prinzkafka
commented
8 months ago - Retrieving data from hass for load forecast using method = mlforecaster 2023-10-20 21:30:02,764 - web_server - INFO - Retrieve hass get data method initiated... /usr/local/lib/python3.9/dist-packages/sklearn/base.py:348: InconsistentVersionWarning: Trying to unpickle estimator KNeighborsRegressor from version 1.3.0 when using version 1.3.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to: https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations warnings.warn( 2023-10-20 21:30:06,193 - web_server - ERROR - Exception on /action/dayahead-optim [POST] Traceback (most recent call last): File "/usr/local/lib/python3.9/dist-packages/flask/app.py", line 1455, in wsgi_app response = self.full_dispatch_request() File "/usr/local/lib/python3.9/dist-packages/flask/app.py", line 869, in full_dispatch_request rv = self.handle_user_exception(e) File "/usr/local/lib/python3.9/dist-packages/flask/app.py", line 867, in full_dispatch_request rv = self.dispatch_request() File "/usr/local/lib/python3.9/dist-packages/flask/app.py", line 852, in dispatch_request return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) File "/usr/local/lib/python3.9/dist-packages/emhass/web_server.py", line 179, in action_call input_data_dict = set_input_data_dict(config_path, str(data_path), costfun, File "/usr/local/lib/python3.9/dist-packages/emhass/command_line.py", line 91, in set_input_data_dict P_load_forecast = fcst.get_load_forecast(method=optim_conf['load_forecast_method']) File "/usr/local/lib/python3.9/dist-packages/emhass/forecast.py", line 615, in get_load_forecast forecast_out = mlf.predict(data_last_window) File "/usr/local/lib/python3.9/dist-packages/emhass/machine_learning_forecaster.py", line 206, in predict predictions = self.forecaster.predict(steps=self.lags_opt, File "/usr/local/lib/python3.9/dist-packages/skforecast/ForecasterAutoreg/ForecasterAutoreg.py", line 696, in predict if self.differentiation is not None: AttributeError: 'ForecasterAutoreg' object has no attribute 'differentiation'