[refactor] update main_season_repartition_of_maxima.py to compare swe results,...

[refactor] update main_season_repartition_of_maxima.py to compare swe results, for safran 2019 and adamont v2, to show the limit of their indicator.

projects/archive/seasonal_analysis/main_season_repartition_of_maxima.py

@@ -4,21 +4,35 @@ import calendar
 
 import numpy as np
 
+from extreme_data.meteo_france_data.adamont_data.abstract_adamont_study import AbstractAdamontStudy
+from extreme_data.meteo_france_data.adamont_data.adamont.adamont_crocus import AdamontSwe
+from extreme_data.meteo_france_data.adamont_data.adamont_scenario import rcm_scenarios_extended, AdamontScenario
+from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusSweTotal
 from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day
 from extreme_data.meteo_france_data.scm_models_data.altitudes_studies import AltitudesStudies
 from extreme_trend.one_fold_fit.altitude_group import altitudes_for_groups, \
     get_altitude_group_from_altitudes
 
 
-def plot_season_repartition_of_maxima(studies, massif_names, title='', idx=0):
+def plot_season_repartition_of_maxima(studies, massif_names, title='', idx=0, projected=False):
 
 
     month_to_name = {month: calendar.month_name[month] for month in range(1, 13)}
 
     all_years = studies.study.ordered_years
-    title += ['-1959-2019', '-past-1959-1988', '-recent-1990-2019'][idx]
+    title += ' on the period '
+    if isinstance(studies.study, AbstractAdamontStudy):
+        assert studies.study.scenario is AdamontScenario.histo
+        title = 'Adamont v2\n' + title
+        title += ['HISTORICAL', '', ''][idx]
+        years = [all_years, all_years[:30], all_years[-30:]][idx]
+    else:
+        title = 'SAFRAN 2019\n' + title
+        title += ['1959-2019', '-past-1959-1988', '-recent-1990-2019'][idx]
+        years = [all_years, all_years[:30], all_years[-30:]][idx]
+
+
     color = ['grey', 'red', 'green'][idx]
-    years = [all_years, all_years[:30], all_years[-30:]][idx]
     ax = plt.gca()
     ax2 = ax.twinx()
 
@@ -27,7 +41,9 @@ def plot_season_repartition_of_maxima(studies, massif_names, title='', idx=0):
     ordered_months = [8, 9, 10, 11, 12] + [1, 2, 3, 4, 5, 6, 7]
     nb_total_maxima = sum([len(v) for v in month_to_maxima.values()])
     percentage_maxima = [100 * len(month_to_maxima[month]) / nb_total_maxima for month in ordered_months]
-    month_names = [month_to_name[m][:3] for m in ordered_months]
+    assert len(percentage_maxima) == 12
+    month_names = [month_to_name[m][:4] for m in ordered_months]
+    print(month_names)
     ax.bar(month_names, percentage_maxima, width=0.5,
            color=color, edgecolor=color, label='Percentage of maxima',
            linewidth=2)
@@ -36,10 +52,10 @@ def plot_season_repartition_of_maxima(studies, massif_names, title='', idx=0):
     ax2.plot(month_names, mean_maxima)
 
     ax.set_ylabel('Percentages of annual maxima')
-    ax.set_ylim((0, 30))
+    ax.set_ylim(bottom=0)
     ax.grid()
     ax2.set_ylabel('Mean annual maxima')
-    ax2.set_ylim((0, 100))
+    ax2.set_ylim(bottom=0)
 
     studies.show_or_save_to_file(plot_name=title)
     plt.close()
@@ -61,25 +77,48 @@ def get_month_to_maxima(massif_names, studies, years):
     return month_to_maxima
 
 
-if __name__ == '__main__':
+def main_repartition_for_snowfall_past():
     study_class = SafranSnowfall1Day
     # 'Vercors'
-
     norht_massif_names = ['Oisans', 'Grandes-Rousses', 'Haute-Maurienne', 'Vanoise',
                           'Maurienne', 'Belledonne', 'Chartreuse', 'Haute-Tarentaise',
                           'Beaufortain', 'Bauges', 'Mont-Blanc', 'Aravis', 'Chablais']
     south_massif_names = ['Mercantour', 'Ubaye', 'Haut_Var-Haut_Verdon', 'Parpaillon', 'Champsaur',
                           'Devoluy', 'Queyras', 'Pelvoux', 'Thabor']
-
-
-    for altitudes in altitudes_for_groups:
+    for altitudes in altitudes_for_groups[:1]:
         studies = AltitudesStudies(study_class, altitudes)
         elevation = get_altitude_group_from_altitudes(altitudes).reference_altitude
 
         # for idx in range(3):
+        # idx enable to plot for some subset of dates
         for idx in range(1):
             for masssif_names, region_name in zip([norht_massif_names, south_massif_names],
                                                   ['North', 'South']):
                 plot_season_repartition_of_maxima(studies, masssif_names, '{} {}'.format(region_name, elevation),
                                                   idx=idx)
 
+def main_repartition_for_swe_projected():
+    for study_class in [AdamontSwe, CrocusSweTotal]:
+        masssif_names = ['Oisans', 'Grandes-Rousses', 'Haute-Maurienne', 'Vanoise',
+                              'Maurienne', 'Belledonne', 'Chartreuse', 'Haute-Tarentaise',
+                              'Beaufortain', 'Bauges', 'Mont-Blanc', 'Aravis', 'Chablais',
+                        'Mercantour', 'Ubaye', 'Haut_Var-Haut_Verdon', 'Parpaillon', 'Champsaur',
+                              'Devoluy', 'Queyras', 'Pelvoux', 'Thabor']
+        region_name = 'French Alps'
+        for altitudes in altitudes_for_groups[1:]:
+            studies = AltitudesStudies(study_class, altitudes)
+
+            if issubclass(study_class, AbstractAdamontStudy):
+                print(studies.study.scenario)
+            title = 'for elevations ' + get_altitude_group_from_altitudes(altitudes).formula
+            # for idx in range(3):
+            # idx enable to plot for some subset of dates
+            for idx in range(1):
+                plot_season_repartition_of_maxima(studies, masssif_names, title,
+                                                  idx=idx)
+
+
+if __name__ == '__main__':
+    # main_repartition_for_snowfall_past()
+    main_repartition_for_swe_projected()
+