[SCM] add crocus study considering the number of days with snow on the ground

experiment/meteo_france_SCM_study/abstract_study.py

@@ -134,6 +134,7 @@ class AbstractStudy(object):
     def load_df_centroid(self) -> pd.DataFrame:
         df_centroid = pd.read_csv(op.join(self.map_full_path, 'coordonnees_massifs_alpes.csv'))
         df_centroid.set_index('NOM', inplace=True)
+        # Sort the column in the order of the SAFRAN dataset
         df_centroid = df_centroid.loc[self.original_safran_massif_names]
         return df_centroid
 

experiment/meteo_france_SCM_study/crocus/crocus.py

@@ -23,7 +23,7 @@ class Crocus(AbstractStudy):
     def annual_aggregation_function(self, *args, **kwargs):
         return np.mean(*args, **kwargs)
 
-    def apply_annual_aggregation(self, time_serie):
+    def winter_annual_aggregation(self, time_serie):
         # In the Durand paper, we only want the data from November to April
         # 91 = 30 + 31 + 30 first days of the time serie correspond to the month of August + September + October
         # 92 = 31 + 30 + 31 last days correspond to the month of May + June + JUly
@@ -35,6 +35,9 @@ class CrocusSwe(Crocus):
     def __init__(self, *args, **kwargs):
         super().__init__(CrocusSweVariable, *args, **kwargs)
 
+    def apply_annual_aggregation(self, time_serie):
+        return self.winter_annual_aggregation(time_serie)
+
 
 class ExtendedCrocusSwe(AbstractExtendedStudy, CrocusSwe):
     pass
@@ -45,11 +48,24 @@ class CrocusDepth(Crocus):
     def __init__(self, *args, **kwargs):
         super().__init__(CrocusDepthVariable, *args, **kwargs)
 
+    def apply_annual_aggregation(self, time_serie):
+        return self.winter_annual_aggregation(time_serie)
+
 
 class ExtendedCrocusDepth(AbstractExtendedStudy, CrocusDepth):
     pass
 
 
+class CrocusDaysWithSnowOnGround(Crocus):
+    """Having snow on the ground is equivalent to snow depth > 0"""
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(CrocusDepthVariable, *args, **kwargs)
+
+    def annual_aggregation_function(self, *args, **kwargs):
+        return np.count_nonzero(*args, **kwargs)
+
+
 if __name__ == '__main__':
     for variable_clas in [CrocusSweVariable, CrocusDepthVariable]:
         study = Crocus(variable_class=variable_clas, altitude=2400)

experiment/meteo_france_SCM_study/crocus/crocus_variables.py

@@ -41,3 +41,4 @@ class CrocusDepthVariable(CrocusVariable):
     def __init__(self, dataset, altitude):
         # Units are m
         super().__init__(dataset, altitude, "SNOWDEPTH")
+

experiment/meteo_france_SCM_study/safran/safran.py

@@ -19,6 +19,7 @@ class Safran(AbstractStudy):
 class SafranFrequency(Safran):
 
     def __init__(self, variable_class: type, nb_consecutive_days=1, *args, **kwargs):
+        assert nb_consecutive_days <= 7
         super().__init__(variable_class, *args, **kwargs)
         self.nb_consecutive_days = nb_consecutive_days
 

experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py

 from experiment.meteo_france_SCM_study.abstract_study import AbstractStudy
 from experiment.meteo_france_SCM_study.crocus.crocus import CrocusDepth, CrocusSwe, ExtendedCrocusDepth, \
-    ExtendedCrocusSwe
+    ExtendedCrocusSwe, CrocusDaysWithSnowOnGround
 from experiment.meteo_france_SCM_study.safran.safran import SafranSnowfall, ExtendedSafranSnowfall, SafranRainfall, \
     SafranTemperature, SafranTotalPrecip
 
@@ -22,7 +22,7 @@ def study_iterator(study_class, only_first_one=False, both_altitude=False, verbo
         for alti in AbstractStudy.ALTITUDES[::1]:
             if verbose:
                 print('alti: {}, nb_day: {}'.format(alti, nb_day))
-            study = study_class(altitude=alti, nb_consecutive_days=nb_day) if is_safran_study else study_class(alti)
+            study = study_class(altitude=alti, nb_consecutive_days=nb_day) if is_safran_study else study_class(altitude=alti)
             yield study
             if only_first_one and not both_altitude:
                 break
@@ -50,12 +50,12 @@ def extended_visualization():
 
 def annual_mean_vizu_compare_durand_study(safran=True, take_mean_value=True):
     if safran:
-        for study_class in [SafranTotalPrecip, SafranRainfall, SafranSnowfall, SafranTemperature][:1]:
+        for study_class in [SafranTotalPrecip, SafranRainfall, SafranSnowfall, SafranTemperature][2:3]:
             study = study_class(altitude=1800, year_min=1958, year_max=2002)
             study_visualizer = StudyVisualizer(study)
             study_visualizer.visualize_annual_mean_values(take_mean_value=True)
     else:
-        for study_class in [CrocusSwe, CrocusDepth][1:]:
+        for study_class in [CrocusSwe, CrocusDepth, CrocusDaysWithSnowOnGround][-1:]:
             study = study_class(altitude=1800, year_min=1958, year_max=2005)
             study_visualizer = StudyVisualizer(study)
             study_visualizer.visualize_annual_mean_values(take_mean_value=take_mean_value)
@@ -65,7 +65,7 @@ def normal_visualization():
     save_to_file = False
     only_first_one = True
     # for study_class in SCM_STUDIES[:1]:
-    for study_class in [SafranRainfall, SafranSnowfall, SafranTemperature][:1]:
+    for study_class in [SafranSnowfall, SafranRainfall, SafranTemperature][:1]:
         for study in study_iterator(study_class, only_first_one=only_first_one):
             study_visualizer = StudyVisualizer(study, save_to_file=save_to_file)
             # study_visualizer.visualize_independent_margin_fits(threshold=[None, 20, 40, 60][0])
@@ -89,7 +89,7 @@ def complete_analysis(only_first_one=False):
 
 
 if __name__ == '__main__':
-    annual_mean_vizu_compare_durand_study(safran=False, take_mean_value=True)
-    # normal_visualization()
+    # annual_mean_vizu_compare_durand_study(safran=True, take_mean_value=True)
+    normal_visualization()
     # extended_visualization()
     # complete_analysis()

experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py

@@ -226,8 +226,6 @@ class StudyVisualizer(object):
             margin_model = margin_class(coordinates=self.coordinates)
             estimator = FullEstimatorInASingleStepWithSmoothMargin(self.dataset, margin_model, max_stable_model)
             title = get_display_name_from_object_type(type(max_stable_model))
-            # if isinstance(max_stable_model, AbstractMaxStableModelWithCovarianceFunction):
-            #     title += ' ' + str(default_covariance_function).split('.')[-1]
             self.fit_and_visualize_estimator(estimator, axes[i], title=title)
         # Add the label
         self.show_or_save_to_file()