[HYPERCUBE] fix starting_year minor display issues.

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

@@ -30,6 +30,12 @@ class AbstractHypercubeVisualizer(object):
         self.trend_test_class = trend_test_class
         self.tuple_to_study_visualizer = tuple_to_study_visualizer  # type: Dict[Tuple, StudyVisualizer]
 
+        if isinstance(nb_data_reduced_for_speed, bool):
+            self.nb_data_for_fast_mode = 7 if nb_data_reduced_for_speed else None
+        else:
+            assert isinstance(nb_data_reduced_for_speed, int)
+            self.nb_data_for_fast_mode = nb_data_reduced_for_speed
+
         if exact_starting_year is not None:
             assert first_starting_year is None
             assert last_starting_year is None
@@ -38,15 +44,17 @@ class AbstractHypercubeVisualizer(object):
             default_first_starting_year, *_, default_last_starting_year = self.all_potential_starting_years
             self.first_starting_year = first_starting_year if first_starting_year is not None else default_first_starting_year
             self.last_starting_year = last_starting_year if last_starting_year is not None else default_last_starting_year
-        if isinstance(nb_data_reduced_for_speed, bool):
-            self.nb_data_for_fast_mode = 7 if nb_data_reduced_for_speed else None
-        else:
-            assert isinstance(nb_data_reduced_for_speed, int)
-            self.nb_data_for_fast_mode = nb_data_reduced_for_speed
+        # Load starting year
+        self.starting_years = [year for year in self.all_potential_starting_years
+                               if self.first_starting_year <= year <= self.last_starting_year]
+        if self.nb_data_for_fast_mode is not None:
+            self.starting_years = self.starting_years[:self.nb_data_for_fast_mode]
+            self.last_starting_year = self.starting_years[-1]
 
         if self.verbose:
             print('Hypercube with parameters:')
-            print('First starting year: {}, Last starting year: {}'.format(self.first_starting_year, self.last_starting_year))
+            print('First starting year: {}, Last starting year: {}'.format(self.first_starting_year,
+                                                                           self.last_starting_year))
             print('Starting years:', self.starting_years)
             print('Trend test class:', get_display_name_from_object_type(self.trend_test_class))
 
@@ -60,14 +68,6 @@ class AbstractHypercubeVisualizer(object):
     def all_potential_starting_years(self):
         return self.study_visualizer.starting_years
 
-    @cached_property
-    def starting_years(self):
-        starting_years = [year for year in self.all_potential_starting_years
-                          if self.first_starting_year <= year <= self.last_starting_year]
-        if self.nb_data_for_fast_mode is not None:
-            starting_years = starting_years[:self.nb_data_for_fast_mode]
-        return starting_years
-
     def tuple_values(self, idx):
         return sorted(set([t[idx] if isinstance(t, tuple) else t for t in self.tuple_to_study_visualizer.keys()]))
 
@@ -81,11 +81,11 @@ class AbstractHypercubeVisualizer(object):
         df_spatio_temporal_trend_strength = [e[idx] for e in self.df_trends_spatio_temporal]
         return pd.concat(df_spatio_temporal_trend_strength, keys=list(self.tuple_to_study_visualizer.keys()), axis=0)
 
-
     @cached_property
     def df_hypercube_trend_type(self) -> pd.DataFrame:
         return self._df_hypercube_trend_meta(idx=0
                                              )
+
     @cached_property
     def df_hypercube_trend_strength(self) -> pd.DataFrame:
         return self._df_hypercube_trend_meta(idx=1)

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

@@ -143,7 +143,7 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
             if plot_title is not None:
                 argmax_idx = np.argmax(values)
                 best_year = xlabel_values[argmax_idx]
-                plot_title += '{} {}'.format(subtitle, best_year)
+                plot_title += ' (max reached in {})'.format(best_year)
 
             if subtitle in SCM_STUDY_NAME_TO_COLOR:
                 ax, color, ylabel = ax.twinx(), SCM_STUDY_NAME_TO_COLOR[subtitle], subtitle

experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py

@@ -15,8 +15,11 @@ from collections import OrderedDict
 from experiment.trend_analysis.univariate_test.abstract_gev_change_point_test import GevLocationChangePointTest
 from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.uniform_normalization import \
     BetweenZeroAndOneNormalization, BetweenMinusOneAndOneNormalization
+from utils import get_display_name_from_object_type
 
 SCM_STUDIES = [SafranSnowfall, CrocusSwe, CrocusDepth]
+SCM_STUDY_NAME_TO_COLOR = {get_display_name_from_object_type(s): color
+                           for s, color in zip(SCM_STUDIES, ['r', 'b', 'g'])}
 SCM_EXTENDED_STUDIES = [ExtendedSafranSnowfall, ExtendedCrocusSwe, ExtendedCrocusDepth]
 SCM_STUDY_TO_EXTENDED_STUDY = OrderedDict(zip(SCM_STUDIES, SCM_EXTENDED_STUDIES))