def _predict_fitted_time_series(self) -> Dict[str, pd.DataFrame]:
prediction_dictionary = {}
if self.level == 0:
prediction_dictionary = super()._predict_fitted_time_series()
elif self.level == max(list(self.level_nodes.keys())):
prediction_dictionary = HierarchicalBottomUp._predict_fitted_time_series(
self)
else:
self._predict_time_series_top_down(prediction_dictionary)
self._predict_fitted_time_series_bottom_up(prediction_dictionary)
return prediction_dictionary
def _predict_new_time_series(self,
X: pd.DataFrame) -> Dict[str, pd.DataFrame]:
new_time_series_dictionary = {}
if self.level == 0:
new_time_series_dictionary = HierarchicalTopDown._predict_new_time_series(
self, X)
elif self.level == max(list(self.level_nodes.keys())):
new_time_series_dictionary = HierarchicalBottomUp._predict_new_time_series(
self, X)
else:
self._predict_time_series_top_down(new_time_series_dictionary, X)
self._predict_new_time_series_bottom_up(new_time_series_dictionary,
X)
return new_time_series_dictionary
def test_constructor(self, time_series_forecasting_model1_no_cache,
dataframes):
tree = tree_construction(dataframes)
HierarchicalBottomUp(time_series_forecasting_model1_no_cache, tree)
def test_basic_constructor(self, time_series_forecasting_model1_no_cache):
HierarchicalBottomUp(model=time_series_forecasting_model1_no_cache,
hierarchy_tree='infer')
def hierarchical_basic_bottom_up_model(
time_series_forecasting_model1_no_cache):
return HierarchicalBottomUp(time_series_forecasting_model1_no_cache,
'infer')
def hierarchical_bottom_up_model(draw,
time_series_forecasting_model1_no_cache):
dataframes = draw(n_time_series_with_same_index(min_n=5))
tree = draw(tree_construction(dataframes))
return HierarchicalBottomUp(time_series_forecasting_model1_no_cache, tree)