def _get_training_data_y(self):
data_getter = DataGetter()
config.DF_BASE_START_DATE = config.TRAINING_DATE_START
config.DF_BASE_END_DATE = config.TRAINING_DATE_END
df_result = data_getter.get_deltas()
df_result = df_result[config.TRAINING_DATA_TARGET]
y = df_result.values
if self.X is None:
raise Exception(
'X needs to be defined before defining Y. Run _get_training_data_x before this method.'
)
y = y[0:self.X.shape[0]]
y = self._one_hot_encode(y, 2)
config.DF_BASE_START_DATE = config.VALIDATION_DATE_START
config.DF_BASE_END_DATE = config.VALIDATION_DATE_END
df_result = data_getter.get_deltas()
df_result = df_result[config.TRAINING_DATA_TARGET]
y_val = df_result.values
if self.X_val is None:
raise Exception(
'X needs to be defined before defining Y. Run _get_training_data_x before this method.'
)
y_val = y_val[0:self.X_val.shape[0]]
y_val = self._one_hot_encode(y_val, 2)
return y, y_val
def test_get_deltas(self):
data_getter = DataGetter()
df_result = data_getter.get_deltas()
self.assertIsInstance(
df_result, pd.DataFrame,
"There was an issue calculating the delta values.")
df_result.to_excel("../output/df_deltas.xlsx")
def _get_testing_data_y(self):
data_getter = DataGetter()
df_result = data_getter.get_deltas()
df_result = df_result[config.TRAINING_DATA_TARGET]
y = df_result.values
if self.X is None:
raise Exception(
'X needs to be defined before defining Y. Run _get_testing_data_x before this method.'
)
y = y[0:self.X.shape[0]]
y = self._one_hot_encode(y, 2)
return y
