fixed in benchmarking notebook

attila-balint-kul · Sep 19, 2024 · deb8c71 · deb8c71
1 parent 25b95bb
commit deb8c71
Showing 1 changed file with 10 additions and 10 deletions.
diff --git a/notebooks/04. Benchmarking.ipynb b/notebooks/04. Benchmarking.ipynb
@@ -84,8 +84,8 @@
    "source": [
     "edd.metadata_subset.read().freq.unique()\n",
     "print(f\"Available frequencies in the {edd.__class__.__name__}: {edd.metadata_subset.read().freq.unique().tolist()}\")\n",
-    "print(f\"Number of buildings in the {pvd.__class__.__name__}: {pvd.metadata_subset.read().freq.unique().tolist()}\")\n",
-    "print(f\"Number of buildings in the {gdd.__class__.__name__}: {gdd.metadata_subset.read().freq.unique().tolist()}\")"
+    "print(f\"Available frequencies in the {pvd.__class__.__name__}: {pvd.metadata_subset.read().freq.unique().tolist()}\")\n",
+    "print(f\"Available frequencies in the {gdd.__class__.__name__}: {gdd.metadata_subset.read().freq.unique().tolist()}\")"
    ],
    "id": "89fa8501c79bd935",
    "outputs": [],
@@ -292,7 +292,7 @@
   {
    "metadata": {},
    "cell_type": "code",
-   "source": "leaderboard = pd.DataFrame()",
+   "source": "ed_leaderboard = pd.DataFrame()",
    "id": "fc08a2dc7a840ab7",
    "outputs": [],
    "execution_count": null
@@ -327,7 +327,7 @@
     "model = SeasonalNaiveModel(seasonality='1D')\n",
     "model_results_df = benchmark_model(dataset, buildings, model, cv_folds=cv_folds, cv_step=cv_step, cv_horizon=cv_horizon)\n",
     "model_results_df['rMAE'] = (model_results_df / baseline_results_df).loc[:, \"MAE\"]\n",
-    "leaderboard['DailyNaiveSeasonal'] = model_results_df.mean()"
+    "ed_leaderboard['DailyNaiveSeasonal'] = model_results_df.mean()"
    ],
    "id": "d5bd62abc9d74384",
    "outputs": [],
@@ -340,7 +340,7 @@
     "model = SeasonalNaiveModel(seasonality='7D')\n",
     "model_results_df = benchmark_model(dataset, buildings, model, cv_folds=cv_folds, cv_step=cv_step, cv_horizon=cv_horizon)\n",
     "model_results_df['rMAE'] = (model_results_df / baseline_results_df).loc[:, \"MAE\"]\n",
-    "leaderboard['WeeklyNaiveSeasonal'] = model_results_df.mean()"
+    "ed_leaderboard['WeeklyNaiveSeasonal'] = model_results_df.mean()"
    ],
    "id": "b24aa0b7833cf4cc",
    "outputs": [],
@@ -383,7 +383,7 @@
     "model = HistoricAverageModel()\n",
     "model_results_df = benchmark_model(dataset, buildings, model, cv_folds=cv_folds, cv_step=cv_step, cv_horizon=cv_horizon)\n",
     "model_results_df['rMAE'] = (model_results_df / baseline_results_df).loc[:, \"MAE\"]\n",
-    "leaderboard['HistoricAverage'] = model_results_df.mean()"
+    "ed_leaderboard['HistoricAverage'] = model_results_df.mean()"
    ],
    "id": "c5592bb9a3be7f91",
    "outputs": [],
@@ -436,7 +436,7 @@
     "model = SeasonalWindowAverageModel(\"1D\", 28)\n",
     "model_results_df = benchmark_model(dataset, buildings, model, cv_folds=cv_folds, cv_step=cv_step, cv_horizon=cv_horizon)\n",
     "model_results_df['rMAE'] = (model_results_df / baseline_results_df).loc[:, \"MAE\"]\n",
-    "leaderboard['SeasonalWindowAverageS1DW28'] = model_results_df.mean()"
+    "ed_leaderboard['SeasonalWindowAverageS1DW28'] = model_results_df.mean()"
    ],
    "id": "86312b6c8b3875aa",
    "outputs": [],
@@ -449,7 +449,7 @@
     "model = SeasonalWindowAverageModel(\"7D\", 4)\n",
     "model_results_df = benchmark_model(dataset, buildings, model, cv_folds=cv_folds, cv_step=cv_step, cv_horizon=cv_horizon)\n",
     "model_results_df['rMAE'] = (model_results_df / baseline_results_df).loc[:, \"MAE\"]\n",
-    "leaderboard['SeasonalWindowAverageS7DW4'] = model_results_df.mean()"
+    "ed_leaderboard['SeasonalWindowAverageS7DW4'] = model_results_df.mean()"
    ],
    "id": "1c6a8dd0645623ae",
    "outputs": [],
@@ -458,7 +458,7 @@
   {
    "metadata": {},
    "cell_type": "code",
-   "source": "leaderboard.T.round(2).sort_values(\"rMAE\")",
+   "source": "ed_leaderboard.T.round(2).sort_values(\"rMAE\")",
    "id": "edb26327f91c508b",
    "outputs": [],
    "execution_count": null
@@ -467,7 +467,7 @@
    "metadata": {},
    "cell_type": "code",
    "source": [
-    "fig = leaderboard.T.sort_values(\"rMAE\", ascending=False).rMAE.plot(kind='barh', figsize=(10, 5), title='Leaderboard', xlabel='rMAE')\n",
+    "fig = ed_leaderboard.T.sort_values(\"rMAE\", ascending=False).rMAE.plot(kind='barh', figsize=(10, 5), title='Electricity Demand Leaderboard', xlabel='rMAE')\n",
     "plt.show()"
    ],
    "id": "ca53db6a92e74387",