[contrasting] add display of name for NON_STATIONARY_TREND_TEST_PAPER_2

extreme_data/meteo_france_data/scm_models_data/visualization/plot_utils.py

@@ -23,7 +23,7 @@ def plot_against_altitude(altitudes, ax, massif_id, massif_name, values):
 
 
 def load_plot(cmap, graduation, label, massif_name_to_value, altitude, fit_method, add_x_label=True,
-              negative_and_positive_values=True):
+              negative_and_positive_values=True, massif_name_to_text=None):
     max_abs_change = max([abs(e) for e in massif_name_to_value.values()])
     if negative_and_positive_values:
         ticks, labels = ticks_values_and_labels_for_percentages(graduation=graduation, max_abs_change=max_abs_change)
@@ -54,6 +54,8 @@ def load_plot(cmap, graduation, label, massif_name_to_value, altitude, fit_metho
                                   ticks_values_and_labels=ticks_values_and_labels,
                                   label=label,
                                   fontsize_label=10,
+                                  massif_name_to_text=massif_name_to_text,
+                                  add_text=massif_name_to_text is not None,
                                   )
     ax.get_xaxis().set_visible(True)
     ax.set_xticks([])

extreme_data/meteo_france_data/scm_models_data/visualization/study_visualizer.py

@@ -709,20 +709,22 @@ class StudyVisualizer(VisualizationParameters):
     # PLot functions that should be common
 
     def plot_map(self, cmap, fit_method, graduation, label, massif_name_to_value, plot_name, add_x_label=True,
-                 negative_and_positive_values=True):
+                 negative_and_positive_values=True, massif_name_to_text=None):
         load_plot(cmap, graduation, label, massif_name_to_value, self.study.altitude, fitmethod_to_str(fit_method),
-                  add_x_label=add_x_label, negative_and_positive_values=negative_and_positive_values)
+                  add_x_label=add_x_label, negative_and_positive_values=negative_and_positive_values,
+                  massif_name_to_text=massif_name_to_text)
         self.plot_name = plot_name
         # self.show_or_save_to_file(add_classic_title=False, tight_layout=True, no_title=True, dpi=500)
         self.show_or_save_to_file(add_classic_title=False, no_title=True, dpi=500)
         plt.close()
 
     def plot_abstract(self, massif_name_to_value, label, plot_name, fit_method='', graduation=10.0, cmap=plt.cm.bwr,
-                      add_x_label=True, negative_and_positive_values=True):
+                      add_x_label=True, negative_and_positive_values=True, massif_name_to_text=None):
         # Regroup the plot by altitudes
         plot_name1 = '{}/{}'.format(self.study.altitude, plot_name)
         # Regroup the plot by type of plot also
         plot_name2 = '{}/{}'.format(plot_name.split()[0], plot_name)
         for plot_name in [plot_name1, plot_name2]:
-            self.plot_map(cmap, fit_method, graduation, label, massif_name_to_value, plot_name, add_x_label, negative_and_positive_values)
+            self.plot_map(cmap, fit_method, graduation, label, massif_name_to_value, plot_name, add_x_label, negative_and_positive_values,
+                          massif_name_to_text)
 

extreme_trend/abstract_gev_trend_test.py

@@ -79,6 +79,31 @@ class AbstractGevTrendTest(object):
         test = cramer_von_mises_and_anderson_darling_tests_pvalues_for_gumbel_distribution(quantiles)
         return test[1] > self.SIGNIFICANCE_LEVEL
 
+    @property
+    def name(self):
+        if self.constrained_model_class is GumbelTemporalModel:
+            family = 'Gum'
+        else:
+            family = 'Gev'
+
+        if self.unconstrained_estimator.margin_model.mul == 1:
+            family += '1'
+        else:
+            family += '0'
+
+        if self.unconstrained_estimator.margin_model.sigl == 1:
+            family += '1'
+        else:
+            family += '0'
+
+        if family.startswith('Gev'):
+            if self.unconstrained_estimator.margin_model.shl == 1:
+                family += '1'
+            else:
+                family += '0'
+
+        return family
+
     @property
     def degree_freedom_chi2(self) -> int:
         raise NotImplementedError
@@ -225,7 +250,6 @@ class AbstractGevTrendTest(object):
         ax.set_ylabel("Non-zero annual maxima of GSL ({})".format(AbstractSnowLoadVariable.UNIT), fontsize=size)
         ax.legend(prop={'size': 17})
 
-
     def intensity_plot_wrt_standard_gumbel(self, massif_name, altitude, psnow):
         ax = plt.gca()
         sorted_maxima = sorted(self.maxima)
@@ -446,7 +470,7 @@ class AbstractGevTrendTest(object):
 
     def unconstrained_average_mean_value(self, year_min, year_max) -> float:
         mean_values = []
-        for year in range(year_min, year_max+1):
+        for year in range(year_min, year_max + 1):
             mean = self.get_unconstrained_gev_params(year).mean
             mean_values.append(mean)
         average_mean_value = np.mean(mean_values)

extreme_trend/trend_test_two_parameters/gev_trend_test_two_parameters.py

@@ -17,7 +17,8 @@ class GevTrendTestTwoParameters(AbstractGevTrendTest):
     def degree_freedom_chi2(self) -> int:
         return 2
 
-class GevTrendTestTwoParametersAgainstGev(AbstractGevTrendTest):
+
+class GevTrendTestTwoParametersAgainstGev(GevTrendTestTwoParameters):
 
     @classproperty
     def total_number_of_parameters_for_unconstrained_model(cls) -> int:
@@ -25,7 +26,7 @@ class GevTrendTestTwoParametersAgainstGev(AbstractGevTrendTest):
 
 
 class GevLocationAndShapeTrendTest(GevTrendTestTwoParametersAgainstGev):
-    
+
     def __init__(self, years, maxima, starting_year, constrained_model_class=StationaryTemporalModel,
                  quantile_level=EUROCODE_QUANTILE, fit_method=MarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
@@ -37,7 +38,6 @@ class GevLocationAndShapeTrendTest(GevTrendTestTwoParametersAgainstGev):
 
 class GevScaleAndShapeTrendTest(GevTrendTestTwoParametersAgainstGev):
 
-
     def __init__(self, years, maxima, starting_year, constrained_model_class=StationaryTemporalModel,
                  quantile_level=EUROCODE_QUANTILE, fit_method=MarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
@@ -83,7 +83,8 @@ class GevLocationAndScaleTrendTest(GevTrendTestTwoParametersAgainstGev):
 
 class GevLocationAgainstGumbel(GevTrendTestTwoParameters, GevLocationTrendTest):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=MarginFitMethod.extremes_fevd_mle):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE,
+                 fit_method=MarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year, quantile_level, GumbelTemporalModel, fit_method=fit_method)
 
     @classproperty
@@ -101,7 +102,8 @@ class GevLocationAgainstGumbel(GevTrendTestTwoParameters, GevLocationTrendTest):
 
 class GevScaleAgainstGumbel(GevTrendTestTwoParameters, GevScaleTrendTest):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=MarginFitMethod.extremes_fevd_mle):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE,
+                 fit_method=MarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year, quantile_level, GumbelTemporalModel, fit_method=fit_method)
 
     @classproperty

projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py

@@ -9,6 +9,7 @@ from projects.contrasting_trends_in_snow_loads.article2_snowfall_versus_time_and
 from projects.contrasting_trends_in_snow_loads.article2_snowfall_versus_time_and_altitude.study_visualizer_for_mean_values import \
     StudyVisualizerForMeanValues
 from projects.contrasting_trends_in_snow_loads.article2_snowfall_versus_time_and_altitude.validation_plot import validation_plot
+from projects.exceeding_snow_loads.section_results.plot_selection_curves import plot_selection_curves
 from projects.exceeding_snow_loads.section_results.plot_trend_curves import plot_trend_map
 
 mpl.rcParams['text.usetex'] = True
@@ -75,6 +76,7 @@ def intermediate_result(altitudes, massif_names=None,
     validation_plot(altitude_to_visualizer, order_derivative=0)
     # validation_plot(altitude_to_visualizer, order_derivative=1)
     plot_snowfall_mean(altitude_to_visualizer)
+    plot_selection_curves(altitude_to_visualizer, paper1=False)
     # plot_snowfall_time_derivative_mean(altitude_to_visualizer)
 
 
@@ -85,10 +87,10 @@ def major_result():
     study_classes = [SafranSnowfall1Day]
     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]
-    draft_altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000]
-    altitudes = draft_altitudes
+    # altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900]
+    altitudes = [900, 1200, 1500, 1800]
+    # 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,

projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py

+from collections import Counter
 from typing import Dict
 
 import matplotlib.pyplot as plt
@@ -37,9 +38,23 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
         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):
+                           negative_and_positive_values=True, add_text=False):
+        massif_name_to_text = self.massif_name_to_text if add_text else None
         super().plot_abstract(massif_name_to_value, label, label, self.fit_method, graduation, cmap, add_x_label,
-                              negative_and_positive_values)
+                              negative_and_positive_values, massif_name_to_text)
+
+    @property
+    def massif_name_to_text(self):
+        d = {}
+        for m, t in self.massif_name_to_trend_test_that_minimized_aic.items():
+            if t.is_significant:
+                name = '$\\textbf{'
+                name += t.name
+                name += '}$'
+            else:
+                name = '${}$'.format(t.name)
+            d[m] = name
+        return d
 
     # Override the main dict massif_name_to_trend_test_that_minimized_aic
 
@@ -48,6 +63,10 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
         return {m: t for m, t in super().massif_name_to_trend_test_that_minimized_aic.items()
                 if t.goodness_of_fit_anderson_test}
 
+    @property
+    def super_massif_name_to_trend_test_that_minimized_aic(self):
+        return super().massif_name_to_trend_test_that_minimized_aic
+
     # Study of the mean
 
     @cached_property

projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/validation_plot.py

@@ -23,9 +23,9 @@ def validation_plot(altitude_to_visualizer: Dict[int, StudyVisualizerForMeanValu
     for altitude, visualizer in altitude_to_visualizer.items():
         altitude_to_relative_differences[altitude] = plot_function(visualizer)
         study_visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
-    # Shoe plot with respect to the altitude.
-    plot_shoe_relative_differences_distribution(altitude_to_relative_differences, altitudes, study_visualizer,
-                                                order_derivative)
+    # # Shoe plot with respect to the altitude.
+    # plot_shoe_relative_differences_distribution(altitude_to_relative_differences, altitudes, study_visualizer,
+    #                                             order_derivative)
     study_visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
     plt.close()
 
@@ -51,13 +51,13 @@ def plot_shoe_relative_differences_distribution(altitude_to_relative_differences
 def plot_relative_difference_map_order_zero(visualizer: StudyVisualizerForMeanValues):
     study = visualizer.study
     label = ' mean annual maxima of {} ({})'.format(SCM_STUDY_CLASS_TO_ABBREVIATION[type(study)], study.variable_unit)
-    visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_empirical_mean,
-                                  label='Empirical' + label, negative_and_positive_values=False)
+    # visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_empirical_mean,
+    #                               label='Empirical' + label, negative_and_positive_values=False)
     visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_model_mean,
-                                  label='Model' + label, negative_and_positive_values=False)
-    visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_relative_difference_for_mean,
-                                  label='Relative difference of the model mean w.r.t. the empirical mean \n'
-                                        'for the ' + label, graduation=1)
+                                  label='Model' + label, negative_and_positive_values=False, add_text=True)
+    # visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_relative_difference_for_mean,
+    #                               label='Relative difference of the model mean w.r.t. the empirical mean \n'
+    #                                     'for the ' + label, graduation=1)
     return list(visualizer.massif_name_to_relative_difference_for_mean.values())
 
 

projects/exceeding_snow_loads/utils.py

@@ -31,9 +31,18 @@ NON_STATIONARY_TREND_TEST_PAPER_2 = [
     # Gumbel models
     GumbelVersusGumbel, GumbelLocationTrendTest, GumbelScaleTrendTest, GumbelLocationAndScaleTrendTest,
     # GEV models with constant shape
-    GevVersusGev, GevLocationTrendTest, GevScaleTrendTest,  GevLocationAndScaleTrendTest,
+    GevVersusGev, GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest,
     # GEV models with linear shape
     GevShapeTrendTest, GevLocationAndShapeTrendTest, GevScaleAndShapeTrendTest, GevLocationAndScaleAndShapeTrendTest
 ]
 
 
+def get_trend_test_name(trend_test_class):
+    years = list(range(10))
+    trend_test = trend_test_class(years, years, None)
+    return trend_test.name
+
+
+if __name__ == '__main__':
+    for trend_test_class in NON_STATIONARY_TREND_TEST_PAPER_2:
+        print(get_trend_test_name(trend_test_class))