[slides] final plots for the slide "climat and avalanche"

projects/exceeding_snow_loads/presentation/accumulation_in_winter.py

 import matplotlib.pyplot as plt
 from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal, CrocusDepth
 from extreme_data.meteo_france_data.scm_models_data.crocus.crocus_variables import AbstractSnowLoadVariable
+from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day
 
 ax = plt.gca()
 fontsize = 20
 altitude = 1800
-studies = [CrocusSnowLoadTotal(altitude=altitude), CrocusDepth(altitude=altitude)]
+# studies = [CrocusSnowLoadTotal(altitude=altitude), CrocusDepth(altitude=altitude)]
+studies = [SafranSnowfall1Day(altitude=altitude), CrocusDepth(altitude=altitude)]
 colors = ['black', 'grey']
 for i, study in enumerate(studies):
     color = colors[i]
@@ -18,7 +20,10 @@ for i, study in enumerate(studies):
     days = [d[5:] for d in study.year_to_days[year]]
     x = list(range(len(days)))
     if i == 0:
-        ylabel = 'ground snow load ({})'.format(AbstractSnowLoadVariable.UNIT)
+        if isinstance(study, SafranSnowfall1Day):
+            ylabel = 'snowfall (mm)'
+        else:
+            ylabel = 'ground snow load ({})'.format(AbstractSnowLoadVariable.UNIT)
     else:
         ylabel = 'snow depth (m)'
     ax.set_ylabel(ylabel, fontsize=fontsize)

projects/exceeding_snow_loads/presentation/main_example_snow_depth_total_plot.py

@@ -13,7 +13,7 @@ def tuples_for_examples_paper1(examples_for_the_paper=True):
 
         marker_altitude_massif_name_for_paper1 = [
             # ('magenta', 900, 'Ubaye'),
-            ('darkblue', 1800, 'Vercors'),
+            ('darkblue', 900, 'Chartreuse'),
             # ('mediumpurple', 2700, 'Beaufortain'),
         ]
     else:

projects/exceeding_snow_loads/presentation/statistical_model.py

@@ -33,28 +33,30 @@ def histogram_for_gev():
     from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusDepth
     ax = plt.gca()
     study_class = CrocusDepth
-    study = study_class(altitude=1800)
-    s = study.observations_annual_maxima.df_maxima_gev.loc['Vercors']
+    study = study_class(altitude=900)
+    s = study.observations_annual_maxima.df_maxima_gev.loc['Chartreuse']
     x_gev = s.values
     gev_params = fitted_stationary_gev(x_gev)
     print(gev_params.return_level(return_period=50))
     samples = gev_params.sample(10000)
-    nb = 10
+    nb = 12
     epsilon = 0.0
-    x, bins, p = ax.hist(samples, bins=nb, color='white', edgecolor='grey', density=True, stacked=True,
-                         linewidth=3, bottom=[-epsilon for _ in range(nb)])
+    x, bins, p = ax.hist(samples, bins=[0.25 * i for i in range(10)],
+                         color='white', edgecolor='grey', density=True, stacked=True,
+                         linewidth=3)
     for item in p:
         item.set_height((item.get_height() / sum(x)))
-    # print(gev_params)
+    print(gev_params)
     # x = np.linspace(0.0, 10, 1000)
     # y = gev_params.density(x)
     # ax.plot(x, y, linewidth=5)
     ax.set_xlabel('Annual maximum of snow depth (m)', fontsize=15)
     ax.set_ylabel('Probability', fontsize=15)
     ax.tick_params(axis='both', which='major', labelsize=15)
-    ax.set_yticks([0, 0.1, 0.2, 0.3])
-    ax.set_xlim([0, 2.5])
-    ax.set_ylim([0, 0.3])
+    ax.set_yticks([0.1 * j for j in range(4)])
+    ax.set_xticks([0.5 * j for j in range(5)])
+    ax.set_xlim([0, 2])
+    ax.set_ylim([0, 0.36])
 
 
 def histogram_for_normal():