[projection snowfall] modify interval limits. plot both merge & mean aggregation.

extreme_data/meteo_france_data/adamont_data/cmip5/temperature_to_year.py

@@ -53,15 +53,15 @@ def plot_nb_data_one_line(ax, gcm, scenario, left_limits, right_limits, first_sc
     linestyle = get_linestyle_from_scenario(scenario)
 
     # Filter out the zero value
-    nb_data, left_limits = np.array(nb_data), np.array(left_limits)
+    nb_data, right_limits = np.array(nb_data), np.array(right_limits)
     ind = np.array(nb_data) > 0
-    nb_data, left_limits = nb_data[ind], left_limits[ind]
+    nb_data, right_limits = nb_data[ind], right_limits[ind]
 
     # For the legend
     if (len(nb_data) > 0) and first_scenario:
-        ax.plot(left_limits[0], nb_data[0], color=color, linestyle='solid', label=gcm)
+        ax.plot(right_limits[0], nb_data[0], color=color, linestyle='solid', label=gcm)
 
-    ax.plot(left_limits, nb_data, linestyle=linestyle, color=color, marker='o')
+    ax.plot(right_limits, nb_data, linestyle=linestyle, color=color, marker='o')
 
 
 def plot_nb_data(is_temperature_interval, is_shift_interval):
@@ -75,7 +75,7 @@ def plot_nb_data(is_temperature_interval, is_shift_interval):
 
     ax.legend()
     ticks_labels = get_ticks_labels_for_interval(is_temperature_interval, is_shift_interval)
-    ax.set_xticks(left_limit)
+    ax.set_xticks(right_limit)
     ax.set_xticklabels(ticks_labels)
     # ax.set_xlabel('Interval')
     ax.set_ylabel('Nb of Maxima')
@@ -101,8 +101,8 @@ def get_interval_limits(is_temperature_interval, is_shift_interval):
         year_max = [2050 + shift * i for i in range(nb)]
         left_limit, right_limit = year_min, year_max
     if not is_shift_interval:
-        max_interval_right = max(right_limit)
-        right_limit = [max_interval_right for _ in left_limit]
+        min_interval_left = min(left_limit)
+        left_limit = [min_interval_left for _ in right_limit]
     return left_limit, right_limit
 
 

extreme_trend/ensemble_fit/independent_ensemble_fit/visualizer_merge.py

@@ -23,6 +23,7 @@ class VisualizerMerge(AltitudesStudiesVisualizerForNonStationaryModels):
                  merge_function=np.median):
         self.merge_function = merge_function
         self.visualizers = visualizers
+        assert len(visualizers) > 0
         super().__init__(studies=visualizers[0].studies, model_classes=model_classes, show=show, massif_names=massif_names,
                          fit_method=fit_method, temporal_covariate_for_fit=temporal_covariate_for_fit,
                          display_only_model_that_pass_anderson_test=display_only_model_that_pass_anderson_test,

extreme_trend/ensemble_fit/visualizer_for_sensitivity.py

@@ -13,6 +13,8 @@ from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fi
 from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
 from extreme_trend.one_fold_fit.altitude_group import get_altitude_class_from_altitudes, \
     get_linestyle_for_altitude_class
+from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
+    AnomalyTemperatureWithSplineTemporalCovariate
 
 
 class VisualizerForSensivity(object):
@@ -26,19 +28,19 @@ class VisualizerForSensivity(object):
                  display_only_model_that_pass_gof_test=False,
                  confidence_interval_based_on_delta_method=False,
                  remove_physically_implausible_models=False,
-                 merge_visualizer_str=AbstractEnsembleFit.Median_merge,  # if we choose the Mean merge, then it is almost impossible to obtain stationary trends
                  is_temperature_interval=False,
                  is_shift_interval=False,
                  ):
         self.is_shift_interval = is_shift_interval
+        self.temporal_covariate_for_fit = temporal_covariate_for_fit
         self.is_temperature_interval = is_temperature_interval
-        self.merge_visualizer_str = merge_visualizer_str
+        self.merge_visualizer_str_list = (AbstractEnsembleFit.Median_merge, AbstractEnsembleFit.Mean_merge)
         self.altitudes_list = altitudes_list
         self.massif_names = massif_names
         self.left_limits, self.right_limits = get_interval_limits(self.is_temperature_interval,
-                                                                  self.is_shift_interval)
+                                                                   self.is_shift_interval)
         self.left_limit_to_right_limit = OrderedDict(zip(self.left_limits, self.right_limits))
-        self.left_limit_to_visualizer = {} # type: Dict[float, VisualizerForProjectionEnsemble]
+        self.right_limit_to_visualizer = {} # type: Dict[float, VisualizerForProjectionEnsemble]
 
         for left_limit, right_limit in zip(self.left_limits, self.right_limits):
             print("Interval is", left_limit, right_limit)
@@ -63,7 +65,7 @@ class VisualizerForSensivity(object):
                 remove_physically_implausible_models=remove_physically_implausible_models,
                 gcm_to_year_min_and_year_max=gcm_to_year_min_and_year_max
             )
-            self.left_limit_to_visualizer[left_limit] = visualizer
+            self.right_limit_to_visualizer[right_limit] = visualizer
 
     def plot(self):
         # todo: before reactivating the subplot, i should ensure that we can modify the prefix
@@ -71,53 +73,60 @@ class VisualizerForSensivity(object):
         # , and not just the plots for the last t_min
         # for visualizer in self.temp_min_to_visualizer.values():
         #     visualizer.plot()
-        self.sensitivity_plot()
+        for merge_visualizer_str in self.merge_visualizer_str_list:
+            self.sensitivity_plot(merge_visualizer_str)
 
-    def sensitivity_plot(self):
+    def sensitivity_plot(self, merge_visualizer_str):
         ax = plt.gca()
         for altitudes in self.altitudes_list:
             altitude_class = get_altitude_class_from_altitudes(altitudes)
-            self.interval_plot(ax, altitude_class)
+            self.interval_plot(ax, altitude_class, merge_visualizer_str)
 
         ticks_labels = get_ticks_labels_for_interval(self.is_temperature_interval, self.is_shift_interval)
         ax.set_ylabel('Percentages of massifs (\%)')
         ax.set_xlabel('Interval used to compute the trends ')
-        ax.set_xticks(self.left_limits)
+        ax.set_xticks(self.right_limits)
         ax.set_xticklabels(ticks_labels)
         ax.legend(prop={'size': 7}, loc='upper center', ncol=2)
         ax.set_ylim((0, 122))
         ax.set_yticks([i*10 for i in range(11)])
-        merge_visualizer = self.first_merge_visualizer
-        merge_visualizer.plot_name = 'Sensitivity plot'
+        merge_visualizer = self.first_merge_visualizer(merge_visualizer_str)
+        temp_cov = self.temporal_covariate_for_fit is AnomalyTemperatureWithSplineTemporalCovariate
+        merge_visualizer.plot_name = 'Sensitivity plot with ' \
+                                     'shift={} temp_interval={}, temp_cov={}'.format(self.is_shift_interval,
+                                                                                     self.is_temperature_interval,
+                                                                                     temp_cov)
         merge_visualizer.show_or_save_to_file(no_title=True)
+        plt.close()
 
-    @property
-    def first_merge_visualizer(self):
+    def first_merge_visualizer(self, merge_visualizer_str):
         altitude_class = get_altitude_class_from_altitudes(self.altitudes_list[0])
-        visualizer_projection = list(self.left_limit_to_visualizer.values())[0]
-        return self.get_merge_visualizer(altitude_class, visualizer_projection)
+        visualizer_projection = list(self.right_limit_to_visualizer.values())[0]
+        return self.get_merge_visualizer(altitude_class, visualizer_projection, merge_visualizer_str)
 
-    def get_merge_visualizer(self, altitude_class, visualizer_projection: VisualizerForProjectionEnsemble):
+    def get_merge_visualizer(self, altitude_class, visualizer_projection: VisualizerForProjectionEnsemble,
+                             merge_visualizer_str):
         independent_ensemble_fit = visualizer_projection.altitude_class_to_ensemble_class_to_ensemble_fit[altitude_class][
             IndependentEnsembleFit]
-        merge_visualizer = independent_ensemble_fit.merge_function_name_to_visualizer[self.merge_visualizer_str]
-        merge_visualizer.studies.study.gcm_rcm_couple = (self.merge_visualizer_str, "merge")
+        merge_visualizer = independent_ensemble_fit.merge_function_name_to_visualizer[merge_visualizer_str]
+        merge_visualizer.studies.study.gcm_rcm_couple = (merge_visualizer_str, "merge")
         return merge_visualizer
 
-    def interval_plot(self, ax, altitude_class):
+    def interval_plot(self, ax, altitude_class, merge_visualizer_str):
         linestyle = get_linestyle_for_altitude_class(altitude_class)
         increasing_key = 'increasing'
         decreasing_key = 'decreasing'
-        label_to_l = {
-            increasing_key: [],
-            decreasing_key: []
-        }
+
         label_to_color = {
             increasing_key: 'red',
             decreasing_key: 'blue'
         }
-        for v in self.left_limit_to_visualizer.values():
-            merge_visualizer = self.get_merge_visualizer(altitude_class, v)
+        label_to_l = {
+            increasing_key: [],
+            decreasing_key: []
+        }
+        for v in self.right_limit_to_visualizer.values():
+            merge_visualizer = self.get_merge_visualizer(altitude_class, v, merge_visualizer_str)
             _, *trends = merge_visualizer.all_trends(self.massif_names, with_significance=False,
                                                      with_relative_change=True)
             label_to_l[decreasing_key].append(trends[0])
@@ -126,5 +135,5 @@ class VisualizerForSensivity(object):
         for label, l in label_to_l.items():
             label_improved = 'with {} trends {}'.format(label, altitude_str)
             color = label_to_color[label]
-            ax.plot(self.left_limits, l, label=label_improved, color=color, linestyle=linestyle)
+            ax.plot(self.right_limits, l, label=label_improved, color=color, linestyle=linestyle)
 

projects/projected_extreme_snowfall/main_sensitivity.py

@@ -83,9 +83,8 @@ def main():
             massif_names=massif_names,
             temporal_covariate_for_fit=temporal_covariate_for_fit,
             remove_physically_implausible_models=remove_physically_implausible_models,
-            merge_visualizer_str=AbstractEnsembleFit.Median_merge,
             is_temperature_interval=False,
-            is_shift_interval=True,
+            is_shift_interval=False,
         )
         visualizer.plot()
 

spatio_temporal_dataset/coordinates/temporal_coordinates/temperature_covariate.py

@@ -44,6 +44,7 @@ class MeanAlpsTemperatureCovariate(AbstractTemperatureCovariate):
     def load_year_to_temperature_covariate(cls):
         return load_year_to_mean_alps_temperatures()
 
+
 class AnomalyTemperatureWithSplineTemporalCovariate(AbstractTemporalCovariateForFit):
     gcm_and_scenario_to_d = {}