Addeed more tests but passing correctly

davidusb-geek · Feb 4, 2024 · ca1151f · ca1151f
1 parent 70bea29
commit ca1151f
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Showing 2 changed files with 28 additions and 0 deletions.
diff --git a/tests/test_command_line_utils.py b/tests/test_command_line_utils.py
@@ -290,6 +290,7 @@ def test_forecast_model_fit_predict_tune(self):
                                               action, logger, get_data_from_file=True)
         self.assertTrue(input_data_dict['params']['passed_data']['model_type'] == 'load_forecast')
         self.assertTrue(input_data_dict['params']['passed_data']['sklearn_model'] == 'KNeighborsRegressor')
+        self.assertTrue(input_data_dict['params']['passed_data']['perform_backtest'] == False)
         # Check that the default params are loaded
         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)

diff --git a/tests/test_utils.py b/tests/test_utils.py
@@ -131,6 +131,19 @@ def test_treat_runtimeparams(self):
         runtimeparams.update({'custom_unit_load_cost_id':'my_custom_unit_load_cost_id'})
         runtimeparams.update({'custom_unit_prod_price_id':'my_custom_unit_prod_price_id'})
         runtimeparams.update({'custom_deferrable_forecast_id':'my_custom_deferrable_forecast_id'})
+        runtimeparams.update({'days_to_retrieve':15})
+        runtimeparams.update({'model_type':"my_special_model"})
+        runtimeparams.update({'var_model':"sensor.my_special_sensor"})
+        runtimeparams.update({'sklearn_model':"LinearRegression"})
+        runtimeparams.update({'num_lags':12})
+        runtimeparams.update({'split_date_delta':"24h"})
+        runtimeparams.update({'perform_backtest':True})
+        runtimeparams.update({'model_predict_entity_id':"sensor.my_custom_model_forecast"})
+        runtimeparams.update({'model_predict_unit_of_measurement':"kW"})
+        runtimeparams.update({'model_predict_friendly_name':"That friendly name"})
+        runtimeparams.update({'model_predict_unit_of_measurement':"kW"})
+        runtimeparams.update({'model_predict_unit_of_measurement':"kW"})
+        runtimeparams.update({'model_predict_unit_of_measurement':"kW"})
 
         runtimeparams_json = json.dumps(runtimeparams)
         retrieve_hass_conf, optim_conf, plant_conf = utils.get_yaml_parse(
@@ -167,6 +180,20 @@ def test_treat_runtimeparams(self):
         self.assertTrue(params['passed_data']['custom_unit_load_cost_id'] == 'my_custom_unit_load_cost_id')
         self.assertTrue(params['passed_data']['custom_unit_prod_price_id'] == 'my_custom_unit_prod_price_id')
         self.assertTrue(params['passed_data']['custom_deferrable_forecast_id'] == 'my_custom_deferrable_forecast_id')
+
+        self.assertTrue(params['passed_data']['days_to_retrieve'] == 15)
+        self.assertTrue(params['passed_data']['model_type'] == "my_special_model")
+        self.assertTrue(params['passed_data']['var_model'] == "sensor.my_special_sensor")
+        self.assertTrue(params['passed_data']['sklearn_model'] == "LinearRegression")
+        self.assertTrue(params['passed_data']['num_lags'] == 12)
+        self.assertTrue(params['passed_data']['split_date_delta'] == "24h")
+        self.assertTrue(params['passed_data']['perform_backtest'] == True)
+        self.assertTrue(params['passed_data']['model_predict_entity_id'] == "sensor.my_custom_model_forecast")
+        self.assertTrue(params['passed_data']['model_predict_unit_of_measurement'] == "kW")
+        self.assertTrue(params['passed_data']['model_predict_friendly_name'] == "That friendly name")
+        self.assertTrue(params['passed_data']['model_predict_unit_of_measurement'] == "kW")
+        self.assertTrue(params['passed_data']['model_predict_unit_of_measurement'] == "kW")
+        self.assertTrue(params['passed_data']['model_predict_unit_of_measurement'] == "kW")
 
     def test_treat_runtimeparams_failed(self):
         params = TestCommandLineUtils.get_test_params()