diff --git a/extract_HydroSig.py b/extract_HydroSig.py
index 796f77427600df56c949375eaee9b7bc8bd90a5e..d00ef12781df44ae6604fd471938aa5ab522cb9a 100644
--- a/extract_HydroSig.py
+++ b/extract_HydroSig.py
@@ -17,28 +17,16 @@ from Watershed import Watershed
# Banque Hydro
banquehydro_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Export2020/'
-# banquehydro_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Export2020/Stations/A1080330.csv'
# SAFRAN
-# safran_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/SAFRAN/daily/'
-# safran_grid_shpfilename = './TestData/SAFRAN/maille_meteo_fr_pr93.shp'
safran_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/SAFRAN/'
# GEOL
-# BDLisa_shp = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BD_Lisa/RegionalHydrogeologyAnalysisMe/BD_Lisa_regionalhydrogeology.shp'
BDLisa_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEOL/BDLisa/'
-# BRGM_geol_map = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/CarteGeolBRGM/FR_vecteur/FR_vecteur/GEO001M_CART_FR_S_FGEOL_2154.shp'
BRGM_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEOL/BRGM/'
# Watersheds
-# shp_stations_filepath = 'E:/DonneesLaura/BanqueHydro/Shapes/StationBHYDRO_L93.shp'
-# df_stations_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/StationsNonInfluenceesExplore2/Synthèse analyses/Synthèse_meta_selection_624.csv'
-# shp_contour_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Shapes/BassinsVersantsMetropole/BV_4207_stations.shp'
-
-# df_stations = pd.read_csv(df_stations_filepath, sep = ';', encoding='latin-1')
-# shp_contour = gpd.read_file(shp_contour_filepath)
-
shp_watersheds_path = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/complete_df_wrong_geometries.shp'
shp_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEOMETRY/'
@@ -47,25 +35,15 @@ shp_watersheds = gpd.read_file(shp_watersheds_path)
# List of the stations'codes
watershed_code = shp_watersheds.loc[:,'Code']
# Get a sample of them for test
-code_for_test = watershed_code.loc[0:3]
-# code_for_test = ['A1072010', 'A1080330']
-# code_for_test = ['A1072010', 'A1080330', 'A3472010', 'I0102010', 'J3413030']
-
-# # extract safran gpd
-# from HydroClimaticFluxes import HydroClimaticFluxes
-# HCF = HydroClimaticFluxes(code=-1)
-# # Ptot_gpd = HCF.extract_safran_variable(safran_foldername, 'Ptot')
-# ET0_gpd = HCF.extract_safran_variable(safran_foldername, 'ET0')
-# Tair_gpd = HCF.extract_safran_variable(safran_foldername, 'Tair')
-# Snow_gpd = HCF.extract_safran_variable(safran_foldername, 'Snow')
-# Rain_gpd = HCF.extract_safran_variable(safran_foldername, 'Rain')
+# code_for_test = watershed_code.loc[0:3]
+
# *************************** Extract watersheds' properties ************************************
studied_watersheds = pd.DataFrame()
-for i in code_for_test:
-#for i in watershed_code:
+# for i in code_for_test:
+for i in watershed_code:
# Get the station's name
watershed_stations_i = shp_watersheds[shp_watersheds.loc[:, 'Code'] == i]
watershed_name_i = watershed_stations_i.loc[:, 'Nom'].values[0]
@@ -74,24 +52,13 @@ for i in code_for_test:
watershed_i = Watershed(i, watershed_name_i)
shpfile_contour_i = gpd.read_file(shp_foldername+i+'.shp')
watershed_i.contour = shpfile_contour_i
- # watershed_i.extract_watershed_contour_from_filename(shp_contour_filepath, 'Code')
- watershed_i.extract_banquehydro_discharge_timeseries(banquehydro_foldername)
-
- # watershed_i.extract_SAFRAN_forcings(safran_foldername, safran_grid_shpfilename)
- # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Ptot_gpd, watershed_i.contour,'Ptot')
- # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(ET0_gpd, watershed_i.contour, 'ET0')
- # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Tair_gpd, watershed_i.contour, 'Tair')
- # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Snow_gpd, watershed_i.contour, 'Snow')
- # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Rain_gpd, watershed_i.contour, 'Rain')
- # watershed_i.hydro_climatic_fluxes.safran_timeseries['Ptot'] = watershed_i.hydro_climatic_fluxes.safran_timeseries['Snow'] + watershed_i.hydro_climatic_fluxes.safran_timeseries['Rain']
+ watershed_i.extract_banquehydro_discharge_timeseries(banquehydro_foldername)
safran_timeseries_i = pd.read_csv(safran_foldername+i+'_safran_timeseries.csv')
watershed_i.hydro_climatic_fluxes.safran_timeseries = safran_timeseries_i
-
watershed_i.extract_hydrological_signatures()
- # watershed_i.extract_geologic_properties_from_filename(BDLisa_shp)
+
watershed_i.extract_geologic_properties_from_filename(BDLisa_filepath+i+'_BDLisa.shp')
- # watershed_i.geologic_properties.extract_average_age_geology(BRGM_geol_map, watershed_i.contour)
watershed_i.geologic_properties.extract_average_age_geology(BRGM_filepath+i+'_BRGM.shp')
# Create a dictionnary and fill the dataframe
@@ -103,16 +70,20 @@ for i in code_for_test:
# And save it
-# studied_watersheds.to_csv('4_stations_df_shp.csv', index=False)
+# studied_watersheds.to_csv('4_stations_df_BDLisa_IDpb_solved.csv', index=False)
+
+
+
-df_v0 = pd.read_csv('4_stations_df_v0.csv')
-df_shp = pd.read_csv('4_stations_df_shp_read_from_files.csv')
-df_brgm = pd.read_csv('4_stations_df_shpANDbrgm_read_from_files.csv')
-df_bdlisa = pd.read_csv('4_stations_df_shpANDbrgmANDbdlisa_read_from_files.csv')
+# df_v0 = pd.read_csv('4_stations_df_v0.csv')
+# df_shp = pd.read_csv('4_stations_df_shp_read_from_files.csv')
+# df_brgm = pd.read_csv('4_stations_df_shpANDbrgm_read_from_files.csv')
+# df_bdlisa = pd.read_csv('4_stations_df_shpANDbrgmANDbdlisa_read_from_files.csv')
-# Few plots for test
-df_some_stations_path = 'few_stations_df.csv'
-df_some_stations = pd.read_csv(df_some_stations_path)
+
+# ## Few plots for test
+# df_some_stations_path = 'few_stations_df.csv'
+# df_some_stations = pd.read_csv(df_some_stations_path)
# # bf indices
# sns.relplot(x="q_mean", y="bfi", hue="maingeol_description", data=df_some_stations)
@@ -125,9 +96,99 @@ df_some_stations = pd.read_csv(df_some_stations_path)
-
# all_watershed = shp_contour.plot(color='white', edgecolor='#f4a460')
# problematic_watershed = shp_contour[shp_contour.Code=="A7821010"]
# problematic_watershed.plot(ax=all_watershed, color='blue');
+
+
+
+# ## PREVIOUS VERSION
+
+# # **************************** Data *****************************
+
+# # Banque Hydro
+# banquehydro_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Export2020/'
+# # banquehydro_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Export2020/Stations/A1080330.csv'
+
+# # SAFRAN
+# # safran_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/SAFRAN/daily/'
+# # safran_grid_shpfilename = './TestData/SAFRAN/maille_meteo_fr_pr93.shp'
+# safran_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/SAFRAN/'
+
+# # GEOL
+# # BDLisa_shp = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BD_Lisa/RegionalHydrogeologyAnalysisMe/BD_Lisa_regionalhydrogeology.shp'
+# BDLisa_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEOL/BDLisa/'
+
+# # BRGM_geol_map = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/CarteGeolBRGM/FR_vecteur/FR_vecteur/GEO001M_CART_FR_S_FGEOL_2154.shp'
+# BRGM_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEOL/BRGM/'
+
+# # Watersheds
+# # shp_stations_filepath = 'E:/DonneesLaura/BanqueHydro/Shapes/StationBHYDRO_L93.shp'
+# # df_stations_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/StationsNonInfluenceesExplore2/Synthèse analyses/Synthèse_meta_selection_624.csv'
+# # shp_contour_filepath = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Shapes/BassinsVersantsMetropole/BV_4207_stations.shp'
+
+# # df_stations = pd.read_csv(df_stations_filepath, sep = ';', encoding='latin-1')
+# # shp_contour = gpd.read_file(shp_contour_filepath)
+
+# shp_watersheds_path = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/complete_df_wrong_geometries.shp'
+# shp_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEOMETRY/'
+
+# shp_watersheds = gpd.read_file(shp_watersheds_path)
+
+# # List of the stations'codes
+# watershed_code = shp_watersheds.loc[:,'Code']
+# # Get a sample of them for test
+# code_for_test = watershed_code.loc[0:3]
+# # code_for_test = ['A1072010', 'A1080330']
+# # code_for_test = ['A1072010', 'A1080330', 'A3472010', 'I0102010', 'J3413030']
+
+# # # extract safran gpd
+# # from HydroClimaticFluxes import HydroClimaticFluxes
+# # HCF = HydroClimaticFluxes(code=-1)
+# # # Ptot_gpd = HCF.extract_safran_variable(safran_foldername, 'Ptot')
+# # ET0_gpd = HCF.extract_safran_variable(safran_foldername, 'ET0')
+# # Tair_gpd = HCF.extract_safran_variable(safran_foldername, 'Tair')
+# # Snow_gpd = HCF.extract_safran_variable(safran_foldername, 'Snow')
+# # Rain_gpd = HCF.extract_safran_variable(safran_foldername, 'Rain')
+
+# # *************************** Extract watersheds' properties ************************************
+
+
+# studied_watersheds = pd.DataFrame()
+# for i in code_for_test:
+# #for i in watershed_code:
+# # Get the station's name
+# watershed_stations_i = shp_watersheds[shp_watersheds.loc[:, 'Code'] == i]
+# watershed_name_i = watershed_stations_i.loc[:, 'Nom'].values[0]
+
+# # Create waterhed object and extract its properties
+# watershed_i = Watershed(i, watershed_name_i)
+# shpfile_contour_i = gpd.read_file(shp_foldername+i+'.shp')
+# watershed_i.contour = shpfile_contour_i
+# # watershed_i.extract_watershed_contour_from_filename(shp_contour_filepath, 'Code')
+# watershed_i.extract_banquehydro_discharge_timeseries(banquehydro_foldername)
+
+# # watershed_i.extract_SAFRAN_forcings(safran_foldername, safran_grid_shpfilename)
+# # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Ptot_gpd, watershed_i.contour,'Ptot')
+# # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(ET0_gpd, watershed_i.contour, 'ET0')
+# # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Tair_gpd, watershed_i.contour, 'Tair')
+# # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Snow_gpd, watershed_i.contour, 'Snow')
+# # watershed_i.hydro_climatic_fluxes.intersect_safran_gpd_and_contour(Rain_gpd, watershed_i.contour, 'Rain')
+# # watershed_i.hydro_climatic_fluxes.safran_timeseries['Ptot'] = watershed_i.hydro_climatic_fluxes.safran_timeseries['Snow'] + watershed_i.hydro_climatic_fluxes.safran_timeseries['Rain']
+
+# safran_timeseries_i = pd.read_csv(safran_foldername+i+'_safran_timeseries.csv')
+# watershed_i.hydro_climatic_fluxes.safran_timeseries = safran_timeseries_i
+
+# watershed_i.extract_hydrological_signatures()
+# # watershed_i.extract_geologic_properties_from_filename(BDLisa_shp)
+# watershed_i.extract_geologic_properties_from_filename(BDLisa_filepath+i+'_BDLisa.shp')
+# # watershed_i.geologic_properties.extract_average_age_geology(BRGM_geol_map, watershed_i.contour)
+# watershed_i.geologic_properties.extract_average_age_geology(BRGM_filepath+i+'_BRGM.shp')
+
+# # Create a dictionnary and fill the dataframe
+# watershed_dict = watershed_i.to_dict()
+# studied_watersheds = studied_watersheds.append(watershed_dict, ignore_index=True)
+
+