From 809fd66289a5d7760859a48cf5a49abef3d011de Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 24 Feb 2021 17:07:36 +0100
Subject: [PATCH] [projections] fix and refactor temperature_to_year.py. Focus
on the median merge function, rather than the mean merge function.
---
.../adamont_data/cmip5/temperature_to_year.py | 25 ++++----
.../one_fold_analysis/altitude_group.py | 16 +++++-
...ation_temporal_for_projections_ensemble.py | 7 ++-
.../visualizer_for_sensitivity.py | 57 ++++++++++++-------
4 files changed, 69 insertions(+), 36 deletions(-)
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 c911fa5e..30bc22ba 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
@@ -36,7 +36,7 @@ def get_nb_data(gcm, scenario, temperature_min, temperature_max):
return year_max - year_min + 1
-def plot_nb_data_one_line(ax, gcm, scenario, temp_min, temp_max):
+def plot_nb_data_one_line(ax, gcm, scenario, temp_min, temp_max, first_scenario):
nb_data = [get_nb_data(gcm, scenario, mi, ma) for mi, ma in zip(temp_min, temp_max)]
color = gcm_to_color[gcm]
@@ -48,26 +48,26 @@ def plot_nb_data_one_line(ax, gcm, scenario, temp_min, temp_max):
nb_data, temp_min = nb_data[ind], temp_min[ind]
# For the legend
- if scenario is AdamontScenario.rcp26:
+ if (len(nb_data) > 0) and first_scenario:
ax.plot(temp_min[0], nb_data[0], color=color, linestyle='solid', label=gcm)
- ax.plot(temp_min, nb_data, linestyle=linestyle, color=color)
+ ax.plot(temp_min, nb_data, linestyle=linestyle, color=color, marker='o')
def plot_nb_data():
- temp_max, temp_min = get_temp_min_and_temp_max()
+ temp_min, temp_max = get_temp_min_and_temp_max()
ax = plt.gca()
for gcm in get_gcm_list(adamont_version=2)[:]:
- for scenario in rcp_scenarios[:]:
- plot_nb_data_one_line(ax, gcm, scenario, temp_min, temp_max)
+ for i, scenario in enumerate(rcp_scenarios[:2]):
+ plot_nb_data_one_line(ax, gcm, scenario, temp_min, temp_max, first_scenario=i == 0)
ax.legend()
- ticks_labels = ['{}-{}'.format(mi, ma) for mi, ma in zip(temp_min, temp_max)]
+ ticks_labels = get_ticks_labels_for_temp_min_and_temp_max()
ax.set_xticks(temp_min)
ax.set_xticklabels(ticks_labels)
ax.set_xlabel('Temperature interval')
- ax.set_ylabel('Nb of Data')
+ ax.set_ylabel('Nb of Maxima')
ax2 = ax.twinx()
legend_elements = [
Line2D([0], [0], color='k', lw=1, label=scenario_to_str(s),
@@ -79,10 +79,15 @@ def plot_nb_data():
def get_temp_min_and_temp_max():
- temp_min = np.arange(0.5, 2.5, 0.5)
- temp_max = temp_min + 1.5
+ temp_min = np.arange(0, 3, 1)
+ temp_max = temp_min + 2
return temp_min, temp_max
+def get_ticks_labels_for_temp_min_and_temp_max():
+ temp_min, temp_max = get_temp_min_and_temp_max()
+ return ['Maxima occured between \n' \
+ ' +${}^o\mathrm{C}$ and +${}^o\mathrm{C}$'.format(mi, ma, **{'C': '{C}'})
+ for mi, ma in zip(temp_min, temp_max)]
if __name__ == '__main__':
plot_nb_data()
diff --git a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitude_group.py b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitude_group.py
index 5a3f8a16..60924af0 100644
--- a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitude_group.py
+++ b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitude_group.py
@@ -19,7 +19,7 @@ class AbstractAltitudeGroup(object):
@property
def altitudes(self):
- return altitudes_for_groups[self.group_id-1]
+ return altitudes_for_groups[self.group_id - 1]
@property
def reference_altitude(self):
@@ -161,3 +161,17 @@ def get_altitude_group_from_altitudes(altitudes):
return VeyHighAltitudeGroup()
else:
return DefaultAltitudeGroup()
+
+
+def get_linestyle_for_altitude_class(altitude_class):
+ assert issubclass(altitude_class, AbstractAltitudeGroup)
+ if altitude_class is LowAltitudeGroup:
+ return 'solid'
+ elif altitude_class is MidAltitudeGroup:
+ return 'dashed'
+ elif altitude_class is HighAltitudeGroup:
+ return 'dashdot'
+ elif altitude_class is VeyHighAltitudeGroup:
+ return 'dotted'
+ else:
+ raise NotImplementedError
diff --git a/projects/projected_snowfall/elevation_temporal_model_for_projections/main_elevation_temporal_for_projections_ensemble.py b/projects/projected_snowfall/elevation_temporal_model_for_projections/main_elevation_temporal_for_projections_ensemble.py
index 23f51598..798ce662 100644
--- a/projects/projected_snowfall/elevation_temporal_model_for_projections/main_elevation_temporal_for_projections_ensemble.py
+++ b/projects/projected_snowfall/elevation_temporal_model_for_projections/main_elevation_temporal_for_projections_ensemble.py
@@ -43,9 +43,9 @@ def main():
set_seed_for_test()
AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
- fast = None
+ fast = False
sensitivity_plot = True
- scenarios = rcp_scenarios if fast is False else [AdamontScenario.rcp85]
+ scenarios = rcp_scenarios[::-1] if fast is False else [AdamontScenario.rcp85]
for scenario in scenarios:
gcm_rcm_couples = get_gcm_rcm_couples(scenario)
@@ -58,7 +58,7 @@ def main():
massif_names = ['Vanoise', 'Haute-Maurienne']
gcm_rcm_couples = gcm_rcm_couples[4:6]
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
- altitudes_list = altitudes_for_groups[2:]
+ altitudes_list = altitudes_for_groups[:]
else:
massif_names = None
altitudes_list = altitudes_for_groups[:]
@@ -77,6 +77,7 @@ def main_loop(gcm_rcm_couples, altitudes_list, massif_names, study_class, ensemb
temporal_covariate_for_fit, sensitivity_plot=False):
assert isinstance(altitudes_list, List)
assert isinstance(altitudes_list[0], List)
+ print('Scenario is', scenario)
print('Covariate is {}'.format(temporal_covariate_for_fit))
model_classes = ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
diff --git a/projects/projected_snowfall/elevation_temporal_model_for_projections/visualizer_for_sensitivity.py b/projects/projected_snowfall/elevation_temporal_model_for_projections/visualizer_for_sensitivity.py
index f3e40b69..72392ee5 100644
--- a/projects/projected_snowfall/elevation_temporal_model_for_projections/visualizer_for_sensitivity.py
+++ b/projects/projected_snowfall/elevation_temporal_model_for_projections/visualizer_for_sensitivity.py
@@ -3,14 +3,14 @@ import matplotlib.pyplot as plt
from typing import List, Dict
from extreme_data.meteo_france_data.adamont_data.cmip5.temperature_to_year import get_temp_min_and_temp_max, \
- temperature_minmax_to_year_minmax
+ temperature_minmax_to_year_minmax, get_ticks_labels_for_temp_min_and_temp_max
from extreme_data.meteo_france_data.scm_models_data.utils import Season
from extreme_fit.model.margin_model.polynomial_margin_model.spatio_temporal_polynomial_model import \
AbstractSpatioTemporalPolynomialModel
from extreme_fit.model.margin_model.utils import MarginFitMethod
from projects.altitude_spatial_model.altitudes_fit.altitudes_studies import AltitudesStudies
from projects.altitude_spatial_model.altitudes_fit.one_fold_analysis.altitude_group import \
- get_altitude_group_from_altitudes, get_altitude_class_from_altitudes
+ get_altitude_group_from_altitudes, get_altitude_class_from_altitudes, get_linestyle_for_altitude_class
from projects.altitude_spatial_model.altitudes_fit.plots.plot_histogram_altitude_studies import \
plot_histogram_all_trends_against_altitudes, plot_shoe_plot_changes_against_altitude
from projects.altitude_spatial_model.altitudes_fit.utils_altitude_studies_visualizer import compute_and_assign_max_abs
@@ -31,7 +31,9 @@ class VisualizerForSensivity(object):
display_only_model_that_pass_gof_test=False,
confidence_interval_based_on_delta_method=False,
remove_physically_implausible_models=False,
+ merge_visualizer_str=IndependentEnsembleFit.Median_merge # if we choose the Mean merge, then it is almost impossible to obtain stationary trends
):
+ self.merge_visualizer_str = merge_visualizer_str
self.altitudes_list = altitudes_list
self.massif_names = massif_names
self.temp_min, self.temp_max = get_temp_min_and_temp_max()
@@ -64,7 +66,8 @@ class VisualizerForSensivity(object):
def plot(self):
# todo: before reactivating the subplot, i should ensure that we can modify the prefix
- # so that we can have all the subplot, and not juste for the last t_min
+ # so that we can have all the subplot for the merge visualizer
+ # , and not just the plots for the last t_min
# for visualizer in self.temp_min_to_visualizer.values():
# visualizer.plot()
self.sensitivity_plot()
@@ -75,41 +78,51 @@ class VisualizerForSensivity(object):
altitude_class = get_altitude_class_from_altitudes(altitudes)
self.temperature_interval_plot(ax, altitude_class)
- ticks_labels = ['+{} to +{}'.format(mi, ma) for mi, ma in zip(self.temp_min, self.temp_max)]
- ax.set_ylabel('Percentages of massifs (%)')
+ ticks_labels = get_ticks_labels_for_temp_min_and_temp_max()
+ ax.set_ylabel('Percentages of massifs (\%)')
ax.set_xlabel('Range of temperatures used to compute the trends ')
ax.set_xticks(self.temp_min)
ax.set_xticklabels(ticks_labels)
- ax.legend()
- mean_visualizer = self.first_mean_visualizer
- mean_visualizer.plot_name = 'Sensitivity plot'
- mean_visualizer.show_or_save_to_file(no_title=True)
+ 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)])
+ merge_visualizer = self.first_merge_visualizer
+ merge_visualizer.plot_name = 'Sensitivity plot'
+ merge_visualizer.show_or_save_to_file(no_title=True)
@property
- def first_mean_visualizer(self):
+ def first_merge_visualizer(self):
altitude_class = get_altitude_class_from_altitudes(self.altitudes_list[0])
visualizer_projection = list(self.temp_min_to_visualizer.values())[0]
- return self.get_mean_visualizer(altitude_class, visualizer_projection)
+ return self.get_merge_visualizer(altitude_class, visualizer_projection)
- def get_mean_visualizer(self, altitude_class, visualizer_projection: VisualizerForProjectionEnsemble):
+ def get_merge_visualizer(self, altitude_class, visualizer_projection: VisualizerForProjectionEnsemble):
independent_ensemble_fit = visualizer_projection.altitude_class_to_ensemble_class_to_ensemble_fit[altitude_class][
IndependentEnsembleFit]
- mean_visualizer = independent_ensemble_fit.merge_function_name_to_visualizer[IndependentEnsembleFit.Mean_merge]
- mean_visualizer.studies.study.gcm_rcm_couple = (IndependentEnsembleFit.Mean_merge, "merge")
- return mean_visualizer
+ merge_visualizer = independent_ensemble_fit.merge_function_name_to_visualizer[self.merge_visualizer_str]
+ merge_visualizer.studies.study.gcm_rcm_couple = (self.merge_visualizer_str, "merge")
+ return merge_visualizer
def temperature_interval_plot(self, ax, altitude_class):
+ linestyle = get_linestyle_for_altitude_class(altitude_class)
+ increasing_key = 'increasing'
+ decreasing_key = 'decreasing'
label_to_l = {
- 'increasing': [],
- 'decreasing': []
+ increasing_key: [],
+ decreasing_key: []
+ }
+ label_to_color = {
+ increasing_key: 'red',
+ decreasing_key: 'blue'
}
for v in self.temp_min_to_visualizer.values():
- mean_visualizer = self.get_mean_visualizer(altitude_class, v)
- _, *trends = mean_visualizer.all_trends(self.massif_names, with_significance=False)
- label_to_l['decreasing'].append(trends[0])
- label_to_l['increasing'].append(trends[2])
+ merge_visualizer = self.get_merge_visualizer(altitude_class, v)
+ _, *trends = merge_visualizer.all_trends(self.massif_names, with_significance=False)
+ label_to_l[decreasing_key].append(trends[0])
+ label_to_l[increasing_key].append(trends[2])
altitude_str = altitude_class().formula
for label, l in label_to_l.items():
label_improved = 'with {} trends {}'.format(label, altitude_str)
- ax.plot(self.temp_min, l, label=label_improved)
+ color = label_to_color[label]
+ ax.plot(self.temp_min, l, label=label_improved, color=color, linestyle=linestyle)
--
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