diff --git a/extreme_trend/one_fold_fit/one_fold_fit.py b/extreme_trend/one_fold_fit/one_fold_fit.py
index f98f09e8e1d2765d31ff1f6200975e1a1dc1dceb..d9b6496881fc71ee6abf48ac84daae90fbc135c2 100644
--- a/extreme_trend/one_fold_fit/one_fold_fit.py
+++ b/extreme_trend/one_fold_fit/one_fold_fit.py
@@ -126,10 +126,7 @@ class OneFoldFit(object):
         return self.relative_changes_of_moment(altitudes=[self.altitude_plot], order=None)[0]
 
     def changes_of_moment(self, altitudes, order=1, covariate_before=None, covariate_after=None):
-        if covariate_before is None:
-            covariate_before = self.covariate_before
-        if covariate_after is None:
-            covariate_after = self.covariate_after
+        covariate_after, covariate_before = self.set_covariate_before_and_after(covariate_after, covariate_before)
         changes = []
         for altitude in altitudes:
             mean_after = self.get_moment(altitude, covariate_after, order)
@@ -138,6 +135,13 @@ class OneFoldFit(object):
             changes.append(change)
         return changes
 
+    def set_covariate_before_and_after(self, covariate_after, covariate_before):
+        if covariate_before is None:
+            covariate_before = self.covariate_before
+        if covariate_after is None:
+            covariate_after = self.covariate_after
+        return covariate_after, covariate_before
+
     @property
     def covariate_before(self):
         return self._covariate_before_and_after[0]
@@ -166,6 +170,7 @@ class OneFoldFit(object):
         return s
 
     def relative_changes_of_moment(self, altitudes, order=1, covariate_before=None, covariate_after=None):
+        covariate_after, covariate_before = self.set_covariate_before_and_after(covariate_after, covariate_before)
         relative_changes = []
         for altitude in altitudes:
             mean_after = self.get_moment(altitude, covariate_after, order)
diff --git a/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py b/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py
index d04f3860cd934df83c6f760c0add0398a26aa474..bf260bc55a1023bb0932a6686ec985af8f2ba6c4 100644
--- a/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py
+++ b/projects/past_extreme_snowfall/section_data_and_results/main_altitudes_studies.py
@@ -41,18 +41,17 @@ def main():
     study_classes = [SafranSnowfall1Day
                      , SafranSnowfall3Days,
                      SafranSnowfall5Days, SafranSnowfall7Days][:1]
-    study_classes = [SafranSnowfall2020, SafranSnowfall2019, SafranSnowfallCenterOnDay1day,
-                     SafranSnowfallNotCenterOnDay1day,
-                     SafranSnowfallCenterOnDay1dayMeanRate, SafranSnowfall1Day][:1]
+    # study_classes = [SafranSnowfall2020, SafranSnowfall2019, SafranSnowfallCenterOnDay1day,
+    #                  SafranSnowfallNotCenterOnDay1day,
+    #                  SafranSnowfallCenterOnDay1dayMeanRate, SafranSnowfall1Day][:1]
     # study_classes = [SafranSnowfallNotCenterOnDay1day, SafranSnowfall2019]
     seasons = [Season.annual, Season.winter, Season.spring, Season.automn][:1]
 
     set_seed_for_test()
-    model_must_pass_the_test = True
+    model_must_pass_the_test = False
     AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
-    year_max = 2005
 
-    fast = False
+    fast = None
     if fast is None:
         massif_names = None
         AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
@@ -66,20 +65,20 @@ def main():
         altitudes_list = altitudes_for_groups[:]
 
     start = time.time()
-    main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_pass_the_test, year_max=year_max)
+    main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_pass_the_test)
     end = time.time()
     duration = str(datetime.timedelta(seconds=end - start))
     print('Total duration', duration)
 
 
-def main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_pass_the_test, year_max=None):
+def main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_pass_the_test):
     assert isinstance(altitudes_list, List)
     assert isinstance(altitudes_list[0], List)
     for season in seasons:
         for study_class in study_classes:
             print('Inner loop', season, study_class)
             visualizer_list = load_visualizer_list(season, study_class, altitudes_list, massif_names,
-                                                   model_must_pass_the_test, year_max=year_max)
+                                                   model_must_pass_the_test)
             plot_visualizers(massif_names, visualizer_list)
             for visualizer in visualizer_list:
                 plot_visualizer(massif_names, visualizer)
@@ -88,11 +87,12 @@ def main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_p
 
 
 def plot_visualizers(massif_names, visualizer_list):
+    with_significance = False
     # plot_histogram_all_models_against_altitudes(massif_names, visualizer_list)
-    plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list, with_significance=False)
+    plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list, with_significance=with_significance)
     # plot_shoe_plot_ratio_interval_size_against_altitude(massif_names, visualizer_list)
     for relative in [True, False]:
-        plot_shoe_plot_changes_against_altitude(massif_names, visualizer_list, relative=relative, with_significance=False)
+        plot_shoe_plot_changes_against_altitude(massif_names, visualizer_list, relative=relative, with_significance=with_significance)
     # plot_coherence_curves(['Vanoise'], visualizer_list)
     pass