diff --git a/projects/archive/seasonal_analysis/main_season_repartition_of_maxima.py b/projects/archive/seasonal_analysis/main_season_repartition_of_maxima.py
index a1da50b08b983496ec2d3e1ec7492513ee12286b..be0db2e20fbab2ef6105bcdde1fcc36f4544a337 100644
--- a/projects/archive/seasonal_analysis/main_season_repartition_of_maxima.py
+++ b/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()
+