def _input_from_parents(self, input_data: InputData,
parent_operation: str,
max_tune_time: Optional[timedelta] = None,
verbose=False) -> InputData:
if len(self.nodes_from) == 0:
raise ValueError()
if verbose:
self.log.info(f'Fit all parent nodes in secondary node with model: {self.model}')
parent_nodes = self._nodes_from_with_fixed_order()
are_prev_nodes_affect_target = \
['affects_target' in parent_node.model_tags for parent_node in parent_nodes]
if any(are_prev_nodes_affect_target):
# is the previous model is the model that changes target
parent_results, target = _combine_parents_that_affects_target(parent_nodes, input_data,
parent_operation)
else:
parent_results, target = _combine_parents_simple(parent_nodes, input_data,
parent_operation, max_tune_time)
secondary_input = InputData.from_predictions(outputs=parent_results,
target=target)
return secondary_input
def test_data_from_predictions(output_dataset):
data_1 = output_dataset
data_2 = output_dataset
data_3 = output_dataset
target = output_dataset.predict
new_input_data = InputData.from_predictions(
outputs=[data_1, data_2, data_3])
assert new_input_data.features.all() == np.array(
[data_1.predict, data_2.predict, data_3.predict]).all()
def _input_from_parents(self, input_data: InputData,
parent_operation: str) -> InputData:
if len(self.nodes_from) == 0:
raise ValueError('No parent nodes found')
self.log.ext_debug(f'Fit all parent nodes in secondary node with operation: {self.operation}')
parent_nodes = self._nodes_from_with_fixed_order()
parent_results, target = _combine_parents(parent_nodes, input_data,
parent_operation)
secondary_input = InputData.from_predictions(outputs=parent_results)
return secondary_input
