final version

summary_test.py

@@ -73,11 +73,12 @@ if __name__ == "__main__":
 
     temperature_df, rain_df, irradiance_df = process_all_data_for_meterological_summary(historical_df, forecast_df)
     
-    # meterological_summary = get_meterological_summary(scenario=scenario, 
-    #                                                   temperature_df=temperature_df,
-    #                                                   irradiance_df=irradiance_df,
-    #                                                   rain_df=rain_df)
-    # print(meterological_summary)
+    #######@
+    meterological_summary = get_meterological_summary(scenario=scenario, 
+                                                      temperature_df=temperature_df,
+                                                      irradiance_df=irradiance_df,
+                                                      rain_df=rain_df)
+    print(meterological_summary)
 
     climate_data = temperature_df.merge(rain_df, on='year').merge(irradiance_df, on='year') # meteo ok
     closest_soil_data = find_nearest_point_to_coordinates(latitude=lat, longitude=lon)  # soil ok
@@ -86,17 +87,17 @@ if __name__ == "__main__":
     # add a step to transform gps coordinates into french region to be able to filter yield data
     yield_past_data, yield_forecast_data = get_yield_data(region=region, culture=culture)
 
-    # rendement  (avec et sans ombrage)
+    # rendement (avec et sans ombrage)
     
-    # print(get_agricultural_yield_comparison(culture=culture, 
-    #                                         region="bourgogne franche comté",
-    #                                         water_df=water_deficit_data, 
-    #                                         climate_df=climate_data,
-    #                                         soil_df=closest_soil_data, 
-    #                                         forecast_yield_df=yield_forecast_data,
-    #                                         historical_yield_df=yield_past_data))
-
-    print(water_deficit_data)
+    second_summary = get_agricultural_yield_comparison(culture=culture, 
+                                            region="bourgogne franche comté",
+                                            water_df=water_deficit_data, 
+                                            climate_df=climate_data,
+                                            soil_df=closest_soil_data, 
+                                            forecast_yield_df=yield_forecast_data,
+                                            historical_yield_df=yield_past_data)
+
+    print(second_summary)
 
     # from utils.soil_utils import find_nearest_point
     # city = "Bourgogne Franche Comté"