def test_fit_predict(self): powerForecaster = PowerForecaster(self.df, Models.LSTM) powerForecaster.fit() result = powerForecaster.predict() if self.interactive: plt.plot(result) self.assertTrue(True) plt.show()
def test_lstm(self): df = self.df.copy() powerForecaster = PowerForecaster(df, model=Models.LSTM, upsample_freq='8H') powerForecaster.block_after_date("2013-06-01") powerForecaster.adjust_index_and_training_shift( start_date_in_labeling_st="2012-11-02") powerForecaster.sliding_window() powerForecaster.fit() if self.interactive: powerForecaster.plot_history() powerForecaster.evaluate() model = powerForecaster.model_type.value df_predicted = powerForecaster.lstm_predict( model, start_date_to_predict_st="2013-6-01", duration_in_freq=3 * 30)
def test_fit_VAR(self): df = self.df.copy() powerForecaster = PowerForecaster(df, model=Models.VAR) powerForecaster.fit() predicted = powerForecaster.predict()