From 01c08f79cc04cacdb573a149fbf58ab0eaf20f94 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Thu, 25 Mar 2021 08:55:54 +0100
Subject: [PATCH] [projection snowfall] add
main_sensitivity_one_altitude_range.py. add detail plot for each massif for
the return level
---
.../cmip5/climate_explorer_cimp5.py | 3 -
.../adamont_data/cmip5/temperature_to_year.py | 22 ++--
.../scm_models_data/safran/safran_variable.py | 6 +-
.../visualization/plot_utils.py | 31 ++---
.../visualizer_for_sensitivity.py | 49 +++++---
...es_visualizer_for_non_stationary_models.py | 12 +-
.../main_altitudes_studies.py | 37 +++---
.../discussion/main_sensitivity.py | 4 +-
.../main_sensitivity_one_altitude_range.py | 108 ++++++++++++++++++
9 files changed, 206 insertions(+), 66 deletions(-)
create mode 100644 projects/projected_extreme_snowfall/discussion/main_sensitivity_one_altitude_range.py
diff --git a/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py b/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
index 0372adc4..87166420 100644
--- a/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
+++ b/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
@@ -58,10 +58,7 @@ def years_and_global_mean_temps(gcm, scenario, year_min=None, year_max=None, ano
download_dat(dat_filepath, txt_filepath)
# Transform nc file into csv file
if not op.exists(csv_filepath):
- print('compute csv')
dat_to_csv(csv_filepath, txt_filepath, gcm)
- else:
- print('read from existing csv')
# Load csv file
df = pd.read_csv(csv_filepath, index_col=0)
diff --git a/extreme_data/meteo_france_data/adamont_data/cmip5/temperature_to_year.py b/extreme_data/meteo_france_data/adamont_data/cmip5/temperature_to_year.py
index c6abcb19..61872585 100644
--- a/extreme_data/meteo_france_data/adamont_data/cmip5/temperature_to_year.py
+++ b/extreme_data/meteo_france_data/adamont_data/cmip5/temperature_to_year.py
@@ -91,28 +91,34 @@ def plot_nb_data(is_temperature_interval, is_shift_interval):
def get_interval_limits(is_temperature_interval, is_shift_interval):
if is_temperature_interval:
- temp_min = np.arange(0, 2, 0.5)
- temp_max = temp_min + 1
+ temp_min = np.arange(0, 4, 0.5)
+ temp_max = temp_min + 1.0
left_limit, right_limit = temp_min, temp_max
else:
shift = 25
nb = 3
- year_min = [2006 + shift * i for i in range(nb)]
- year_max = [2050 + shift * i for i in range(nb)]
+ year_min = [1959 + shift * i for i in range(nb)]
+ year_max = [2020 + shift * i for i in range(nb)]
left_limit, right_limit = year_min, year_max
if not is_shift_interval:
min_interval_left = min(left_limit)
left_limit = [min_interval_left for _ in right_limit]
- return left_limit[:3], right_limit[:3]
+ idx = None
+ if idx is None:
+ return left_limit, right_limit
+ else:
+ return left_limit[:idx], right_limit[:idx]
def get_ticks_labels_for_interval(is_temperature_interval, is_shift_interval):
left_limits, right_limits = get_interval_limits(is_temperature_interval, is_shift_interval)
- ticks_labels = [' +${}^o\mathrm{C}$ and +${}^o\mathrm{C}$'.format(left_limit, right_limit, **{'C': '{C}'})
+ left_limits = [int(l) if int(l) == l else l for l in left_limits]
+ right_limits = [int(l) if int(l) == l else l for l in right_limits]
+ ticks_labels = [' ${}$-${}^o\mathrm{C}$'.format(left_limit, right_limit, **{'C': '{C}'})
if is_temperature_interval else '{} and {}'.format(left_limit, right_limit)
for left_limit, right_limit in zip(left_limits, right_limits)]
- prefix = 'Maxima between \n'
- ticks_labels = [prefix + l for l in ticks_labels]
+ # prefix = 'Maxima between \n'
+ ticks_labels = [l for l in ticks_labels]
return ticks_labels
diff --git a/extreme_data/meteo_france_data/scm_models_data/safran/safran_variable.py b/extreme_data/meteo_france_data/scm_models_data/safran/safran_variable.py
index 485560d4..fe1bdfff 100644
--- a/extreme_data/meteo_france_data/scm_models_data/safran/safran_variable.py
+++ b/extreme_data/meteo_france_data/scm_models_data/safran/safran_variable.py
@@ -63,15 +63,15 @@ class SafranSnowfallVariable(AbstractVariable):
return snowfall_in_consecutive_days
-
-
class SafranSnowfallVariableNotCenterOnDay(SafranSnowfallVariable):
+ NAME = 'Snowfall MeteoFranceRate 6hto5h'
def get_snowfall_rates(self, variable_array):
return variable_array[:-1]
class SafranSnowfallVariableCenterOnDay(SafranSnowfallVariable):
+ NAME = 'Snowfall MeteoFranceRate CenterOnDay'
def daily_snowfall(self, hourly_snowfall, nb_days):
hourly_snowfall_without_first_and_last_days = hourly_snowfall[18:-6]
@@ -86,12 +86,12 @@ class SafranSnowfallVariableCenterOnDay(SafranSnowfallVariable):
class SafranSnowfallVariableCenterOnDayMeanRate(SafranSnowfallVariableCenterOnDay):
+ NAME = 'Snowfall MyRate CenterOnDay'
def get_snowfall_rates(self, variable_array):
return 0.5 * (variable_array[:-1] + variable_array[1:])
-
class SafranDateFirstSnowfallVariable(SafranSnowfallVariable):
NAME = 'Date First Snow'
UNIT = 'days'
diff --git a/extreme_data/meteo_france_data/scm_models_data/visualization/plot_utils.py b/extreme_data/meteo_france_data/scm_models_data/visualization/plot_utils.py
index 75e0f219..8a1c9141 100644
--- a/extreme_data/meteo_france_data/scm_models_data/visualization/plot_utils.py
+++ b/extreme_data/meteo_france_data/scm_models_data/visualization/plot_utils.py
@@ -10,19 +10,7 @@ from extreme_data.meteo_france_data.scm_models_data.visualization.create_shifted
def plot_against_altitude(x_ticks, ax, massif_id, massif_name, values, altitude=None, fill=False, massif_name_as_labels=True,
elevation_as_xaxis=True, legend=False):
if massif_name_as_labels:
- di = massif_id // 8
- if di == 0:
- linestyle = '-.'
- elif di == 1:
- linestyle = 'dotted'
- else:
- linestyle = '--'
- colors = list(mcolors.TABLEAU_COLORS)
- colors[-3:-1] = [] # remove gray and olive
- color = colors[massif_id % 8]
- # Label
- massif_name_str = ' '.join(massif_name.split('_'))
- label = massif_name_str
+ color, linestyle, label = get_color_and_linestyle_from_massif_id(massif_id, massif_name)
else:
color = None
linestyle = None
@@ -40,6 +28,23 @@ def plot_against_altitude(x_ticks, ax, massif_id, massif_name, values, altitude=
ax.fill_between(x_ticks, lower_bound, upper_bound, color=color, alpha=0.2)
+def get_color_and_linestyle_from_massif_id(massif_id, massif_name):
+ di = massif_id // 8
+ if di == 0:
+ linestyle = '-.'
+ elif di == 1:
+ linestyle = 'dotted'
+ else:
+ linestyle = '--'
+ colors = list(mcolors.TABLEAU_COLORS)
+ colors[-3:-1] = [] # remove gray and olive
+ color = colors[massif_id % 8]
+ # Label
+ massif_name_str = ' '.join(massif_name.split('_'))
+ label = massif_name_str
+ return color, linestyle, label
+
+
def load_plot(cmap, graduation, label, massif_name_to_value, altitude, add_x_label=True,
negative_and_positive_values=True, massif_name_to_text=None, add_colorbar=True, max_abs_change=None,
xlabel=None, fontsize_label=10):
diff --git a/extreme_trend/ensemble_fit/visualizer_for_sensitivity.py b/extreme_trend/ensemble_fit/visualizer_for_sensitivity.py
index d24fed25..07968587 100644
--- a/extreme_trend/ensemble_fit/visualizer_for_sensitivity.py
+++ b/extreme_trend/ensemble_fit/visualizer_for_sensitivity.py
@@ -6,7 +6,10 @@ import numpy as np
from extreme_data.meteo_france_data.adamont_data.cmip5.temperature_to_year import get_interval_limits, \
get_year_min_and_year_max, get_ticks_labels_for_interval
+from extreme_data.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from extreme_data.meteo_france_data.scm_models_data.utils import Season
+from extreme_data.meteo_france_data.scm_models_data.visualization.plot_utils import \
+ get_color_and_linestyle_from_massif_id
from extreme_fit.model.margin_model.polynomial_margin_model.spatio_temporal_polynomial_model import \
AbstractSpatioTemporalPolynomialModel
from extreme_fit.model.margin_model.utils import MarginFitMethod
@@ -15,7 +18,7 @@ from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fi
from extreme_trend.ensemble_fit.together_ensemble_fit.together_ensemble_fit import TogetherEnsembleFit
from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
from extreme_trend.one_fold_fit.altitude_group import get_altitude_class_from_altitudes, \
- get_linestyle_for_altitude_class
+ get_linestyle_for_altitude_class, get_altitude_group_from_altitudes
from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
AnomalyTemperatureWithSplineTemporalCovariate
@@ -92,32 +95,44 @@ class VisualizerForSensivity(object):
def sensitivity_plot_return_levels(self, merge_visualizer_str):
ax = plt.gca()
for altitudes in self.altitudes_list:
- altitude_class = get_altitude_class_from_altitudes(altitudes)
- self.interval_plot_return_levels(ax, altitude_class, merge_visualizer_str)
+ altitude_group = get_altitude_class_from_altitudes(altitudes)
+ self.interval_plot_return_levels(ax, altitude_group, merge_visualizer_str)
ticks_labels = get_ticks_labels_for_interval(self.is_temperature_interval, self.is_shift_interval)
name = 'Return levels at the end of the interval'
+ if len(self.altitudes_list) == 1:
+ altitude_group = get_altitude_group_from_altitudes(self.altitudes_list[0])
+ name += ' at {} m'.format(altitude_group.reference_altitude)
ax.set_ylabel(name)
- ax.set_xlabel('Interval used to compute the trends ')
+ ax.set_xlabel('Interval for the maxima used to compute the trends ')
ax.set_xticks(self.right_limits)
ax.set_xticklabels(ticks_labels)
- lim_left, lim_right = ax.get_xlim()
- ax.legend(prop={'size': 7}, loc='upper center', ncol=2)
- # ax.set_ylim((0, 122))
- # ax.set_yticks([i * 10 for i in range(11)])
self.save_plot(merge_visualizer_str, name)
def interval_plot_return_levels(self, ax, altitude_class, merge_visualizer_str):
- linestyle = get_linestyle_for_altitude_class(altitude_class)
mean_return_levels = []
- for v in self.right_limit_to_visualizer.values():
+ massif_names = AbstractStudy.all_massif_names() if self.massif_names is None else self.massif_names
+ massif_name_to_tuple_list = {m: [] for m in massif_names}
+ for r, v in self.right_limit_to_visualizer.items():
merge_visualizer = self.get_merge_visualizer(altitude_class, v, merge_visualizer_str)
- mean_return_level = merge_visualizer.mean_return_level(self.massif_names)
- mean_return_levels.append(mean_return_level)
-
- label = altitude_class().formula
- ax.plot(self.right_limits, mean_return_levels, linestyle=linestyle, label=label, color='orange')
+ massif_name_to_return_level = merge_visualizer.massif_name_to_return_level(massif_names)
+ for massif_name, return_level in massif_name_to_return_level.items():
+ massif_name_to_tuple_list[massif_name].append((r, return_level))
+ mean_return_levels.append(np.mean(list(massif_name_to_return_level.values())))
+
+ for massif_id, massif_name in enumerate(AbstractStudy.all_massif_names()):
+ if len(massif_name_to_tuple_list[massif_name]) > 0:
+ x, y = zip(*massif_name_to_tuple_list[massif_name])
+ else:
+ x, y = [], []
+ color, linestyle, label = get_color_and_linestyle_from_massif_id(massif_id, massif_name)
+ ax.plot(x, y, color=color, linestyle=linestyle, label=label)
+
+ ax.plot(self.right_limits, mean_return_levels, label="Mean", color='k', linewidth=4)
+ down, up = ax.get_ylim()
+ ax.set_ylim((down, up * 1.3))
+ ax.legend(prop={'size': 7}, ncol=3, loc="upper center")
def interval_plot_changes(self, ax, altitude_class, merge_visualizer_str, relative):
linestyle = get_linestyle_for_altitude_class(altitude_class)
@@ -141,7 +156,7 @@ class VisualizerForSensivity(object):
ticks_labels = get_ticks_labels_for_interval(self.is_temperature_interval, self.is_shift_interval)
name = 'relative changes' if relative else "changes"
ax.set_ylabel(name)
- ax.set_xlabel('Interval used to compute the trends ')
+ ax.set_xlabel('Interval for the maxima used to compute the trends ')
ax.set_xticks(self.right_limits)
ax.set_xticklabels(ticks_labels)
lim_left, lim_right = ax.get_xlim()
@@ -172,7 +187,7 @@ class VisualizerForSensivity(object):
ticks_labels = get_ticks_labels_for_interval(self.is_temperature_interval, self.is_shift_interval)
ax.set_ylabel('Percentages of massifs (\%)')
- ax.set_xlabel('Interval used to compute the trends ')
+ ax.set_xlabel('Interval used for the maxima to compute the trends ')
ax.set_xticks(self.right_limits)
ax.set_xticklabels(ticks_labels)
ax.legend(prop={'size': 7}, loc='upper center', ncol=2)
diff --git a/extreme_trend/one_fold_fit/altitudes_studies_visualizer_for_non_stationary_models.py b/extreme_trend/one_fold_fit/altitudes_studies_visualizer_for_non_stationary_models.py
index 73b674f5..f856a926 100644
--- a/extreme_trend/one_fold_fit/altitudes_studies_visualizer_for_non_stationary_models.py
+++ b/extreme_trend/one_fold_fit/altitudes_studies_visualizer_for_non_stationary_models.py
@@ -462,13 +462,13 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
self.studies.show_or_save_to_file(plot_name=plot_name, show=self.show)
plt.close()
- def mean_return_level(self, massif_names):
+ def massif_name_to_return_level(self, massif_names):
valid_massif_names = self.get_valid_names(massif_names)
- return_levels = []
- for one_fold in [one_fold for m, one_fold in self.massif_name_to_one_fold_fit.items()
- if m in valid_massif_names]:
- return_levels.append(one_fold.return_level_last_temporal_coordinate)
- return np.mean(return_levels)
+ massif_name_to_return_level = {}
+ for m, one_fold in self.massif_name_to_one_fold_fit.items():
+ if m in valid_massif_names:
+ massif_name_to_return_level[m] = one_fold.return_level_last_temporal_coordinate
+ return massif_name_to_return_level
def all_trends(self, massif_names, with_significance=True, with_relative_change=False):
"""return percents which contain decrease, significant decrease, increase, significant increase percentages"""
diff --git a/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py b/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py
index bef9ed2e..1801c8d2 100644
--- a/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py
+++ b/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py
@@ -1,18 +1,20 @@
import datetime
import time
from typing import List
-
-
import matplotlib as mpl
-
-from extreme_trend.one_fold_fit.utils_altitude_studies_visualizer import load_visualizer_list
-
mpl.rcParams['text.usetex'] = True
mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
import matplotlib
matplotlib.use('Agg')
+
+from extreme_data.meteo_france_data.scm_models_data.safran.safran_max_snowf import SafranSnowfall2020, \
+ SafranSnowfall2019
+from extreme_trend.one_fold_fit.utils_altitude_studies_visualizer import load_visualizer_list
+
+
+
from extreme_trend.one_fold_fit.plots.plot_histogram_altitude_studies import \
plot_shoe_plot_changes_against_altitude, plot_histogram_all_trends_against_altitudes, \
plot_histogram_all_models_against_altitudes
@@ -29,14 +31,19 @@ from extreme_trend.one_fold_fit.plots.plot_coherence_curves import plot_coherenc
from extreme_trend.one_fold_fit.altitude_group import altitudes_for_groups
from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day, SafranSnowfall3Days, \
- SafranSnowfall5Days, SafranSnowfall7Days
+ SafranSnowfall5Days, SafranSnowfall7Days, SafranSnowfallCenterOnDay1day, SafranSnowfallNotCenterOnDay1day, \
+ SafranSnowfallCenterOnDay1dayMeanRate
from extreme_data.meteo_france_data.scm_models_data.utils import Season
def main():
+
study_classes = [SafranSnowfall1Day
, SafranSnowfall3Days,
SafranSnowfall5Days, SafranSnowfall7Days][:1]
+ study_classes = [SafranSnowfall2019, SafranSnowfall2020, SafranSnowfallCenterOnDay1day,
+ SafranSnowfallNotCenterOnDay1day,
+ SafranSnowfallCenterOnDay1dayMeanRate, SafranSnowfall1Day][1:2]
seasons = [Season.annual, Season.winter, Season.spring, Season.automn][:1]
set_seed_for_test()
@@ -70,8 +77,8 @@ def main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_p
for study_class in study_classes:
print('Inner loop', season, study_class)
visualizer_list = load_visualizer_list(season, study_class, altitudes_list, massif_names,
- model_must_pass_the_test
- )
+ model_must_pass_the_test,
+ year_max=2019)
plot_visualizers(massif_names, visualizer_list)
for visualizer in visualizer_list:
plot_visualizer(massif_names, visualizer)
@@ -80,12 +87,12 @@ def main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_p
def plot_visualizers(massif_names, visualizer_list):
- plot_histogram_all_models_against_altitudes(massif_names, visualizer_list)
- plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list, with_significance=True)
+ # plot_histogram_all_models_against_altitudes(massif_names, visualizer_list)
+ plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list, with_significance=False)
# plot_shoe_plot_ratio_interval_size_against_altitude(massif_names, visualizer_list)
for relative in [True, False]:
- plot_shoe_plot_changes_against_altitude(massif_names, visualizer_list, relative=relative)
- plot_coherence_curves(['Vanoise'], visualizer_list)
+ plot_shoe_plot_changes_against_altitude(massif_names, visualizer_list, relative=relative, with_significance=False)
+ # plot_coherence_curves(['Vanoise'], visualizer_list)
pass
@@ -94,11 +101,13 @@ def plot_visualizer(massif_names, visualizer):
# visualizer.studies.plot_maxima_time_series(massif_names)
# visualizer.studies.plot_maxima_time_series(['Vanoise'])
- visualizer.plot_shape_map()
+ # visualizer.plot_shape_map()
visualizer.plot_moments()
- visualizer.plot_qqplots()
+ # visualizer.plot_qqplots()
+
# for std in [True, False]:
# visualizer.studies.plot_mean_maxima_against_altitude(std=std)
+ pass
if __name__ == '__main__':
main()
diff --git a/projects/projected_extreme_snowfall/discussion/main_sensitivity.py b/projects/projected_extreme_snowfall/discussion/main_sensitivity.py
index ddc3dc94..6ed567ff 100644
--- a/projects/projected_extreme_snowfall/discussion/main_sensitivity.py
+++ b/projects/projected_extreme_snowfall/discussion/main_sensitivity.py
@@ -45,10 +45,10 @@ def main():
set_seed_for_test()
AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
- fast = False
+ fast = None
scenarios = [AdamontScenario.rcp85]
scenarios = rcp_scenarios[1:]
- scenarios = rcm_scenarios_extended[1:]
+ scenarios = rcm_scenarios_extended[2:][::-1]
if fast in [None, True]:
scenarios = scenarios[:1]
diff --git a/projects/projected_extreme_snowfall/discussion/main_sensitivity_one_altitude_range.py b/projects/projected_extreme_snowfall/discussion/main_sensitivity_one_altitude_range.py
new file mode 100644
index 00000000..d421a5c7
--- /dev/null
+++ b/projects/projected_extreme_snowfall/discussion/main_sensitivity_one_altitude_range.py
@@ -0,0 +1,108 @@
+import datetime
+import time
+from typing import List
+import matplotlib
+
+
+matplotlib.use('Agg')
+import matplotlib as mpl
+
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
+
+from extreme_trend.ensemble_fit.abstract_ensemble_fit import AbstractEnsembleFit
+from extreme_trend.ensemble_fit.together_ensemble_fit.together_ensemble_fit import TogetherEnsembleFit
+
+from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fit import IndependentEnsembleFit
+from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
+from extreme_trend.ensemble_fit.visualizer_for_sensitivity import VisualizerForSensivity
+from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
+ AnomalyTemperatureWithSplineTemporalCovariate
+
+from extreme_fit.model.margin_model.polynomial_margin_model.utils import \
+ ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
+
+from extreme_fit.model.utils import set_seed_for_test
+
+from extreme_data.meteo_france_data.adamont_data.adamont.adamont_safran import AdamontSnowfall
+from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario, get_gcm_rcm_couples, \
+ rcp_scenarios, rcm_scenarios_extended
+from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
+ TimeTemporalCovariate
+
+from extreme_fit.model.result_from_model_fit.result_from_extremes.abstract_extract_eurocode_return_level import \
+ AbstractExtractEurocodeReturnLevel
+
+from extreme_trend.one_fold_fit.altitude_group import altitudes_for_groups
+
+from extreme_data.meteo_france_data.scm_models_data.utils import Season
+
+
+def main():
+ start = time.time()
+ study_class = AdamontSnowfall
+ ensemble_fit_classes = [IndependentEnsembleFit, TogetherEnsembleFit][1:]
+ set_seed_for_test()
+ AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
+
+ fast = False
+ scenarios = [AdamontScenario.rcp85]
+ scenarios = rcp_scenarios[1:]
+ scenarios = rcm_scenarios_extended[:][::-1]
+
+ if fast in [None, True]:
+ scenarios = scenarios[:1]
+
+ for scenario in scenarios:
+ gcm_rcm_couples = get_gcm_rcm_couples(scenario)
+ if fast is None:
+ massif_names = None
+ gcm_rcm_couples = gcm_rcm_couples[:2]
+ AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
+ altitudes_list = altitudes_for_groups[:1]
+ elif fast:
+ massif_names = ['Vanoise', 'Haute-Maurienne', 'Vercors', 'Ubaye']
+ gcm_rcm_couples = gcm_rcm_couples[4:6]
+ AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
+ altitudes_list = altitudes_for_groups[1:3]
+ else:
+ massif_names = None
+ altitudes_list = altitudes_for_groups[:]
+
+ assert isinstance(gcm_rcm_couples, list)
+
+ assert isinstance(altitudes_list, List)
+ assert isinstance(altitudes_list[0], List)
+ print('Scenario is', scenario)
+
+ model_classes = ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
+ assert scenario is not AdamontScenario.histo
+ remove_physically_implausible_models = True
+ temp_cov = True
+ temporal_covariate_for_fit = AnomalyTemperatureWithSplineTemporalCovariate if temp_cov else TimeTemporalCovariate
+ print('Covariate is {}'.format(temporal_covariate_for_fit))
+
+ for altitudes in altitudes_list:
+ sub_altitudes_list = [altitudes]
+ print(sub_altitudes_list)
+ for is_temperature_interval in [True, False][:1]:
+ for is_shift_interval in [True, False][1:]:
+ visualizer = VisualizerForSensivity(
+ sub_altitudes_list, gcm_rcm_couples, study_class, Season.annual, scenario,
+ model_classes=model_classes,
+ ensemble_fit_classes=ensemble_fit_classes,
+ massif_names=massif_names,
+ temporal_covariate_for_fit=temporal_covariate_for_fit,
+ remove_physically_implausible_models=remove_physically_implausible_models,
+ is_temperature_interval=is_temperature_interval,
+ is_shift_interval=is_shift_interval,
+ )
+ visualizer.plot()
+
+ end = time.time()
+ duration = str(datetime.timedelta(seconds=end - start))
+ print('Total duration', duration)
+
+
+if __name__ == '__main__':
+ main()
--
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