[POSTER EVAN] tight layout for the first part of the poster

experiment/meteo_france_data/scm_models_data/abstract_study.py

@@ -267,6 +267,7 @@ class AbstractStudy(object):
                         show_label=True,
                         scaled=False,
                         fontsize=7,
+                        axis_off=False,
                         ):
         if ax is None:
             ax = plt.gca()
@@ -302,15 +303,6 @@ class AbstractStudy(object):
                 else:
                     ax.fill(*coords_list, **{'color': default_color_for_missing_massif})
 
-                # else:
-                #     fill_kwargs = {}
-
-                # x , y = list(self.massifs_coordinates.df_all_coordinates.loc[massif_name])
-                # x , y= coords_list[0][0], coords_list[0][1]
-                # print(x, y)
-                # print(massif_name)
-                # ax.scatter(x, y)
-                # ax.text(x, y, massif_name)
         # Display the center of the massif
         masssif_coordinate_for_display = cls.massifs_coordinates_for_display(massif_names)
 
@@ -338,6 +330,8 @@ class AbstractStudy(object):
 
         if scaled:
             plt.axis('scaled')
+        if axis_off:
+            plt.axis('off')
 
         if show:
             plt.show()

experiment/meteo_france_data/scm_models_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py

@@ -283,7 +283,9 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
         return title
 
     def visualize_trend_test_repartition_poster(self, reduction_function, axes=None, subtitle='', isin_parameters=None,
-                                                plot_title=None):
+                                                plot_title=None,
+                                                poster_plot=False,
+                                                write_text_on_massif=True):
         trend_type_to_serie = {k: v[0].replace(0.0, np.nan) for k, v in
                                self.trend_type_to_series(reduction_function, isin_parameters).items()}
 
@@ -313,7 +315,7 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
                         massif_to_strength.update(massif_to_value_for_trend_type[0])
                         massif_to_constant.update(massif_to_value_for_trend_type[1])
                     else:
-                        massif_to_value_for_trend_type = {k: int(v) for k, v in
+                        massif_to_value_for_trend_type = {k: "$t_0=$" + str(int(v)) for k, v in
                                                           self.trend_type_to_series(reduction_function,
                                                                                     isin_parameters)[
                                                               display_trend_type][1].items()
@@ -330,11 +332,12 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
         else:
             massif_name_to_value = massif_to_year
         self.study.visualize_study(None, massif_name_to_color=massif_to_color, show=False,
-                                   show_label=False, scaled=True, add_text=add_text,
+                                   show_label=False, scaled=True, add_text=write_text_on_massif,
                                    massif_name_to_value=massif_name_to_value,
-                                   fontsize=4)
+                                   fontsize=4,
+                                   axis_off=True)
 
-        title = self.set_trend_test_reparition_title(subtitle, set=True)
+        title = self.set_trend_test_reparition_title(subtitle, set=not poster_plot)
 
 
         return title
@@ -459,15 +462,19 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
 
     def visualize_massif_trend_test_one_altitude(self, axes=None, add_detailed_plots=False, plot_title=None,
                                                  isin_parameters=None,
-                                                 show_or_save_to_file=True):
+                                                 show_or_save_to_file=True,
+                                                 poster_plot=False,
+                                                write_text_on_massif=True):
         last_title = ''
         for subtitle, reduction_function in self.subtitle_to_reduction_function(self.index_reduction,
                                                                                 level=self.massif_index_level,
                                                                                 add_detailed_plot=add_detailed_plots).items():
             last_title = self.visualize_trend_test_repartition_poster(reduction_function, axes, subtitle=subtitle,
                                                                       isin_parameters=isin_parameters,
-                                                                      plot_title=plot_title)
+                                                                      plot_title=plot_title,
+                                                                      poster_plot=poster_plot,
+                                                                      write_text_on_massif=write_text_on_massif)
         if show_or_save_to_file:
-            self.show_or_save_to_file(specific_title=last_title, dpi=1000)
+            self.show_or_save_to_file(specific_title=last_title, dpi=1000, tight=poster_plot)
 
         return last_title

experiment/paper1_steps/poster_EVAN2019/main_poster_EVAN2019.py

+from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_year_hypercube_visualizer import \
+    Altitude_Hypercube_Year_Visualizer
+from experiment.trend_analysis.univariate_test.gev_trend_test_one_parameter import GevScaleTrendTest, \
+    GevLocationTrendTest
+from experiment.trend_analysis.univariate_test.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
+from experiment.paper1_steps.utils import get_full_altitude_visualizer
+
+POSTER_ALTITUDES = [900, 1800, 2700]
+
+
+def main_poster_A_non_stationary_model_choice():
+    nb = 1
+    for altitude in POSTER_ALTITUDES[:nb]:
+        for trend_test_class in [GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest][-nb:]:
+            vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
+                                                      exact_starting_year=1958, reduce_strength_array=False,
+                                                      trend_test_class=trend_test_class,
+                                                      )
+            # vizualiser.save_to_file = False
+            vizualiser.visualize_massif_trend_test_one_altitude(poster_plot=True, write_text_on_massif=False)
+
+
+def main_poster_B_starting_years_analysis():
+    pass
+
+
+if __name__ == '__main__':
+    main_poster_A_non_stationary_model_choice()

experiment/trend_analysis/univariate_test/gev_trend_test_one_parameter.py

@@ -26,8 +26,8 @@ class GevLocationTrendTest(GevTrendTestOneParameter):
                          NonStationaryLocationStationModel, GevParams.LOC)
 
     def _slope_strength(self):
-        return self.non_stationary_constant_gev_params.quantile_strength_evolution_ratio(p=self.quantile_for_strength,
-                                                                                         mu1=self.non_stationary_linear_coef)
+        return self.non_stationary_constant_gev_params.quantile_strength_evolution(p=self.quantile_for_strength,
+                                                                                   mu1=self.non_stationary_linear_coef)
 
 
 class GevScaleTrendTest(GevTrendTestOneParameter):
@@ -37,7 +37,7 @@ class GevScaleTrendTest(GevTrendTestOneParameter):
                          NonStationaryScaleStationModel, GevParams.SCALE)
 
     def _slope_strength(self):
-        return self.non_stationary_constant_gev_params.quantile_strength_evolution_ratio(
+        return self.non_stationary_constant_gev_params.quantile_strength_evolution(
             p=self.quantile_for_strength,
             sigma1=self.non_stationary_linear_coef)
 

experiment/trend_analysis/univariate_test/gev_trend_test_two_parameters.py

@@ -20,6 +20,6 @@ class GevLocationAndScaleTrendTest(GevTrendTestTwoParameters):
     def _slope_strength(self):
         mu1 = self.get_non_stationary_linear_coef(gev_param_name=GevParams.LOC)
         sigma1 = self.get_non_stationary_linear_coef(gev_param_name=GevParams.SCALE)
-        return self.non_stationary_constant_gev_params.quantile_strength_evolution_ratio(p=self.quantile_for_strength,
-                                                                                         mu1=mu1,
-                                                                                         sigma1=sigma1)
+        return self.non_stationary_constant_gev_params.quantile_strength_evolution(p=self.quantile_for_strength,
+                                                                                   mu1=mu1,
+                                                                                   sigma1=sigma1)

extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py

@@ -166,7 +166,8 @@ class AbstractMarginFunction(object):
             ax = plt.gca()
 
         # Special display
-        imshow_shifted(ax, gev_param_name, self.grid_2D(temporal_step)[gev_param_name], self.visualization_extend, self.mask_2D)
+        imshow_shifted(ax, gev_param_name, self.grid_2D(temporal_step)[gev_param_name], self.visualization_extend,
+                       self.mask_2D)
 
         # X axis
         ax.set_xlabel('coordinate X')
@@ -215,7 +216,7 @@ class AbstractMarginFunction(object):
                 grid.append(self.get_gev_params(np.array(coordinate)).summary_dict)
         grid = {value_name: np.array([g[value_name] for g in grid]).reshape(
             [self.VISUALIZATION_RESOLUTION, self.VISUALIZATION_RESOLUTION])
-                for value_name in GevParams.SUMMARY_NAMES}
+            for value_name in GevParams.SUMMARY_NAMES}
         return grid
 
     # Visualization 3D

extreme_estimator/margin_fits/gev/gev_params.py

@@ -45,22 +45,21 @@ class GevParams(ExtremeParams):
     def __str__(self):
         return self.to_dict().__str__()
 
-    def quantile_strength_evolution_ratio(self, p=0.99, mu1=0.0, sigma1=0.0):
+    def quantile_strength_evolution(self, p=0.99, mu1=0.0, sigma1=0.0):
         """
-        Compute the relative evolution of some quantile with respect to time.
+        Compute the variation of some quantile with respect to time.
         (when mu1 and sigma1 can be modified with time)
 
         :param p: level of the quantile
         :param mu1: temporal slope of the location parameter
         :param sigma1: temporal slope of the scale parameter
-        :return: A string summarizing the evolution ratio
+        :return: A float that equals evolution ratio
         """
-        initial_quantile = self.quantile(p)
-        quantity_increased = mu1
+        quantile_annual_variation = mu1
         if sigma1 != 0:
             power = np.float_power(- np.log(p), -self.shape)
-            quantity_increased -= (sigma1 / self.shape) * (1 - power)
-        return quantity_increased / initial_quantile
+            quantile_annual_variation -= (sigma1 / self.shape) * (1 - power)
+        return quantile_annual_variation
 
     # Compute some indicators (such as the mean and the variance)