[paper 1] fix exceedance curve

experiment/eurocode_data/eurocode_region.py

@@ -47,6 +47,11 @@ class AbstractEurocodeRegion(object):
     def plot_eurocode_snow_load_on_ground_characteristic_value_variable_action(self, ax, altitudes,
                                                                                label='French standards',
                                                                                linestyle=None):
+        # The breaking point must be exactly at 500 and 1000
+        for threshold in [500, 1000]:
+            if min(altitudes) < threshold < max(altitudes):
+                assert threshold in altitudes
+        # Plot the curve
         ax.plot(altitudes, [self.valeur_caracteristique(altitude) for altitude in altitudes],
                 label=label, color=self.eurocode_color, linewidth=5, linestyle=linestyle)
 

papers/exceeding_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py

@@ -66,12 +66,12 @@ def intermediate_result(altitudes, massif_names=None,
             _ = compute_minimized_aic(visualizer)
 
     # Plots
-    plot_trend_map(altitude_to_visualizer)
+    # plot_trend_map(altitude_to_visualizer)
     # plot_diagnosis_risk(altitude_to_visualizer)
-    plot_trend_curves(altitude_to_visualizer={a: v for a, v in altitude_to_visualizer.items() if a >= 900})
+    # plot_trend_curves(altitude_to_visualizer={a: v for a, v in altitude_to_visualizer.items() if a >= 900})
     plot_uncertainty_massifs(altitude_to_visualizer)
-    plot_uncertainty_histogram(altitude_to_visualizer)
-    plot_selection_curves(altitude_to_visualizer)
+    # plot_uncertainty_histogram(altitude_to_visualizer)
+    # plot_selection_curves(altitude_to_visualizer)
 
 
 def major_result():
@@ -91,11 +91,11 @@ def major_result():
 
 
 if __name__ == '__main__':
-    major_result()
-    # intermediate_result(altitudes=[1500, 1800][:1], massif_names=None,
-    #                     uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
-    #                                          ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
-    #                     multiprocessing=True)
+    # major_result()
+    intermediate_result(altitudes=paper_altitudes, massif_names=['Beaufortain', 'Vercors'],
+                        uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
+                                             ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
+                        multiprocessing=True)
     # intermediate_result(altitudes=[900, 1200], massif_names=['Maurienne'],
     #                     uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
     #                                          ConfidenceIntervalMethodFromExtremes.ci_mle][1:],

papers/exceeding_snow_loads/result_trends_and_return_levels/plot_uncertainty_curves.py

@@ -99,8 +99,9 @@ def plot_single_uncertainty_massif_and_non_stationary_context(ax, massif_name, m
     for j, uncertainty_method in enumerate(visualizer.uncertainty_methods):
         if j == 0:
             # Plot eurocode norm
+            altitudes_for_plot = list(range(min(altitudes), max(altitudes)+1, 100))
             eurocode_region.plot_eurocode_snow_load_on_ground_characteristic_value_variable_action(ax,
-                                                                                                   altitudes=altitudes)
+                                                                                                   altitudes=altitudes_for_plot)
 
         # Plot uncertainties
         color = ci_method_to_color[uncertainty_method]
@@ -162,8 +163,9 @@ def plot_tdrl_bars(altitude_to_visualizer, ax, massif_name, valid_altitudes, leg
                    width=150, color=colors, label=visualizers[0].label_tdrl_bar, edgecolor='black', hatch='//')
         # Plot markers
         markers_kwargs = [v.massif_name_to_marker_style[massif_name] for v in visualizers]
+        markersize = 20
         for k in markers_kwargs:
-            k['markersize'] = 10
+            k['markersize'] = markersize
         for altitude, marker_kwargs, value in zip(valid_altitudes, markers_kwargs, tdrl_values):
             # ax.plot([altitude], [value / 2], **marker_kwargs)
             # Better to plot all the markers on the same line
@@ -172,13 +174,16 @@ def plot_tdrl_bars(altitude_to_visualizer, ax, massif_name, valid_altitudes, leg
         visualizer = visualizers[0]
         markers = [v.massif_name_to_marker_style[massif_name]['marker'] for v in visualizers]
         marker_to_label = {m: visualizer.all_marker_style_to_label_name[m] for m in markers}
-        legend_elements = AbstractStudy.get_legend_for_model_symbol(marker_to_label, markersize=9)
+        legend_elements = AbstractStudy.get_legend_for_model_symbol(marker_to_label, markersize=markersize)
         ax2 = ax.twinx()
         # ax2.legend(handles=legend_elements, bbox_to_anchor=(0.93, 0.7), loc='upper right')
         # ax2.annotate("Filled symbol = significant trend ", xy=(0.85, 0.5), xycoords='axes fraction', fontsize=7)
         ax2.legend(handles=legend_elements, loc='center left', prop={'size': legend_size})
+        # for handle in lgnd.legendHandles:
+        #     handle.set_sizes([6.0])
         # ax2.annotate("Filled symbol =\nsignificant trend  \nw.r.t $\mathcal{M}_0$", xy=(0.6, 0.85), xycoords='axes fraction', fontsize=fontsize)
         ax2.annotate('\n'.join(filled_marker_legend_list), xy=(0.23, 0.43), xycoords='axes fraction', fontsize=fontsize)
+        ax2.annotate('Markers show selected model $\mathcal{M}_N$', xy=(0.02, 0.605), xycoords='axes fraction', fontsize=fontsize)
         ax2.set_yticks([])