Merge branch '107-feature-save-time-series-of-mean-variables-in-a-csv-file' into 'develop'

Resolve "[feature] Save time series of mean variables in a csv file"

See merge request !29

MODULES/DATA_MANAGEMENT/output/save_csv.py

+import pandas as pd
+import numpy as np
+import os
+
+def save_csv(filename, nyears_data, variables):
+    """
+    Save the mean values of the variables in the nyears_data dictionary to a CSV file.
+    
+    Args:
+        filename: The name of the CSV file to save.
+        filename type: str
+        nyears_data: A dictionary containing the data for each year.
+        nyears_data type: dict
+        variables: A list of variables to save.
+        variables type: list
+    """
+    records = []
+    
+    for year in nyears_data:
+        missing_var = []
+        for var in variables:
+            if var in nyears_data[year]:  # Ensure the variable exists in the dictionary
+                for date, array in nyears_data[year][var].items():
+                    mean_value = np.mean(array)
+                    records.append((date, var, mean_value))
+            else:
+                missing_var.append(var)
+        if missing_var:
+            print(f'Warning: variable(s) {missing_var} not in nyears_data for year {year}')
+    
+    # Create a DataFrame
+    df = pd.DataFrame(records, columns=['Date', 'Variable', 'Mean'])
+    df['Date'] = pd.to_datetime(df['Date'])  # Convert to datetime
+    df = df.pivot(index='Date', columns='Variable', values='Mean')  # Reshape to have variables as columns
+    
+    # Save to CSV
+    filepath = os.path.join('OUTPUTS', filename)
+    df.to_csv(filepath)
+    print('saved to', filepath)

main.py

@@ -13,6 +13,7 @@ import pickle
 from MODULES.user_support_tools import PASE_Logger
 from MODULES.DATA_MANAGEMENT.yaml_inputs_provider import YAML_Inputs_provider, Inputs_aggregator
 from MODULES.DATA_MANAGEMENT.weather_data_provider import Weather_data
+from MODULES.DATA_MANAGEMENT.output.save_csv import save_csv
 from MODULES.PHOTOVOLTAICS.configuration import PV_Configuration_3D
 from MODULES.ENVIRONMENT.light import Sun_positions_sampled, Sun_positions, Light
 from MODULES.ENVIRONMENT.light import show_light_map2, Ray_casting_scene
@@ -200,6 +201,8 @@ Soil_plot, Crop_plot = run_crop_simu(crop_config, option_2D, WD.nyears_daily_dat
                                      L.daily_irr_spat,
                                      Loc_1)
 
+save_csv('mean_data.csv', Crop_plot.nyears_data, ['Biomass', 'Dry_yield'])
+
 show_light_map2(L.sourcepoints[:,:-1], 
                 Crop_plot[0].nyears_data['2008']['BM'][datetime.strptime('2008-10-10 00:00:00', '%Y-%m-%d %H:%M:%S')]/100,
                 PV_1_3Dconfig.PV_central_PD,