batchh prediction and update does not work

v2/test_predictor_sktime.py

@@ -14,18 +14,34 @@ from sktime.forecasting.model_evaluation import evaluate
 from sktime.utils.plotting import plot_series
 
 
-# step 1: splitting historical data
-y = load_airline()
+from data_processing import read_datasets, add_production_field, interpolate_and_join, SolarParameters
 
-# forecaster = NaiveForecaster(strategy="last", sp=12)
-forecaster = AutoETS(auto=True, sp=12, n_jobs=-1)
-# forecaster = AutoARIMA(sp=12, suppress_warnings=True)
+
+parameters = SolarParameters()
+met_2021_data, cons_2021_data = read_datasets()
+add_production_field(met_2021_data, parameters)
+all_data = interpolate_and_join(met_2021_data, cons_2021_data)
+
+all_data['y'] = all_data['Consumption']
+y = all_data[['y']]
+y = y[y.index <= '2021-01-20']
+
+print(len(y['y']), "data points read")
+
+# 5 mins timestep means:
+period = 12*24
+
+forecaster = NaiveForecaster(strategy="last", sp=period)
+# forecaster = AutoETS(auto=True, sp=period, n_jobs=-1)
+# forecaster = AutoARIMA(sp=period, suppress_warnings=True)
 
 cv = ExpandingWindowSplitter(
-    step_length=12, fh=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], initial_window=72
+    step_length=period, fh=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], initial_window=period*10
+    # step_length=period, fh=[1, 2], initial_window=period*2
 )
 
-df = evaluate(forecaster=forecaster, y=y, cv=cv, strategy="refit", return_data=True)
+strategy = "no-update_params"
+df = evaluate(forecaster=forecaster, y=y, cv=cv, strategy=strategy, return_data=True)
 
 print(df['y_pred'])
 
@@ -43,7 +59,7 @@ fig, ax = plot_series(
 ax.legend()
 plt.show()
 
-
+exit()
 
 y_train, y_test = temporal_train_test_split(y, test_size=len(y.index) // 2)