       "Check_if_home_insurance_quote_is_requested      0.291847       0.178800   \n",
       "Prepare_acceptance_pack                         0.291847       0.178800   \n",
       "Send_acceptance_pack                            0.055744       0.009371   \n",
       "Send_home_insurance_quote                       0.055744       0.009371   \n",
       "Return_application_back_to_applicant            0.006408       0.020518   \n",
       "Receive_updated_application                     0.006408       0.020518   \n",
       "Appraise_property                               0.000000       0.000000   \n",
       "Loan__application_received                      0.000000       0.000000   \n",
       "Reject_application                              0.000000       0.000000   \n",
       "Loan_application_rejected                       0.000000       0.000000   \n",
       "Loan__application_canceled                      0.000000       0.000000   \n",
       "Approve_application                             0.000000       0.000000   \n",
       "Loan__application_approved                      0.000000       0.000000   \n",
       "Check_credit_history                            0.000000       0.000000   \n",
       "Check__application__form_completeness           0.000000       0.000000   \n",
       "Cancel_application                              0.000000       0.000000   \n",
       "Assess_loan_risk                                0.000000       0.000000   \n",
       "Assess_eligibility                              0.000000       0.000000   \n",
       "Verify_repayment_agreement                      0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_1625  drift_at_2125  \\\n",
       "Check_if_home_insurance_quote_is_requested       0.162058       0.106056   \n",
       "Prepare_acceptance_pack                          0.162058       0.106056   \n",
       "Send_acceptance_pack                             0.008542       0.027757   \n",
       "Send_home_insurance_quote                        0.008542       0.027757   \n",
       "Return_application_back_to_applicant             0.011018       0.005978   \n",
       "Receive_updated_application                      0.011018       0.005978   \n",
       "Appraise_property                                0.000000       0.000000   \n",
       "Loan__application_received                       0.000000       0.000000   \n",
       "Reject_application                               0.000000       0.000000   \n",
       "Loan_application_rejected                        0.000000       0.000000   \n",
       "Loan__application_canceled                       0.000000       0.000000   \n",
       "Approve_application                              0.000000       0.000000   \n",
       "Loan__application_approved                       0.000000       0.000000   \n",
       "Check_credit_history                             0.000000       0.000000   \n",
       "Check__application__form_completeness            0.000000       0.000000   \n",
       "Cancel_application                               0.000000       0.000000   \n",
       "Assess_loan_risk                                 0.000000       0.000000   \n",
       "Assess_eligibility                               0.000000       0.000000   \n",
       "Verify_repayment_agreement                       0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_2625  drift_at_3125  \\\n",
       "Check_if_home_insurance_quote_is_requested       0.117309       0.118831   \n",
       "Prepare_acceptance_pack                          0.117309       0.118831   \n",
       "Send_acceptance_pack                             0.005993       0.009591   \n",
       "Send_home_insurance_quote                        0.005993       0.009591   \n",
       "Return_application_back_to_applicant             0.003944       0.003094   \n",
       "Receive_updated_application                      0.003944       0.003094   \n",
       "Appraise_property                                0.000000       0.000000   \n",
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       "Loan_application_rejected                        0.000000       0.000000   \n",
       "Loan__application_canceled                       0.000000       0.000000   \n",
       "Approve_application                              0.000000       0.000000   \n",
       "Loan__application_approved                       0.000000       0.000000   \n",
       "Check_credit_history                             0.000000       0.000000   \n",
       "Check__application__form_completeness            0.000000       0.000000   \n",
       "Cancel_application                               0.000000       0.000000   \n",
       "Assess_loan_risk                                 0.000000       0.000000   \n",
       "Assess_eligibility                               0.000000       0.000000   \n",
       "Verify_repayment_agreement                       0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_3625  drift_at_4125  \\\n",
       "Check_if_home_insurance_quote_is_requested       0.194832       0.190859   \n",
       "Prepare_acceptance_pack                          0.194832       0.190859   \n",
       "Send_acceptance_pack                             0.007875       0.009032   \n",
       "Send_home_insurance_quote                        0.007875       0.009032   \n",
       "Return_application_back_to_applicant             0.006355       0.009204   \n",
       "Receive_updated_application                      0.006355       0.009204   \n",
       "Appraise_property                                0.000000       0.000000   \n",
       "Loan__application_received                       0.000000       0.000000   \n",
       "Reject_application                               0.000000       0.000000   \n",
       "Loan_application_rejected                        0.000000       0.000000   \n",
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       "Approve_application                              0.000000       0.000000   \n",
       "Loan__application_approved                       0.000000       0.000000   \n",
       "Check_credit_history                             0.000000       0.000000   \n",
       "Check__application__form_completeness            0.000000       0.000000   \n",
       "Cancel_application                               0.000000       0.000000   \n",
       "Assess_loan_risk                                 0.000000       0.000000   \n",
       "Assess_eligibility                               0.000000       0.000000   \n",
       "Verify_repayment_agreement                       0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_4625  \n",
       "Check_if_home_insurance_quote_is_requested       0.144066  \n",
       "Prepare_acceptance_pack                          0.144066  \n",
       "Send_acceptance_pack                             0.002299  \n",
       "Send_home_insurance_quote                        0.002299  \n",
       "Return_application_back_to_applicant             0.002468  \n",
       "Receive_updated_application                      0.002468  \n",
       "Appraise_property                                0.000000  \n",
       "Loan__application_received                       0.000000  \n",
       "Reject_application                               0.000000  \n",
       "Loan_application_rejected                        0.000000  \n",
       "Loan__application_canceled                       0.000000  \n",
       "Approve_application                              0.000000  \n",
       "Loan__application_approved                       0.000000  \n",
       "Check_credit_history                             0.000000  \n",
       "Check__application__form_completeness            0.000000  \n",
       "Cancel_application                               0.000000  \n",
       "Assess_loan_risk                                 0.000000  \n",
       "Assess_eligibility                               0.000000  \n",
       "Verify_repayment_agreement                       0.000000  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Result of drift localization in the ground truth drifts\n",
    "\n",
    "dl.localize_all_drifts(\n",
    "    run_df,\n",
    "    [x + clustering_window_size for x in y_true], \n",
    "    clustering_window_size,\n",
    "    activity_binary.columns\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>drift_at_625</th>\n",
       "      <th>drift_at_1125</th>\n",
       "      <th>drift_at_1625</th>\n",
       "      <th>drift_at_2125</th>\n",
       "      <th>drift_at_2625</th>\n",
       "      <th>drift_at_3125</th>\n",
       "      <th>drift_at_3625</th>\n",
       "      <th>drift_at_4125</th>\n",
       "      <th>drift_at_4625</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Check_if_home_insurance_quote_is_requested</th>\n",
       "      <td>0.291847</td>\n",
       "      <td>0.178800</td>\n",
       "      <td>0.162058</td>\n",
       "      <td>0.106056</td>\n",
       "      <td>0.117309</td>\n",
       "      <td>0.118831</td>\n",
       "      <td>0.194832</td>\n",
       "      <td>0.190859</td>\n",
       "      <td>0.144066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prepare_acceptance_pack</th>\n",
       "      <td>0.291847</td>\n",
       "      <td>0.178800</td>\n",
       "      <td>0.162058</td>\n",
       "      <td>0.106056</td>\n",
       "      <td>0.117309</td>\n",
       "      <td>0.118831</td>\n",
       "      <td>0.194832</td>\n",
       "      <td>0.190859</td>\n",
       "      <td>0.144066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Send_acceptance_pack</th>\n",
       "      <td>0.055744</td>\n",
       "      <td>0.009371</td>\n",
       "      <td>0.008542</td>\n",
       "      <td>0.027757</td>\n",
       "      <td>0.005993</td>\n",
       "      <td>0.009591</td>\n",
       "      <td>0.007875</td>\n",
       "      <td>0.009032</td>\n",
       "      <td>0.002299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Send_home_insurance_quote</th>\n",
       "      <td>0.055744</td>\n",
       "      <td>0.009371</td>\n",
       "      <td>0.008542</td>\n",
       "      <td>0.027757</td>\n",
       "      <td>0.005993</td>\n",
       "      <td>0.009591</td>\n",
       "      <td>0.007875</td>\n",
       "      <td>0.009032</td>\n",
       "      <td>0.002299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Return_application_back_to_applicant</th>\n",
       "      <td>0.006408</td>\n",
       "      <td>0.020518</td>\n",
       "      <td>0.011018</td>\n",
       "      <td>0.005978</td>\n",
       "      <td>0.003944</td>\n",
       "      <td>0.003094</td>\n",
       "      <td>0.006355</td>\n",
       "      <td>0.009204</td>\n",
       "      <td>0.002468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Receive_updated_application</th>\n",
       "      <td>0.006408</td>\n",
       "      <td>0.020518</td>\n",
       "      <td>0.011018</td>\n",
       "      <td>0.005978</td>\n",
       "      <td>0.003944</td>\n",
       "      <td>0.003094</td>\n",
       "      <td>0.006355</td>\n",
       "      <td>0.009204</td>\n",
       "      <td>0.002468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Appraise_property</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_received</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reject_application</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan_application_rejected</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_canceled</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Approve_application</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loan__application_approved</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check_credit_history</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Check__application__form_completeness</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cancel_application</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assess_loan_risk</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assess_eligibility</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Verify_repayment_agreement</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            drift_at_625  drift_at_1125  \\\n",
       "Check_if_home_insurance_quote_is_requested      0.291847       0.178800   \n",
       "Prepare_acceptance_pack                         0.291847       0.178800   \n",
       "Send_acceptance_pack                            0.055744       0.009371   \n",
       "Send_home_insurance_quote                       0.055744       0.009371   \n",
       "Return_application_back_to_applicant            0.006408       0.020518   \n",
       "Receive_updated_application                     0.006408       0.020518   \n",
       "Appraise_property                               0.000000       0.000000   \n",
       "Loan__application_received                      0.000000       0.000000   \n",
       "Reject_application                              0.000000       0.000000   \n",
       "Loan_application_rejected                       0.000000       0.000000   \n",
       "Loan__application_canceled                      0.000000       0.000000   \n",
       "Approve_application                             0.000000       0.000000   \n",
       "Loan__application_approved                      0.000000       0.000000   \n",
       "Check_credit_history                            0.000000       0.000000   \n",
       "Check__application__form_completeness           0.000000       0.000000   \n",
       "Cancel_application                              0.000000       0.000000   \n",
       "Assess_loan_risk                                0.000000       0.000000   \n",
       "Assess_eligibility                              0.000000       0.000000   \n",
       "Verify_repayment_agreement                      0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_1625  drift_at_2125  \\\n",
       "Check_if_home_insurance_quote_is_requested       0.162058       0.106056   \n",
       "Prepare_acceptance_pack                          0.162058       0.106056   \n",
       "Send_acceptance_pack                             0.008542       0.027757   \n",
       "Send_home_insurance_quote                        0.008542       0.027757   \n",
       "Return_application_back_to_applicant             0.011018       0.005978   \n",
       "Receive_updated_application                      0.011018       0.005978   \n",
       "Appraise_property                                0.000000       0.000000   \n",
       "Loan__application_received                       0.000000       0.000000   \n",
       "Reject_application                               0.000000       0.000000   \n",
       "Loan_application_rejected                        0.000000       0.000000   \n",
       "Loan__application_canceled                       0.000000       0.000000   \n",
       "Approve_application                              0.000000       0.000000   \n",
       "Loan__application_approved                       0.000000       0.000000   \n",
       "Check_credit_history                             0.000000       0.000000   \n",
       "Check__application__form_completeness            0.000000       0.000000   \n",
       "Cancel_application                               0.000000       0.000000   \n",
       "Assess_loan_risk                                 0.000000       0.000000   \n",
       "Assess_eligibility                               0.000000       0.000000   \n",
       "Verify_repayment_agreement                       0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_2625  drift_at_3125  \\\n",
       "Check_if_home_insurance_quote_is_requested       0.117309       0.118831   \n",
       "Prepare_acceptance_pack                          0.117309       0.118831   \n",
       "Send_acceptance_pack                             0.005993       0.009591   \n",
       "Send_home_insurance_quote                        0.005993       0.009591   \n",
       "Return_application_back_to_applicant             0.003944       0.003094   \n",
       "Receive_updated_application                      0.003944       0.003094   \n",
       "Appraise_property                                0.000000       0.000000   \n",
       "Loan__application_received                       0.000000       0.000000   \n",
       "Reject_application                               0.000000       0.000000   \n",
       "Loan_application_rejected                        0.000000       0.000000   \n",
       "Loan__application_canceled                       0.000000       0.000000   \n",
       "Approve_application                              0.000000       0.000000   \n",
       "Loan__application_approved                       0.000000       0.000000   \n",
       "Check_credit_history                             0.000000       0.000000   \n",
       "Check__application__form_completeness            0.000000       0.000000   \n",
       "Cancel_application                               0.000000       0.000000   \n",
       "Assess_loan_risk                                 0.000000       0.000000   \n",
       "Assess_eligibility                               0.000000       0.000000   \n",
       "Verify_repayment_agreement                       0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_3625  drift_at_4125  \\\n",
       "Check_if_home_insurance_quote_is_requested       0.194832       0.190859   \n",
       "Prepare_acceptance_pack                          0.194832       0.190859   \n",
       "Send_acceptance_pack                             0.007875       0.009032   \n",
       "Send_home_insurance_quote                        0.007875       0.009032   \n",
       "Return_application_back_to_applicant             0.006355       0.009204   \n",
       "Receive_updated_application                      0.006355       0.009204   \n",
       "Appraise_property                                0.000000       0.000000   \n",
       "Loan__application_received                       0.000000       0.000000   \n",
       "Reject_application                               0.000000       0.000000   \n",
       "Loan_application_rejected                        0.000000       0.000000   \n",
       "Loan__application_canceled                       0.000000       0.000000   \n",
       "Approve_application                              0.000000       0.000000   \n",
       "Loan__application_approved                       0.000000       0.000000   \n",
       "Check_credit_history                             0.000000       0.000000   \n",
       "Check__application__form_completeness            0.000000       0.000000   \n",
       "Cancel_application                               0.000000       0.000000   \n",
       "Assess_loan_risk                                 0.000000       0.000000   \n",
       "Assess_eligibility                               0.000000       0.000000   \n",
       "Verify_repayment_agreement                       0.000000       0.000000   \n",
       "\n",
       "                                            drift_at_4625  \n",
       "Check_if_home_insurance_quote_is_requested       0.144066  \n",
       "Prepare_acceptance_pack                          0.144066  \n",
       "Send_acceptance_pack                             0.002299  \n",
       "Send_home_insurance_quote                        0.002299  \n",
       "Return_application_back_to_applicant             0.002468  \n",
       "Receive_updated_application                      0.002468  \n",
       "Appraise_property                                0.000000  \n",
       "Loan__application_received                       0.000000  \n",
       "Reject_application                               0.000000  \n",
       "Loan_application_rejected                        0.000000  \n",
       "Loan__application_canceled                       0.000000  \n",
       "Approve_application                              0.000000  \n",
       "Loan__application_approved                       0.000000  \n",
       "Check_credit_history                             0.000000  \n",
       "Check__application__form_completeness            0.000000  \n",
       "Cancel_application                               0.000000  \n",
       "Assess_loan_risk                                 0.000000  \n",
       "Assess_eligibility                               0.000000  \n",
       "Verify_repayment_agreement                       0.000000  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Result of drift localization in all predicted drifts\n",
    "\n",
    "dl.localize_all_drifts(\n",
    "    run_df,\n",
    "    drifts, \n",
    "    clustering_window_size,\n",
    "    activity_binary.columns\n",
    ")"
   ]
  }
 ],
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