diff --git a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
index 6891acfbba86a4dcf46fdc8e1196c4bd5654e1c3..df61a53190e7e70acb0c8dd1dba49568f37d4c27 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
@@ -6,6 +6,7 @@ from random import sample, seed
from typing import Dict, Tuple
import math
+
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
@@ -819,7 +820,7 @@ class StudyVisualizer(VisualizationParameters):
ax.set_aspect('equal')
def show_or_save_to_file(self, add_classic_title=True, no_title=False, tight_layout=False, tight_pad=None,
- dpi=None):
+ dpi=None, folder_for_variable=True):
if tight_layout:
if tight_pad is not None:
plt.tight_layout(**tight_pad)
@@ -839,7 +840,10 @@ class StudyVisualizer(VisualizationParameters):
plt.show()
if self.save_to_file:
main_title, specific_title = '_'.join(self.study.title.split()).split('/')
- filename = "{}/{}/".format(VERSION_TIME, main_title)
+ if folder_for_variable:
+ filename = "{}/{}/".format(VERSION_TIME, main_title)
+ else:
+ filename = "{}/".format(VERSION_TIME)
if not self.only_one_graph:
filename += "{}".format('_'.join(self.plot_name.split())) + '_'
filename += specific_title
diff --git a/papers/contrasting_snow_loads/main_result.py b/papers/contrasting_snow_loads/main_result.py
index dba2c4387bedcd21b6f5d9eb53d9e009b5ef5287..d152057b8e7555acb3dfb35731b48ecdb7d75280 100644
--- a/papers/contrasting_snow_loads/main_result.py
+++ b/papers/contrasting_snow_loads/main_result.py
@@ -1,6 +1,9 @@
from multiprocessing.pool import Pool
import matplotlib as mpl
+mpl.use('Agg')
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal, CrocusSnowLoad3Days, \
CrocusSnowLoad5Days, CrocusSnowLoad7Days, CrocusSnowLoad1Day
@@ -19,14 +22,14 @@ from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_uncertaint
plot_uncertainty_histogram
from root_utils import NB_CORES
-mpl.rcParams['text.usetex'] = True
-mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
+
def intermediate_result(altitudes, massif_names=None,
model_subsets_for_uncertainty=None, uncertainty_methods=None,
study_class=CrocusSnowLoad3Days,
- multiprocessing=False):
+ multiprocessing=False,
+ save_to_file=True):
"""
Plot all the trends for all altitudes
And enable to plot uncertainty plot for some specific massif_names, uncertainty methods to be fast
@@ -39,7 +42,7 @@ def intermediate_result(altitudes, massif_names=None,
"""
# Load altitude to visualizer
altitude_to_visualizer = load_altitude_to_visualizer(altitudes, massif_names, model_subsets_for_uncertainty,
- study_class, uncertainty_methods)
+ study_class, uncertainty_methods, save_to_file=save_to_file)
# Load variable object efficiently
for v in altitude_to_visualizer.values():
_ = v.study.year_to_variable_object
@@ -62,7 +65,7 @@ def major_result():
massif_names = None
model_subsets_for_uncertainty = None
altitudes = paper_altitudes
- altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700]
+ # altitudes = [600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300]
study_classes = [CrocusSnowLoad1Day, CrocusSnowLoad3Days, CrocusSnowLoad5Days, CrocusSnowLoad7Days][:]
for study_class in study_classes:
intermediate_result(altitudes, massif_names, model_subsets_for_uncertainty,
@@ -74,4 +77,5 @@ if __name__ == '__main__':
# intermediate_result(altitudes=[1500, 1800][:], massif_names=None,
# uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
# ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
- # multiprocessing=True)
\ No newline at end of file
+ # multiprocessing=True,
+ # save_to_file=False)
\ No newline at end of file
diff --git a/papers/contrasting_snow_loads/plot_contrasting_trend_curves.py b/papers/contrasting_snow_loads/plot_contrasting_trend_curves.py
index 616bb7289a2b32b5e872acad7c25701943594ab1..8d4b154ab32432515e23ef0d11e550f12fc70a5d 100644
--- a/papers/contrasting_snow_loads/plot_contrasting_trend_curves.py
+++ b/papers/contrasting_snow_loads/plot_contrasting_trend_curves.py
@@ -16,7 +16,8 @@ def plot_contrasting_trend_curves(altitude_to_visualizer: Dict[int, StudyVisuali
visualizer = list(altitude_to_visualizer.values())[0]
ax = create_adjusted_axes(1, 1)
- ax_twinx = ax.twinx()
+ # ax_twinx = ax.twinx()
+ ax_twinx = ax
ax_twiny = ax.twiny()
trend_summary_values = list(zip(*[v.trend_summary_contrasting_values() for v in altitude_to_visualizer.values()]))
@@ -60,19 +61,20 @@ def plot_contrasting_trend_curves(altitude_to_visualizer: Dict[int, StudyVisuali
# axis.set_ylim(ax_lim)
# axis.set_yticks(ax_ticks)
# axis.tick_params(labelsize=labelsize)
- ax.yaxis.grid()
+ ax_twinx.yaxis.grid()
- label_curve = (visualizer.label).replace('change', 'decrease')
- ax_twinx.set_ylabel(label_curve.replace('', ''), fontsize=legend_fontsize)
- for region_name, mean_change in zip(AbstractExtendedStudy.region_names, mean_changes):
- if len(mean_changes) > 1:
+ ax_twinx.set_ylabel(visualizer.label, fontsize=legend_fontsize)
+ for j, (region_name, mean_change) in enumerate(zip(AbstractExtendedStudy.region_names, mean_changes)):
+ if len(mean_changes) > 2:
label = region_name
+ elif len(mean_changes) == 2:
+ label = 'North' if j == 0 else 'South'
else:
label = 'Mean relative change'
ax_twinx.plot(altitudes, mean_change, label=label, linewidth=linewidth, marker='o')
ax_twinx.legend(loc='upper right', prop={'size': size})
# Save plot
- visualizer.plot_name = 'Trend curves'
- visualizer.show_or_save_to_file(no_title=True, dpi=dpi_paper1_figure)
+ visualizer.plot_name = 'Trend curves for' + visualizer.study.variable_name.split('(')[0]
+ visualizer.show_or_save_to_file(no_title=True, dpi=dpi_paper1_figure, folder_for_variable=False)
plt.close()
diff --git a/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py b/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py
index a7f3e056da4c042b1b4effe953e985015ab3ca84..52af41d3a0a172a44d48d8aa9701e3e8413b21bb 100644
--- a/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py
+++ b/papers/exceeding_snow_loads/study_visualizer_for_non_stationary_trends.py
@@ -436,12 +436,21 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
# percentage_decrease = 100 * len(decreasing_trend_tests) / len(trend_tests)
# significative_decrease_trend_tests = [t for t in decreasing_trend_tests if t.is_significant]
# percentage_decrease_significative = 100 * len(significative_decrease_trend_tests) / len(trend_tests)
- compute_mean_change = lambda l: np.mean(np.array(list(l)))
- mean_changes = [compute_mean_change(self.massif_name_to_relative_change_value.values())]
- # Compute mean relatives per regions (for the moment i don't add the region means)
+ compute_mean_change = lambda l: np.mean(np.array(list(l))) if len(l) > 0 else 0
+ all_regions = False
massif_name_to_region_name = AbstractExtendedStudy.massif_name_to_region_name
- for region_name in AbstractExtendedStudy.real_region_names:
- change_values = [v for m, v in self.massif_name_to_relative_change_value.items()
- if massif_name_to_region_name[m] == region_name]
- mean_changes.append(compute_mean_change(change_values))
+ if all_regions:
+ mean_changes = [compute_mean_change(self.massif_name_to_relative_change_value.values())]
+ # Compute mean relatives per regions (for the moment i don't add the region means)
+ for region_name in AbstractExtendedStudy.real_region_names:
+ change_values = [v for m, v in self.massif_name_to_relative_change_value.items()
+ if massif_name_to_region_name[m] == region_name]
+ mean_changes.append(compute_mean_change(change_values))
+ else:
+ mean_changes = [
+ compute_mean_change([v for m, v in self.massif_name_to_relative_change_value.items()
+ if massif_name_to_region_name[m] in regions])
+ for regions in [AbstractExtendedStudy.real_region_names[:2], AbstractExtendedStudy.real_region_names[2:]]
+ ]
+
return (self.altitude, *mean_changes)