From b6c39b54251c639fc6280914a537769efff9c136 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Thu, 11 Jun 2020 15:18:36 +0200
Subject: [PATCH] [contrasting] use NON_STATIONARY_TREND_TEST_PAPER_2 in study
visualizer for mean values
---
.../scm_models_data/abstract_study.py | 8 ++++--
.../gev_trend_test_three_parameters.py | 4 +--
.../main_snowfall_article.py | 6 ++--
.../study_visualizer_for_mean_values.py | 28 +++++++++++++++----
4 files changed, 34 insertions(+), 12 deletions(-)
diff --git a/extreme_data/meteo_france_data/scm_models_data/abstract_study.py b/extreme_data/meteo_france_data/scm_models_data/abstract_study.py
index 32d1fcfb..0ea55349 100644
--- a/extreme_data/meteo_france_data/scm_models_data/abstract_study.py
+++ b/extreme_data/meteo_france_data/scm_models_data/abstract_study.py
@@ -492,6 +492,7 @@ class AbstractStudy(object):
massif_name_to_marker_style=None,
marker_style_to_label_name=None,
ticks_values_and_labels=None,
+ massif_name_to_text=None,
fontsize_label=15,
):
if ax is None:
@@ -563,8 +564,11 @@ class AbstractStudy(object):
for _, row in masssif_coordinate_for_display.df_all_coordinates.iterrows():
x, y = list(row)
massif_name = row.name
- value = massif_name_to_value[massif_name]
- str_value = str(value)
+ if massif_name_to_text is None:
+ value = massif_name_to_value[massif_name]
+ str_value = str(value)
+ else:
+ str_value = massif_name_to_text[massif_name]
ax.text(x, y, str_value, horizontalalignment='center', verticalalignment='center', fontsize=fontsize)
if scaled:
diff --git a/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py b/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py
index caaed063..dc411f3a 100644
--- a/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py
+++ b/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py
@@ -21,8 +21,8 @@ class GevLocationAndScaleAndShapeTrendTest(GevTrendTestThreeParameters):
def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE,
fit_method=MarginFitMethod.extremes_fevd_mle):
super().__init__(years, maxima, starting_year,
- unconstrained_model_class=StationaryTemporalModel,
- constrained_model_class=NonStationaryLocationAndScaleAndShapeTemporalModel,
+ unconstrained_model_class=NonStationaryLocationAndScaleAndShapeTemporalModel,
+ constrained_model_class=StationaryTemporalModel,
quantile_level=quantile_level,
fit_method=fit_method)
diff --git a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py
index 06759a89..db109f24 100644
--- a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py
+++ b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py
@@ -72,7 +72,7 @@ def intermediate_result(altitudes, massif_names=None,
_ = compute_minimized_aic(visualizer)
# Plots
- # validation_plot(altitude_to_visualizer, order_derivative=0)
+ validation_plot(altitude_to_visualizer, order_derivative=0)
# validation_plot(altitude_to_visualizer, order_derivative=1)
plot_snowfall_mean(altitude_to_visualizer)
# plot_snowfall_time_derivative_mean(altitude_to_visualizer)
@@ -86,7 +86,9 @@ def major_result():
model_subsets_for_uncertainty = None
altitudes = paper_altitudes
altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900]
- altitudes = [900, 1200]
+ # altitudes = [900, 1200]
+ draft_altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000]
+ altitudes = draft_altitudes
for study_class in study_classes:
intermediate_result(altitudes, massif_names, model_subsets_for_uncertainty,
diff --git a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py
index ca2cfce6..ab0586f6 100644
--- a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py
+++ b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py
@@ -1,3 +1,5 @@
+from typing import Dict
+
import matplotlib.pyplot as plt
import numpy as np
from cached_property import cached_property
@@ -5,7 +7,9 @@ from cached_property import cached_property
from extreme_data.eurocode_data.utils import YEAR_OF_INTEREST_FOR_RETURN_LEVEL
from extreme_data.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
from extreme_fit.model.margin_model.utils import MarginFitMethod
+from extreme_trend.abstract_gev_trend_test import AbstractGevTrendTest
from extreme_trend.visualizers.study_visualizer_for_non_stationary_trends import StudyVisualizerForNonStationaryTrends
+from projects.exceeding_snow_loads.utils import NON_STATIONARY_TREND_TEST_PAPER_2
class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
@@ -19,6 +23,10 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
non_stationary_trend_test_to_marker=None, fit_method=MarginFitMethod.extremes_fevd_mle,
select_only_acceptable_shape_parameter=True, fit_gev_only_on_non_null_maxima=False,
fit_only_time_series_with_ninety_percent_of_non_null_values=True):
+
+ # Change the type of models used in the study
+ non_stationary_trend_test_to_marker = {c: '' for c in NON_STATIONARY_TREND_TEST_PAPER_2}
+
super().__init__(study, show, save_to_file, only_one_graph, only_first_row, vertical_kde_plot,
year_for_kde_plot, plot_block_maxima_quantiles, temporal_non_stationarity,
transformation_class, verbose, multiprocessing, complete_non_stationary_trend_analysis,
@@ -26,11 +34,19 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
uncertainty_massif_names, effective_temporal_covariate, relative_change_trend_plot,
non_stationary_trend_test_to_marker, fit_method, select_only_acceptable_shape_parameter,
fit_gev_only_on_non_null_maxima, fit_only_time_series_with_ninety_percent_of_non_null_values)
-
+ assert len(self.non_stationary_trend_test) == len(NON_STATIONARY_TREND_TEST_PAPER_2)
def plot_abstract_fast(self, massif_name_to_value, label, graduation=10.0, cmap=plt.cm.coolwarm, add_x_label=True,
negative_and_positive_values=True):
- super().plot_abstract(massif_name_to_value, label, label, self.fit_method, graduation, cmap, add_x_label, negative_and_positive_values)
+ super().plot_abstract(massif_name_to_value, label, label, self.fit_method, graduation, cmap, add_x_label,
+ negative_and_positive_values)
+
+ # Override the main dict massif_name_to_trend_test_that_minimized_aic
+
+ @property
+ def massif_name_to_trend_test_that_minimized_aic(self) -> Dict[str, AbstractGevTrendTest]:
+ return {m: t for m, t in super().massif_name_to_trend_test_that_minimized_aic.items()
+ if t.goodness_of_fit_anderson_test}
# Study of the mean
@@ -55,7 +71,7 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
for massif_name in self.massif_name_to_trend_test_that_minimized_aic.keys():
e = self.massif_name_to_empirical_mean[massif_name]
m = self.massif_name_to_model_mean[massif_name]
- relative_diference = 100 * (m-e) / e
+ relative_diference = 100 * (m - e) / e
massif_name_to_relative_difference[massif_name] = relative_diference
return massif_name_to_relative_difference
@@ -66,7 +82,7 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
massif_name_to_empirical_value = {}
for massif_name, maxima in self.study.massif_name_to_annual_maxima.items():
index = self.study.ordered_years.index(1989)
- maxima_before, maxima_after = maxima[:index+1], maxima[index+1:]
+ maxima_before, maxima_after = maxima[:index + 1], maxima[index + 1:]
massif_name_to_empirical_value[massif_name] = np.mean(maxima_after) / np.mean(maxima_before)
return massif_name_to_empirical_value
@@ -85,6 +101,6 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
for massif_name in self.massif_name_to_trend_test_that_minimized_aic.keys():
e = self.massif_name_to_change_ratio_in_empirical_mean[massif_name]
m = self.massif_name_to_change_ratio_in_model_mean[massif_name]
- relative_diference = 100 * (m-e) / e
+ relative_diference = 100 * (m - e) / e
massif_name_to_relative_difference[massif_name] = relative_diference
- return massif_name_to_relative_difference
\ No newline at end of file
+ return massif_name_to_relative_difference
--
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