From 32ed5bef8efdf483499c2ad4d4b1bfee40e3d0cd Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Fri, 5 Feb 2021 19:02:51 +0100
Subject: [PATCH] [contrasting] Final modifications for the plot for the v4 of
the article
---
.../altitudes_fit/main_altitudes_studies.py | 11 +--
...es_visualizer_for_non_stationary_models.py | 15 ++--
.../one_fold_analysis/plot_total_aic.py | 2 +-
.../plots/plot_histogram_altitude_studies.py | 76 +++++++++----------
4 files changed, 53 insertions(+), 51 deletions(-)
diff --git a/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py b/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
index c0199b7c..dae8f4eb 100644
--- a/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
+++ b/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
@@ -10,7 +10,7 @@ from extreme_data.meteo_france_data.scm_models_data.safran.safran_max_snowf impo
SafranSnowfall2020
from projects.altitude_spatial_model.altitudes_fit.plots.plot_histogram_altitude_studies import \
plot_shoe_plot_changes_against_altitude, plot_histogram_all_trends_against_altitudes, \
- plot_shoe_plot_ratio_interval_size_against_altitude
+ plot_shoe_plot_ratio_interval_size_against_altitude, plot_histogram_all_models_against_altitudes
from extreme_fit.model.result_from_model_fit.result_from_extremes.abstract_extract_eurocode_return_level import \
AbstractExtractEurocodeReturnLevel
@@ -44,10 +44,10 @@ def main():
model_must_pass_the_test = False
AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
- fast = True
+ fast = False
if fast is None:
- massif_names = ['Vanoise']
- altitudes_list = altitudes_for_groups[:]
+ massif_names = None
+ altitudes_list = altitudes_for_groups[2:3]
elif fast:
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
massif_names = ['Vanoise', 'Haute-Maurienne', 'Vercors'][:1]
@@ -80,6 +80,7 @@ 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)
# plot_shoe_plot_ratio_interval_size_against_altitude(massif_names, visualizer_list)
# for relative in [True, False]:
@@ -95,7 +96,7 @@ def plot_visualizer(massif_names, visualizer):
# visualizer.studies.plot_maxima_time_series(['Vanoise'])
# Plot the results for the model that minimizes the individual aic
- plot_individual_aic(visualizer)
+ # plot_individual_aic(visualizer)
# Plot the results for the model that minimizes the total aic
# plot_total_aic(model_classes, visualizer)
diff --git a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py
index c5cb8818..2dafde17 100644
--- a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py
+++ b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py
@@ -517,13 +517,14 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
coordinate_for_filter = (altitude, None)
unconstrained_empirical_quantiles = one_fold_fit.best_estimator.sorted_empirical_standard_gumbel_quantiles(coordinate_for_filter=coordinate_for_filter)
n = len(unconstrained_empirical_quantiles)
- assert n == 61
- standard_gumbel_quantiles = one_fold_fit.standard_gumbel_quantiles(n=n)
- ax.plot(standard_gumbel_quantiles, unconstrained_empirical_quantiles, linestyle='None',
- label='{} m'.format(altitude), marker='o')
-
- all_quantiles.extend(standard_gumbel_quantiles)
- all_quantiles.extend(unconstrained_empirical_quantiles)
+ if n > 0:
+ assert n == 61
+ standard_gumbel_quantiles = one_fold_fit.standard_gumbel_quantiles(n=n)
+ ax.plot(standard_gumbel_quantiles, unconstrained_empirical_quantiles, linestyle='None',
+ label='{} m'.format(altitude), marker='o')
+
+ all_quantiles.extend(standard_gumbel_quantiles)
+ all_quantiles.extend(unconstrained_empirical_quantiles)
size_label = 20
ax.set_xlabel("Theoretical quantile", fontsize=size_label)
diff --git a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py
index a8e3dffb..ad0fa2a4 100644
--- a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py
+++ b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py
@@ -14,7 +14,7 @@ from projects.exceeding_snow_loads.utils import dpi_paper1_figure
def plots(visualizer: AltitudesStudiesVisualizerForNonStationaryModels):
- # visualizer.plot_shape_map()
+ visualizer.plot_shape_map()
# visualizer.plot_moments()
visualizer.plot_qqplots()
# for std in [True, False]:
diff --git a/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py b/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py
index f9501c7b..75c37793 100644
--- a/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py
+++ b/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py
@@ -40,44 +40,44 @@ def plot_histogram_all_models_against_altitudes(massif_names, visualizer_list: L
print(model_name_to_mean_percentage[model_name], model_name_to_mean_percentage_significant[model_name],
model_name)
- # Plot part
- ax = plt.gca()
- width = 5
- size = 8
- legend_fontsize = 10
- labelsize = 10
- linewidth = 1
- tick_list = np.array([((len(visualizer_list) + 2) * i + (1 + len(visualizer_list) / 2)) * width
- for i in range(len(sorted_model_names))])
- for tick_middle, model_name in zip(tick_list, sorted_model_names):
- x_shifted = [tick_middle + width * shift / 2 for shift in range(-3, 5, 2)]
- percentages = model_name_to_percentages[model_name]
- percentages_significant = model_name_to_percentages_significant[model_name]
- colors = ['white', 'yellow', 'orange', 'red']
- labels = ['{} m - {} m (\% out of {} massifs)'.format(1000 * i, 1000 * (i + 1),
- len(v.get_valid_names(massif_names))) for i, v in
- enumerate(visualizer_list)]
- for x, color, percentage, label, percentage_significant in zip(x_shifted, colors, percentages, labels,
- percentages_significant):
- ax.bar([x], [percentage], width=width, label=label,
- linewidth=2 * linewidth, edgecolor='black', color=color)
- heights = list(range(0, math.ceil(percentage_significant), 1))[::-1]
- for height in heights:
- ax.bar([x], [height], width=width, linewidth=linewidth, edgecolor='black', color=color)
-
- handles, labels = ax.get_legend_handles_labels()
- ax.legend(handles[:len(visualizer_list)], labels[:len(visualizer_list)], prop={'size': size})
- ax.set_xticklabels(sorted_model_names)
- ax.set_xticks(tick_list)
- ax.set_ylabel('Percentage of massifs (\%) ', fontsize=legend_fontsize)
- ax.set_xlabel('Models', fontsize=legend_fontsize)
- ax.set_ylim(bottom=0)
- ax.yaxis.grid()
- ax.tick_params(axis='both', which='major', labelsize=labelsize)
-
- visualizer.plot_name = 'All models'
- visualizer.show_or_save_to_file(add_classic_title=False, no_title=True)
- plt.close()
+ # # Plot part
+ # ax = plt.gca()
+ # width = 5
+ # size = 8
+ # legend_fontsize = 10
+ # labelsize = 10
+ # linewidth = 1
+ # tick_list = np.array([((len(visualizer_list) + 2) * i + (1 + len(visualizer_list) / 2)) * width
+ # for i in range(len(sorted_model_names))])
+ # for tick_middle, model_name in zip(tick_list, sorted_model_names):
+ # x_shifted = [tick_middle + width * shift / 2 for shift in range(-3, 5, 2)]
+ # percentages = model_name_to_percentages[model_name]
+ # percentages_significant = model_name_to_percentages_significant[model_name]
+ # colors = ['white', 'yellow', 'orange', 'red']
+ # labels = ['{} m - {} m (\% out of {} massifs)'.format(1000 * i, 1000 * (i + 1),
+ # len(v.get_valid_names(massif_names))) for i, v in
+ # enumerate(visualizer_list)]
+ # for x, color, percentage, label, percentage_significant in zip(x_shifted, colors, percentages, labels,
+ # percentages_significant):
+ # ax.bar([x], [percentage], width=width, label=label,
+ # linewidth=2 * linewidth, edgecolor='black', color=color)
+ # heights = list(range(0, math.ceil(percentage_significant), 1))[::-1]
+ # for height in heights:
+ # ax.bar([x], [height], width=width, linewidth=linewidth, edgecolor='black', color=color)
+ #
+ # handles, labels = ax.get_legend_handles_labels()
+ # ax.legend(handles[:len(visualizer_list)], labels[:len(visualizer_list)], prop={'size': size})
+ # ax.set_xticklabels(sorted_model_names)
+ # ax.set_xticks(tick_list)
+ # ax.set_ylabel('Percentage of massifs (\%) ', fontsize=legend_fontsize)
+ # ax.set_xlabel('Models', fontsize=legend_fontsize)
+ # ax.set_ylim(bottom=0)
+ # ax.yaxis.grid()
+ # ax.tick_params(axis='both', which='major', labelsize=labelsize)
+ #
+ # visualizer.plot_name = 'All models'
+ # visualizer.show_or_save_to_file(add_classic_title=False, no_title=True)
+ # plt.close()
def plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list: List[
--
GitLab