[paper 1] add some remarks, or modify to main scripts

experiment/meteo_france_data/scm_models_data/cumulated_study.py

@@ -6,7 +6,7 @@ NB_DAYS = [1, 3, 5, 7]
 
 class CumulatedStudy(AbstractStudy):
     def __init__(self, variable_class: type, nb_consecutive_days: int = 3, *args, **kwargs):
-        assert nb_consecutive_days in NB_DAYS
+        assert nb_consecutive_days in NB_DAYS, nb_consecutive_days
         super().__init__(variable_class, *args, **kwargs)
         self.nb_consecutive_days = nb_consecutive_days
 

experiment/meteo_france_data/scm_models_data/safran/safran_variable.py

@@ -68,6 +68,7 @@ class SafranSnowfallVariable(AbstractVariable):
 
 
 class SafranRainfallVariable(SafranSnowfallVariable):
+    """Warning: this corresponds to water falling. Total precipitaiton equals Rainfall + Snowfall"""
     NAME = 'Rainfall'
 
     @classmethod

experiment/paper_past_snow_loads/check_mle_convergence_for_trends/qqplot/plot_qqplot.py

@@ -8,7 +8,7 @@ from matplotlib.ticker import PercentFormatter
 from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
 from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.main_study_visualizer import \
     ALL_ALTITUDES_WITHOUT_NAN
-from experiment.paper_past_snow_loads.data.main_example_swe_total_plot import marker_altitude_massif_name_for_paper1
+from experiment.paper_past_snow_loads.data.main_example_swe_total_plot import tuples_for_examples_paper1
 from experiment.paper_past_snow_loads.study_visualizer_for_non_stationary_trends import \
     StudyVisualizerForNonStationaryTrends
 
@@ -29,6 +29,7 @@ def plot_qqplot_for_time_series_with_missing_zeros(
 
 
 def plot_qqplot_for_time_series_examples(altitude_to_visualizer: Dict[int, StudyVisualizerForNonStationaryTrends]):
+    marker_altitude_massif_name_for_paper1 = tuples_for_examples_paper1()
     for color, a, m in marker_altitude_massif_name_for_paper1:
         v = altitude_to_visualizer[a]
         v.qqplot(m, color)
@@ -60,7 +61,8 @@ def plot_hist_psnow(altitude_to_visualizer: Dict[int, StudyVisualizerForNonStati
 
 if __name__ == '__main__':
     # altitudes = [300, 600, 900, 1200, 1500, 1800][:2]
-    altitudes = ALL_ALTITUDES_WITHOUT_NAN
+    # altitudes = ALL_ALTITUDES_WITHOUT_NAN
+    altitudes = [900, 1800, 2700]
     altitude_to_visualizer = {altitude: StudyVisualizerForNonStationaryTrends(CrocusSnowLoadTotal(altitude=altitude),
                                                                               multiprocessing=True)
                               for altitude in altitudes}

experiment/paper_past_snow_loads/check_mle_convergence_for_trends/shape/main_shape_repartition.py

@@ -19,9 +19,9 @@ def main_shape_repartition(altitudes, massif_names=None,
                                  if altitude in altitudes_for_plot_trend]
     max_abs_tdrl = max([visualizer.max_abs_change for visualizer in visualizers_for_altitudes])
     for visualizer in visualizers_for_altitudes:
-        # visualizer.plot_trends(max_abs_tdrl, add_colorbar=visualizer.study.altitude == 2700)
+        visualizer.plot_trends(max_abs_tdrl, add_colorbar=visualizer.study.altitude == 2700)
         # visualizer.plot_trends(max_abs_tdrl, add_colorbar=True)
-        visualizer.plot_trends()
+        # visualizer.plot_trends()
 
 
 if __name__ == '__main__':

experiment/paper_past_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py

@@ -99,7 +99,7 @@ def major_result():
 
 if __name__ == '__main__':
     major_result()
-    # intermediate_result(altitudes=[900, 1200], massif_names=['Vercors'],
+    # intermediate_result(altitudes=[900, 1200], massif_names=['Chartreuse'],
     #                     uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
     #                                          ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
     #                     multiprocessing=True)