Fix - Added more unittest for passing data as list

CHANGELOG.md

@@ -4,7 +4,8 @@
 ### Improvement
 - Improving documentation, added more information on forecast page.
 - Added support for SolCast PV production forecasts. 
-- Added possibility to pass some optimization parameters at runtime
+- Added possibility to pass some optimization parameters at runtime.
+- Added some unittest for passing data as list testing.
 ### Fix
 - Fixed small bug on webserver using pandas sum function for non numeric data. This was throwing the following message: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated.
 
@@ -259,6 +260,10 @@
 [0.3.9]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.9
 [0.3.11]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.11
 [0.3.13]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.13
+[0.3.14]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.14
+[0.3.15]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.15
+[0.3.16]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.16
+[0.3.17]: https://github.com/davidusb-geek/emhass/releases/tag/v0.3.17
 
 # Notes
 All notable changes to this project will be documented in this file.

tests/test_command_line_utils.py

@@ -139,6 +139,10 @@ def test_set_input_data_dict(self):
         self.assertIsInstance(input_data_dict['df_input_data_dayahead'], pd.DataFrame)
         self.assertTrue(input_data_dict['df_input_data_dayahead'].index.freq is not None)
         self.assertTrue(input_data_dict['df_input_data_dayahead'].isnull().sum().sum()==0)
+        self.assertTrue(input_data_dict['fcst'].optim_conf['weather_forecast_method']=='list')
+        self.assertTrue(input_data_dict['fcst'].optim_conf['load_forecast_method']=='list')
+        self.assertTrue(input_data_dict['fcst'].optim_conf['load_cost_forecast_method']=='list')
+        self.assertTrue(input_data_dict['fcst'].optim_conf['prod_price_forecast_method']=='list')
         action = 'publish-data'
         input_data_dict = set_input_data_dict(config_path, base_path, costfun, self.params_json, self.runtimeparams_json, 
                                               action, logger, get_data_from_file=True)
@@ -175,6 +179,14 @@ def test_set_input_data_dict(self):
         self.assertTrue(input_data_dict['df_input_data_dayahead'].index.freq is not None)
         self.assertTrue(input_data_dict['df_input_data_dayahead'].isnull().sum().sum()==0)
         self.assertTrue(len(input_data_dict['df_input_data_dayahead'])==10) # The default value for prediction_horizon
+        # action = 'dayahead-optim'
+        # input_data_dict = set_input_data_dict(config_path, base_path, costfun, params_json, runtimeparams_json, 
+        #                                       action, logger, get_data_from_file=True)
+        # self.assertIsInstance(input_data_dict, dict)
+        # self.assertIsInstance(input_data_dict['df_input_data_dayahead'], pd.DataFrame)
+        # self.assertTrue(input_data_dict['df_input_data_dayahead'].index.freq is not None)
+        # self.assertTrue(input_data_dict['df_input_data_dayahead'].isnull().sum().sum()==0)
+        # self.assertTrue(len(input_data_dict['df_input_data_dayahead'])==10) # The default value for prediction_horizon
 
     def test_dayahead_forecast_optim(self):
         config_path = pathlib.Path(root+'/config_emhass.yaml')