[Confidence Interval] refactor shape visualizer

experiment/paper_past_snow_loads/check_mle_convergence_for_trends/main_shape_repartition.py

 from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
 from experiment.paper_past_snow_loads.check_mle_convergence_for_trends.study_visualizer_for_shape_repartition import \
-    StudyVisualizerForShape, StudyVisualizerGumbel, StudyVisualizerAll
+    StudyVisualizerForShape
 from experiment.paper_past_snow_loads.paper_main_utils import load_altitude_to_visualizer
 
 
@@ -28,6 +28,6 @@ if __name__ == '__main__':
     # main_shape_repartition([900], save_to_file=False)
     # main_shape_repartition([900, 1800, 2700])
     # main_shape_repartition([300, 600, 900, 1200, 1500, 1800, 2700])
-    main_shape_repartition([900], study_visualizer_class=StudyVisualizerAll, save_to_file=False)
-    # main_shape_repartition([300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900, 4200],
-    #                        study_visualizer_class=StudyVisualizerAll, save_to_file=True)
+    # main_shape_repartition([900], study_visualizer_class=StudyVisualizerForShape, save_to_file=False)
+    main_shape_repartition([300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900, 4200],
+                           study_visualizer_class=StudyVisualizerForShape, save_to_file=True)

experiment/paper_past_snow_loads/check_mle_convergence_for_trends/study_visualizer_for_shape_repartition.py

@@ -6,8 +6,6 @@ from experiment.meteo_france_data.scm_models_data.abstract_study import Abstract
 from experiment.paper_past_snow_loads.study_visualizer_for_non_stationary_trends import \
     StudyVisualizerForNonStationaryTrends
 from experiment.trend_analysis.abstract_score import MeanScore
-from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter import \
-    GevStationaryVersusGumbel
 
 
 class StudyVisualizerForShape(StudyVisualizerForNonStationaryTrends):
@@ -32,7 +30,6 @@ class StudyVisualizerForShape(StudyVisualizerForNonStationaryTrends):
 
     @cached_property
     def massif_name_to_change_value(self):
-        print(self.massif_name_to_unconstrained_shape_parameter)
         return self.massif_name_to_unconstrained_shape_parameter
 
     @property
@@ -48,36 +45,3 @@ class StudyVisualizerForShape(StudyVisualizerForNonStationaryTrends):
         return get_shifted_map(-self._max_abs_change, self._max_abs_change, matplotlib.cm.get_cmap('BrBG_r'))
 
 
-class StudyVisualizerGumbel(StudyVisualizerForShape):
-
-    def __init__(self, study: AbstractStudy, show=True, save_to_file=False, only_one_graph=False, only_first_row=False,
-                 vertical_kde_plot=False, year_for_kde_plot=None, plot_block_maxima_quantiles=False,
-                 temporal_non_stationarity=False, transformation_class=None, verbose=False, multiprocessing=False,
-                 complete_non_stationary_trend_analysis=False, normalization_under_one_observations=True,
-                 score_class=MeanScore, uncertainty_methods=None, non_stationary_contexts=None,
-                 uncertainty_massif_names=None, effective_temporal_covariate=2017, relative_change_trend_plot=True):
-        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,
-                         normalization_under_one_observations, score_class, uncertainty_methods,
-                         non_stationary_contexts, uncertainty_massif_names, effective_temporal_covariate,
-                         relative_change_trend_plot)
-        # Assign default argument for the non stationary trends
-        self.non_stationary_trend_test = [GevStationaryVersusGumbel]
-        self.non_stationary_trend_test_to_marker = dict(zip(self.non_stationary_trend_test, ["o"]))
-
-
-class StudyVisualizerAll(StudyVisualizerForShape):
-
-    def __init__(self, study: AbstractStudy, show=True, save_to_file=False, only_one_graph=False, only_first_row=False,
-                 vertical_kde_plot=False, year_for_kde_plot=None, plot_block_maxima_quantiles=False,
-                 temporal_non_stationarity=False, transformation_class=None, verbose=False, multiprocessing=False,
-                 complete_non_stationary_trend_analysis=False, normalization_under_one_observations=True,
-                 score_class=MeanScore, uncertainty_methods=None, non_stationary_contexts=None,
-                 uncertainty_massif_names=None, effective_temporal_covariate=2017, relative_change_trend_plot=True):
-        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,
-                         normalization_under_one_observations, score_class, uncertainty_methods,
-                         non_stationary_contexts, uncertainty_massif_names, effective_temporal_covariate,
-                         relative_change_trend_plot)

experiment/paper_past_snow_loads/study_visualizer_for_non_stationary_trends.py

@@ -76,7 +76,6 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
                                               GevLocationAgainstGumbel, GevScaleAgainstGumbel, GevLocationAndScaleTrendTestAgainstGumbel
                                               ]
             self.non_stationary_trend_test_to_marker = {t: t.marker for t in self.non_stationary_trend_test}
-                                                                # ["v", "^", "D", "X", "x", 7, 6, "d"]))
         else:
             self.non_stationary_trend_test = list(self.non_stationary_trend_test_to_marker.keys())
         self.global_max_abs_change = None