diff --git a/data_visualisation.py b/data_visualisation.py
index 350ce329f8b010285b1c8a6219b748a901b437ac..ce4fa5879275f59935b0fba674bd5d58ab92c4da 100644
--- a/data_visualisation.py
+++ b/data_visualisation.py
@@ -10,7 +10,7 @@ import geopandas as gpd
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
-
+import numpy as np
# **************************** Data *****************************
@@ -36,15 +36,22 @@ shp_foldername = 'C:/Users/laura.lindeperg/Documents/DonneesLaura/Watersheds/GEO
shp_watersheds = gpd.read_file(shp_watersheds_path)
# Geol
-df_geol_path = '613_stations_geol_df.csv'
+df_geol_path = 'C:/Users/laura.lindeperg/Documents/INRAE_2021/CODE/fhysa/613_stations_geol_df.csv'
df_geol = pd.read_csv(df_geol_path)
+# Geomorpho
+df_geomorpho_path = 'C:/Users/laura.lindeperg/Documents/INRAE_2021/CODE/fhysa/DeltaV.csv'
+df_geomorpho = pd.read_csv(df_geomorpho_path)
+
+delta_v = df_geomorpho.loc[:, ['Code', 'DeltaV']].rename(columns = {'Code':'code'})
# Transform in long-form data structure
df_hydro_sig = df_hydro_sig.drop(columns = ['name'])
df_hydro_sig_long = df_hydro_sig.melt(id_vars = ['code'], var_name = 'hydro_sig')
my_df = pd.merge(df_hydro_sig_long, df_geol, on = 'code', how = 'outer')
+# my_df = pd.merge(my_df, delta_v, on = 'code', how = 'outer')
+
# Merge hydrological signatures with geometry file
shp_watersheds = shp_watersheds.rename(columns = {'Code':'code'})
@@ -61,14 +68,34 @@ my_geol = df_geol.loc[df_geol.loc[:, 'maingeol_proportion'] > 0.70]
my_df = my_df.loc[my_df.loc[:, 'code'].isin(my_geol.loc[:,'code'])==True]
-# Exclude catchments which disturb scales
-my_df = my_df.loc[my_df.loc[:,'code'].isin(['K6492510', 'V2814020', 'P7041510', 'A9001050', 'H8043310', 'H4033010']) == False]
+# # Exclude catchments which disturb scales
+# my_df = my_df.loc[my_df.loc[:,'code'].isin(['K6492510', 'V2814020', 'P7041510', 'A9001050', 'H8043310', 'H4033010']) == False]
# **************************** Plots *****************************
+# my_df.value=np.log(my_df.value)
+sns.relplot(x='DeltaV', y='DeltaV', hue = 'maingeol_description', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'q_mean'])
+sns.boxplot(x='maingeol_description', y='DeltaV', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'q_mean']).tick_params(axis='x', labelrotation=45)
+
+df_geol = df_geol.loc[:, ['code', 'maingeol_description']]
+my_data = pd.merge(df_hydro_sig, df_geol)
+viz = sns.PairGrid(data=my_data, hue='maingeol_description')
+viz.map(sns.scatterplot)
+viz.add_legend()
+
+# viz.map_diag(sns.histplot)
+# viz.map_offdiag(sns.scatterplot)
+# viz.add_legend()
+
+
+
+
+
+
+
## Boxplot of the hydrological signatures
figure, axes = plt.subplots(4, 4, figsize = (17, 17))
@@ -110,8 +137,8 @@ axes[3, 3].axis("off")
## Boxplot of the hydrological signatures from their main hydrogeologic type perspective
-figure, axes = plt.subplots(4, 4, figsize = (17, 17))
-figure.suptitle('Hydrological signatures')
+figure, axes = plt.subplots(4, 4, figsize = (17, 17), sharex=True)
+# figure.suptitle('Hydrological signatures')
axes[0, 0].set_title('Qmean')
axes[0, 1].set_title('Aridity ratio')
axes[0, 2].set_title('Runoff ratio')
@@ -127,20 +154,20 @@ axes[2, 3].set_title('tau 2')
axes[3, 0].set_title('tau Roques')
axes[3, 1].set_title('BFI 90')
-sns.boxplot(ax=axes[0, 0], x='hydro_sig', y='value', hue = 'maingeol_description', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'q_mean'])
-sns.boxplot(ax=axes[0, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'aridity_ratio'])
-sns.boxplot(ax=axes[0, 2], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'runoff_ratio'])
-sns.boxplot(ax=axes[0, 3], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'bfi_5'])
-sns.boxplot(ax=axes[1, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'bf_magni'])
-sns.boxplot(ax=axes[1, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'a_q'])
-sns.boxplot(ax=axes[1, 2], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'b_q'])
-sns.boxplot(ax=axes[1, 3], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'fdc_quantile10'])
-sns.boxplot(ax=axes[2, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'fdc_quantile90'])
-sns.boxplot(ax=axes[2, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'fdc_slope'])
-sns.boxplot(ax=axes[2, 2], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'tau_1'])
-sns.boxplot(ax=axes[2, 3], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'tau_2'])
-sns.boxplot(ax=axes[3, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'tau_roques'])
-sns.boxplot(ax=axes[3, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'bfi_90'])
+ax00 = sns.boxplot(ax=axes[0, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'q_mean']).legend('off')
+ax01 = sns.boxplot(ax=axes[0, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'aridity_ratio'])
+ax02 = sns.boxplot(ax=axes[0, 2], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'runoff_ratio'])
+ax03 = sns.boxplot(ax=axes[0, 3], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'bfi_5'])
+ax10 = sns.boxplot(ax=axes[1, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'bf_magni'])
+ax11 = sns.boxplot(ax=axes[1, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'a_q'])
+ax12 = sns.boxplot(ax=axes[1, 2], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'b_q'])
+ax13 = sns.boxplot(ax=axes[1, 3], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'fdc_quantile10'])
+ax20 = sns.boxplot(ax=axes[2, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'fdc_quantile90'])
+ax21 = sns.boxplot(ax=axes[2, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'fdc_slope'])
+ax22 = sns.boxplot(ax=axes[2, 2], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'tau_1'])
+ax23 = sns.boxplot(ax=axes[2, 3], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'tau_2'])
+ax30 = sns.boxplot(ax=axes[3, 0], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'tau_roques'])
+ax31 = sns.boxplot(ax=axes[3, 1], x='maingeol_description', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'bfi_90'])
axes[3, 2].axis("off")
axes[3, 3].axis("off")
@@ -202,7 +229,7 @@ axes[3, 3].axis("off")
-
+# En vrac - ne fonctionne pas toujours
sns.relplot(x='value', y='value', data=my_df.loc[my_df.loc[:, 'hydro_sig'] == 'a_q'])
@@ -237,7 +264,6 @@ sns.relplot(x="XL93", y="YL93", hue="value",
col="hydro_sig", col_wrap=2,
kind="scatter", data= my_df);
-# ## Few plots for test
# # bf indices