From 86a1593b8b8898c17513d2982199818773b5db30 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Fri, 7 Feb 2020 18:10:03 +0100
Subject: [PATCH] [paper 1] add plot selection curves. refactor imports
---
.../exceeding_snow_loads/paper_main_utils.py | 5 +-
.../main_result_trends_and_return_levels.py | 18 ++--
.../plot_selection_curves.py | 101 ++++++++++++++++++
.../plot_uncertainty_histogram.py | 4 +-
...dy_visualizer_for_non_stationary_trends.py | 14 ++-
5 files changed, 127 insertions(+), 15 deletions(-)
create mode 100644 papers/exceeding_snow_loads/result_trends_and_return_levels/plot_selection_curves.py
diff --git a/papers/exceeding_snow_loads/paper_main_utils.py b/papers/exceeding_snow_loads/paper_main_utils.py
index a4ff6384..4b5fc27d 100644
--- a/papers/exceeding_snow_loads/paper_main_utils.py
+++ b/papers/exceeding_snow_loads/paper_main_utils.py
@@ -1,10 +1,9 @@
from collections import OrderedDict
-from enum import Enum
-from experiment.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
- StudyVisualizerForNonStationaryTrends
from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
TemporalMarginFitMethod
+from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
+ StudyVisualizerForNonStationaryTrends
def load_altitude_to_visualizer(altitudes, massif_names, model_subsets_for_uncertainty, study_class,
diff --git a/papers/exceeding_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py b/papers/exceeding_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py
index 65d14343..043da14e 100644
--- a/papers/exceeding_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py
+++ b/papers/exceeding_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py
@@ -6,6 +6,9 @@ from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSno
from papers.exceeding_snow_loads.paper_main_utils import load_altitude_to_visualizer
from papers.exceeding_snow_loads.paper_utils import paper_study_classes, paper_altitudes
from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_diagnosis_risk import plot_diagnosis_risk
+from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_selection_curves import plot_selection_curves
+from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_trend_curves import plot_trend_curves
+from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_uncertainty_curves import plot_uncertainty_massifs
from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_uncertainty_histogram import \
plot_uncertainty_histogram
from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
@@ -63,10 +66,11 @@ def intermediate_result(altitudes, massif_names=None,
# Plots
# plot_trend_map(altitude_to_visualizer)
- plot_diagnosis_risk(altitude_to_visualizer)
+ # plot_diagnosis_risk(altitude_to_visualizer)
# plot_trend_curves(altitude_to_visualizer={a: v for a, v in altitude_to_visualizer.items() if a >= 900})
# plot_uncertainty_massifs(altitude_to_visualizer)
- plot_uncertainty_histogram(altitude_to_visualizer)
+ # plot_uncertainty_histogram(altitude_to_visualizer)
+ plot_selection_curves(altitude_to_visualizer)
def major_result():
@@ -86,11 +90,11 @@ def major_result():
if __name__ == '__main__':
- # major_result()
- intermediate_result(altitudes=[1500, 1800], massif_names=None,
- uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
- ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
- multiprocessing=True)
+ major_result()
+ # intermediate_result(altitudes=[1500, 1800][:1], massif_names=None,
+ # uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
+ # ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
+ # multiprocessing=True)
# intermediate_result(altitudes=[900, 1200], massif_names=['Maurienne'],
# uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
# ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
diff --git a/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_selection_curves.py b/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_selection_curves.py
new file mode 100644
index 00000000..dfb96643
--- /dev/null
+++ b/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_selection_curves.py
@@ -0,0 +1,101 @@
+from typing import Dict
+from collections import Counter
+import matplotlib.pyplot as plt
+
+from experiment.meteo_france_data.scm_models_data.abstract_extended_study import AbstractExtendedStudy
+from experiment.meteo_france_data.scm_models_data.visualization.utils import create_adjusted_axes
+from papers.exceeding_snow_loads.paper_utils import dpi_paper1_figure
+from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import StudyVisualizerForNonStationaryTrends
+from itertools import chain
+
+def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNonStationaryTrends]):
+ """
+ Plot a single trend curves
+ :return:
+ """
+ visualizer = list(altitude_to_visualizer.values())[0]
+
+ ax = create_adjusted_axes(1, 1)
+
+ selected_counter = merge_counter([v.selected_trend_test_class_counter for v in altitude_to_visualizer.values()])
+ selected_and_significative_counter = merge_counter([v.selected_and_significative_trend_test_class_counter for v in altitude_to_visualizer.values()])
+ total_of_selected_models = sum(selected_counter.values())
+ select_list = get_ordered_list_from_counter(selected_counter, total_of_selected_models, visualizer)
+ selected_and_signifcative_list = get_ordered_list_from_counter(selected_and_significative_counter, total_of_selected_models, visualizer)
+ print(select_list)
+ print(selected_and_signifcative_list)
+
+ # parameters
+ width = 5
+ size = 20
+ legend_fontsize = 20
+ color = 'white'
+ labelsize = 15
+ linewidth = 3
+ x = [10 * (i+1) for i in range(len(select_list))]
+ ax.bar(x, select_list, width=width, color=color, edgecolor='blue', label='selected model',
+ linewidth=linewidth)
+ ax.bar(x, selected_and_signifcative_list, width=width, color=color, edgecolor='black',
+ label='significative selected model',
+ linewidth=linewidth)
+ ax.legend(loc='upper left', prop={'size': size})
+ ax.set_ylabel('Selected model (\%)', fontsize=legend_fontsize)
+ ax.set_xlabel('Models', fontsize=legend_fontsize)
+
+ ax.set_xticks(x)
+ labels = ['${}$'.format(t.label) for t in visualizer.non_stationary_trend_test]
+ ax.set_xticklabels(labels)
+
+ # for ax_horizontal in [ax, ax_twiny]:
+ # if ax_horizontal == ax_twiny:
+ # ax_horizontal.plot(altitudes, [0 for _ in altitudes], linewidth=0)
+ # else:
+ # ax_horizontal.set_xlabel('Altitude', fontsize=legend_fontsize)
+ # ax_horizontal.set_xticks(altitudes)
+ # ax_horizontal.set_xlim([700, 5000])
+ # ax_horizontal.tick_params(labelsize=labelsize)
+ #
+ # # Set the number of massifs on the upper axis
+ # ax_twiny.set_xticklabels([v.study.nb_study_massif_names for v in altitude_to_visualizer.values()])
+ # ax_twiny.set_xlabel('Total number of massifs at each altitude (for the percentage)', fontsize=legend_fontsize)
+ #
+ # ax.set_ylabel('Massifs with decreasing trend (\%)', fontsize=legend_fontsize)
+ # max_percent = int(max(percent_decrease))
+ # n = 2 + (max_percent // 10)
+ # ax_ticks = [10 * i for i in range(n)]
+ # # upper_lim = max_percent + 3
+ # upper_lim = n + 5
+ # ax_lim = [0, upper_lim]
+ # for axis in [ax, ax_twinx]:
+ # axis.set_ylim(ax_lim)
+ # axis.set_yticks(ax_ticks)
+ # axis.tick_params(labelsize=labelsize)
+ # ax.yaxis.grid()
+ #
+ # label_curve = (visualizer.label).replace('change', 'decrease')
+ # ax_twinx.set_ylabel(label_curve.replace('', ''), fontsize=legend_fontsize)
+ # for region_name, mean_decrease in zip(AbstractExtendedStudy.region_names, mean_decreases):
+ # if len(mean_decreases) > 1:
+ # label = region_name
+ # else:
+ # label = 'Mean relative decrease'
+ # ax_twinx.plot(altitudes, mean_decrease, label=label, linewidth=linewidth, marker='o')
+ # ax_twinx.legend(loc='upper right', prop={'size': size})
+
+ # Save plot
+ plt.show()
+ visualizer.plot_name = 'Selection curves'
+ visualizer.show_or_save_to_file(no_title=True, dpi=dpi_paper1_figure)
+ plt.close()
+
+
+def get_ordered_list_from_counter(selected_counter, total_of_selected_models, visualizer):
+ return [100 * float(selected_counter[t]) / total_of_selected_models if t in selected_counter else 0
+ for t in visualizer.non_stationary_trend_test]
+
+def merge_counter(counters_list):
+ global_counter = counters_list[0]
+ for c in counters_list[1:]:
+ global_counter += c
+ return global_counter
+
diff --git a/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_histogram.py b/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_histogram.py
index a9a9f95c..76936a3d 100644
--- a/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_histogram.py
+++ b/papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_histogram.py
@@ -3,8 +3,8 @@ import matplotlib.pyplot as plt
import numpy as np
from experiment.eurocode_data.utils import EUROCODE_RETURN_LEVEL_STR, EUROCODE_ALTITUDES
-from experiment.exceeding_snow_loads.paper_utils import dpi_paper1_figure, ModelSubsetForUncertainty
-from experiment.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
+from papers.exceeding_snow_loads.paper_utils import dpi_paper1_figure, ModelSubsetForUncertainty
+from papers.exceeding_snow_loads.study_visualizer_for_non_stationary_trends import \
StudyVisualizerForNonStationaryTrends
from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import ci_method_to_color, \
ci_method_to_label, ConfidenceIntervalMethodFromExtremes
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 0ea784f8..cd7b1748 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
@@ -1,4 +1,4 @@
-from collections import OrderedDict
+from collections import OrderedDict, Counter
from multiprocessing.pool import Pool
from typing import Dict, List, Tuple
@@ -14,9 +14,9 @@ from experiment.meteo_france_data.scm_models_data.abstract_extended_study import
from experiment.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
StudyVisualizer
-from experiment.exceeding_snow_loads.check_mcmc_convergence_for_return_levels.gelman_convergence_test import \
+from papers.exceeding_snow_loads.check_mcmc_convergence_for_return_levels.gelman_convergence_test import \
compute_gelman_convergence_value
-from experiment.exceeding_snow_loads.paper_utils import ModelSubsetForUncertainty
+from papers.exceeding_snow_loads.paper_utils import ModelSubsetForUncertainty
from experiment.trend_analysis.abstract_score import MeanScore
from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import AbstractGevTrendTest
from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gumbel_trend_test_one_parameter import \
@@ -278,6 +278,14 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
return {m: get_colors([v], self.cmap, -self._max_abs_change, self._max_abs_change)[0]
for m, v in self.massif_name_to_change_value.items()}
+ @cached_property
+ def selected_trend_test_class_counter(self):
+ return Counter([type(t) for t in self.massif_name_to_trend_test_that_minimized_aic.values()])
+
+ @cached_property
+ def selected_and_significative_trend_test_class_counter(self):
+ return Counter([type(t) for t in self.massif_name_to_trend_test_that_minimized_aic.values() if t.is_significant])
+
@cached_property
def massif_name_to_marker_style(self):
d = {}
--
GitLab