diff --git a/extract_HydroSig.py b/extract_HydroSig.py
index 0a52924aa3f52d99b5b7f30bd097eae7ee177c5a..07cca94d7b86143f96394537adcc8d2acf79b7d7 100644
--- a/extract_HydroSig.py
+++ b/extract_HydroSig.py
@@ -40,7 +40,8 @@ shp_contour = gpd.read_file(shp_contour_filepath)
 watershed_code = df_stations.loc[:,'Code']
 # Get a sample of them for test
 code_for_test = watershed_code.loc[1:2]
-# code_for_test = ['A1080330']
+# code_for_test = ['A1072010', 'A1080330']
+# code_for_test = ['A1072010', 'A1080330', 'A3472010', 'I0102010', 'J3413030']
 
 # # extract safran gpd
 # from HydroClimaticFluxes import HydroClimaticFluxes
@@ -57,7 +58,7 @@ code_for_test = watershed_code.loc[1:2]
 studied_watersheds = pd.DataFrame()
 for i in code_for_test:
 #for i in watershed_code:
-    
+    print(i)
     # Get the station's name
     watershed_stations_i = df_stations[df_stations.loc[:, 'Code'] == i]
     watershed_name_i =  watershed_stations_i.loc[:, 'Nom'].values[0]
@@ -66,18 +67,18 @@ for i in code_for_test:
     watershed_i = Watershed(i, watershed_name_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.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.hydro_climatic_fluxes.safran_timeseries['Datetime'] =  pd.Timestamp.asm8
-    #print(pd.api.types.is_datetime64_ns_dtype(watershed_i.hydro_climatic_fluxes.safran_timeseries['Datetime']))
-    #print(pd.api.types.is_datetime64_ns_dtype(watershed_i.hydro_climatic_fluxes.discharge_timeseries['Datetime']))
+    
     watershed_i.extract_hydrological_signatures()
     watershed_i.extract_geologic_properties_from_filename(BDLisa_shp)
     watershed_i.geologic_properties.extract_average_age_geology(BRGM_geol_map, watershed_i.contour)