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()