def get_composite_chain():
chain = TsForecastingChain()
node_trend = PrimaryNode('trend_data_model')
node_model_trend = SecondaryNode('linear', nodes_from=[node_trend])
node_residual = PrimaryNode('residual_data_model')
node_model_residual = SecondaryNode('linear', nodes_from=[node_residual])
node_final = SecondaryNode(
'linear', nodes_from=[node_model_residual, node_model_trend])
chain.add_node(node_final)
return chain
data['Date'] = pd.to_datetime(data['Date'])
dataframe = data.copy()
chain = TsForecastingChain()
node_trend = PrimaryNode('trend_data_model')
node_trend.labels = ["fixed"]
node_lstm_trend = SecondaryNode('linear', nodes_from=[node_trend])
node_trend.labels = ["fixed"]
node_residual = PrimaryNode('residual_data_model')
node_ridge_residual = SecondaryNode('linear',
nodes_from=[node_residual])
node_final = SecondaryNode(
'linear', nodes_from=[node_ridge_residual, node_lstm_trend])
node_final.labels = ["fixed"]
chain.add_node(node_final)
print(f'Размер исходной цепочки {len(chain.nodes)}')
# Заполнение пропусков
gapfiller = ModelGapFiller(gap_value=-100.0, chain=chain)
with_gap_array = np.array(data['gap'])
withoutgap_arr = gapfiller.forward_filling(with_gap_array,
max_window_size=30)
dataframe['gap'] = withoutgap_arr
validate(parameter='Height',
mask='gap',
data=data,
withoutgap_arr=withoutgap_arr)
save_path = os.path.join(folder_to_save, file)