Merge branch 'master' of https://gitlab.irstea.fr/jean.marcais/fhysa

extract_HydroSig.py

+# -*- coding: utf-8 -*-
+"""
+Created on Mon Mar 15 12:34:40 2021
+
+@author: laura.lindeperg
+"""
+
+import geopandas as gpd
+import pandas as pd
+import seaborn as sns
+from Watershed import Watershed
+
+
+
+
+# **************************** Data *****************************
+
+# Banque Hydro
+banquehydro_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BanqueHydro/Export2020/'
+
+# SAFRAN
+safran_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/SAFRAN/daily/'
+# safran_grid_shpfilename = './TestData/SAFRAN/maille_meteo_fr_pr93.shp'
+
+# GEOL
+BDLisa_shp = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/BD_Lisa/RegionalHydrogeologyAnalysisMe/BD_Lisa_regionalhydrogeology.shp'
+
+BRGM_geol_map = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/CarteGeolBRGM/FR_vecteur/FR_vecteur/GEO001M_CART_FR_S_FGEOL_2154.shp'
+
+# 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)
+# List of the stations'codes
+watershed_code = df_stations.loc[:,'Code']
+# Get a sample of them for test
+code_for_test = watershed_code.loc[1:10]
+
+
+
+# *************************** 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 = df_stations[df_stations.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)
+    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.extract_SAFRAN_forcings(safran_foldername)
+    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)
+    
+    # Create a dictionnary and fill the dataframe
+    watershed_dict = watershed_i.to_dict()
+    studied_watersheds = studied_watersheds.append(watershed_dict, ignore_index=True)
+
+
+
+
+
+# And save it
+# studied_watersheds.to_csv('few_stations_df.csv', index=False)
+
+
+# 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)
+sns.relplot(x="bfi", y="bf_magni", hue="maingeol_description", data=df_some_stations)
+
+ # recession indices
+sns.relplot(x="q_mean", y="tau_1", hue="maingeol_description", data=df_some_stations)
+sns.relplot(x="q_mean", y="tau_2", hue="maingeol_description", data=df_some_stations)
+sns.relplot(x="tau_1", y="tau_2", hue="maingeol_description", data=df_some_stations)
+
+
+
+
+# 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');
+
+