[refactor] refactor some folder name. add test_results.py

extreme_trend/visualizers/study_visualizer_for_non_stationary_trends.py

@@ -82,6 +82,8 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
                                         ConfidenceIntervalMethodFromExtremes.ci_mle][1:]
         if self.uncertainty_massif_names is None:
             self.uncertainty_massif_names = self.study.study_massif_names
+        else:
+            assert set(self.uncertainty_massif_names).issubset(set(self.study.study_massif_names))
         if self.non_stationary_trend_test_to_marker is None:
             # Assign default argument for the non stationary trends
             self.non_stationary_trend_test = NON_STATIONARY_TREND_TEST_PAPER
@@ -95,7 +97,7 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
     @cached_property
     def massif_name_to_years_and_maxima(self):
         d = {}
-        df_maxima = self.study.observations_annual_maxima.df_maxima_gev
+        df_maxima = self.study.observations_annual_maxima.df_maxima_gev.loc[self.uncertainty_massif_names]
         years = np.array(df_maxima.columns)
         for massif_name, s_maxima in df_maxima.iterrows():
             d[massif_name] = (years, np.array(s_maxima))
@@ -135,6 +137,7 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
         # In both cases, we remove any massif with psnow < 0.9
         if self.fit_only_time_series_with_ninety_percent_of_non_null_values:
             d = {m: v for m, v in d.items() if self.massif_name_to_psnow[m] >= 0.9}
+        print(d.keys())
         return d
 
     @property

projects/contrasting_snow_loads/main_result.py → projects/contrasting_trends_in_snow_loads/main_result.py

@@ -18,7 +18,7 @@ from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusS
     CrocusSnowLoad5Days, CrocusSnowLoad7Days, CrocusSnowLoad1Day
 from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import \
     ConfidenceIntervalMethodFromExtremes
-from projects.contrasting_snow_loads.plot_contrasting_trend_curves import plot_contrasting_trend_curves
+from projects.contrasting_trends_in_snow_loads.plot_contrasting_trend_curves import plot_contrasting_trend_curves
 from projects.exceeding_snow_loads.section_results.main_result_trends_and_return_levels import \
     compute_minimized_aic
 from root_utils import NB_CORES

projects/exceeding_snow_loads/section_results/main_result_trends_and_return_levels.py

 from multiprocessing.pool import Pool
 
 import matplotlib as mpl
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
 
 from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
-from extreme_trend.visualizers.utils import load_altitude_to_visualizer
-from projects.exceeding_snow_loads.utils import paper_study_classes, paper_altitudes
-from projects.exceeding_snow_loads.section_results.plot_uncertainty_curves import plot_uncertainty_massifs
-from extreme_trend.visualizers.study_visualizer_for_non_stationary_trends import \
-    StudyVisualizerForNonStationaryTrends
 from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import \
     ConfidenceIntervalMethodFromExtremes
+from extreme_trend.visualizers.study_visualizer_for_non_stationary_trends import \
+    StudyVisualizerForNonStationaryTrends
+from extreme_trend.visualizers.utils import load_altitude_to_visualizer
+from projects.exceeding_snow_loads.section_results.plot_uncertainty_curves import plot_uncertainty_massifs
+from projects.exceeding_snow_loads.utils import paper_study_classes, paper_altitudes
 from root_utils import NB_CORES
 
-mpl.rcParams['text.usetex'] = True
-mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
+
 import matplotlib.pyplot as plt
 
 

projects/exceeding_snow_loads/section_results/plot_uncertainty_curves.py

 from typing import Dict
+
+import matplotlib as mpl
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
+
 import matplotlib.pyplot as plt
 
 import numpy as np

projects/exceeding_snow_loads/utils.py

@@ -24,3 +24,5 @@ NON_STATIONARY_TREND_TEST_PAPER = [GumbelVersusGumbel,
                                    GevLocationAgainstGumbel, GevScaleAgainstGumbel,
                                    GevLocationAndScaleTrendTestAgainstGumbel]
 
+
+

test/test_projects/test_exceeding_snow_loads/test_results.py

+import unittest
+
+from extreme_data.meteo_france_data.scm_models_data.crocus.crocus import CrocusSnowLoadTotal
+from extreme_fit.model.result_from_model_fit.result_from_extremes.confidence_interval_method import \
+    ConfidenceIntervalMethodFromExtremes
+from extreme_trend.visualizers.utils import load_altitude_to_visualizer
+from projects.exceeding_snow_loads.section_results.plot_selection_curves import plot_selection_curves
+from projects.exceeding_snow_loads.section_results.plot_trend_curves import plot_trend_curves, plot_trend_map
+from projects.exceeding_snow_loads.section_results.plot_uncertainty_curves import plot_uncertainty_massifs
+from projects.exceeding_snow_loads.section_results.plot_uncertainty_histogram import plot_uncertainty_histogram
+
+
+class TestResults(unittest.TestCase):
+
+    def test_run_intermediate_results(self):
+        # Load data
+        altitude_to_visualizer = load_altitude_to_visualizer(altitudes=[300, 600], massif_names=['Chartreuse'],
+                                                             study_class=CrocusSnowLoadTotal,
+                                                             model_subsets_for_uncertainty=None,
+                                                             uncertainty_methods=[
+                                                                 ConfidenceIntervalMethodFromExtremes.ci_mle])
+        plot_trend_map(altitude_to_visualizer)
+        plot_trend_curves(altitude_to_visualizer)
+        plot_uncertainty_massifs(altitude_to_visualizer)
+        plot_uncertainty_histogram(altitude_to_visualizer)
+        plot_selection_curves(altitude_to_visualizer)
+        self.assertTrue(True)
+
+
+if __name__ == '__main__':
+    unittest.main()