[refactor] fix issue. the temporal covariate is the the anomaly of temperature...

[refactor] fix issue. the temporal covariate is the the anomaly of temperature smoothed with a spline

extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py

@@ -26,7 +26,7 @@ def get_scenario_name(scenario):
         return str(scenario).split('.')[-1]
 
 
-def year_to_global_mean_temp(gcm, scenario, year_min=None, year_max=None, spline=False, anomaly=False):
+def year_to_global_mean_temp(gcm, scenario, year_min=None, year_max=None, spline=True, anomaly=True):
     d = OrderedDict()
     years, global_mean_temps = years_and_global_mean_temps(gcm, scenario, year_min, year_max, spline=spline,
                                                            anomaly=anomaly)
@@ -43,7 +43,7 @@ def get_column_name(anomaly, spline):
         return basic_column_name
 
 
-def years_and_global_mean_temps(gcm, scenario, year_min=None, year_max=None, anomaly=False, spline=True):
+def years_and_global_mean_temps(gcm, scenario, year_min=None, year_max=None, anomaly=True, spline=True):
     # Compute everything
     ensemble_member = 'r{}i1p1'.format(gcm_to_rnumber[gcm])
     scenario_name = get_scenario_name(scenario)
@@ -75,7 +75,7 @@ def years_and_global_mean_temps(gcm, scenario, year_min=None, year_max=None, ano
     return years, global_mean_temp
 
 
-def dat_to_csv(csv_filepath, txt_filepath, spline):
+def dat_to_csv(csv_filepath, txt_filepath):
     d = OrderedDict()
     with open(txt_filepath, 'r') as f:
         for i, l in enumerate(f):

extreme_data/meteo_france_data/adamont_data/cmip5/plot_temperatures.py

@@ -13,7 +13,7 @@ from extreme_data.meteo_france_data.scm_models_data.visualization.study_visualiz
 from root_utils import VERSION_TIME
 
 
-def main_plot_temperature_all(anomaly=False, spline=False):
+def main_plot_temperature_all(anomaly=True, spline=True):
     ax = plt.gca()
     for gcm in get_gcm_list(adamont_version=2)[:]:
         for scenario in rcp_scenarios[:]:
@@ -23,7 +23,7 @@ def main_plot_temperature_all(anomaly=False, spline=False):
     end_plot(anomaly, ax, spline)
 
 
-def main_plot_temperature_with_spline_on_top(anomaly=False):
+def main_plot_temperature_with_spline_on_top(anomaly=True):
     spline = None
     for gcm in get_gcm_list(adamont_version=2)[:]:
         ax = plt.gca()
@@ -67,7 +67,7 @@ def end_plot(anomaly, ax, spline, title=None):
 
 
 def plot_temperature_for_rcp_gcm(ax, gcm, scenario, year_min, year_max, linestyle=None,
-                                 label=None, spline: Union[None, bool] = False, anomaly=False):
+                                 label=None, spline: Union[None, bool] = True, anomaly=True):
     splines = [spline] if spline is not None else [True, False]
     for spline in splines:
         years, global_mean_temp = years_and_global_mean_temps(gcm, scenario, year_min=year_min, year_max=year_max, spline=spline, anomaly=anomaly)
@@ -87,5 +87,5 @@ def plot_temperature_for_rcp_gcm(ax, gcm, scenario, year_min, year_max, linestyl
 
 
 if __name__ == '__main__':
-    main_plot_temperature_with_spline_on_top(anomaly=True)
-    # main_plot_temperature_all(anomaly=True, spline=False)
+    # main_plot_temperature_with_spline_on_top(anomaly=True)
+    main_plot_temperature_all(anomaly=True, spline=True)

extreme_trend/one_fold_fit/altitudes_studies_visualizer_for_non_stationary_models.py

@@ -26,7 +26,7 @@ from extreme_trend.one_fold_fit.one_fold_fit import \
     OneFoldFit
 from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
 from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
-    AnomalyTemperatureTemporalCovariate
+    AnomalyTemperatureWithSplineTemporalCovariate
 
 
 class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
@@ -182,7 +182,7 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
         moment = ' '.join(method_name.split('_'))
         d_temperature = {'C': '{C}'}
         str_for_last_year = ' at +${}^o\mathrm{C}$' \
-            if self.temporal_covariate_for_fit is AnomalyTemperatureTemporalCovariate else ' in {}'
+            if self.temporal_covariate_for_fit is AnomalyTemperatureWithSplineTemporalCovariate else ' in {}'
         str_for_last_year = str_for_last_year.format(self.first_one_fold_fit.covariate_after, **d_temperature)
         moment = moment.replace('moment', '{}{}'.format(OneFoldFit.get_moment_str(order=order), str_for_last_year))
         plot_name = '{} '.format(moment)

extreme_trend/one_fold_fit/one_fold_fit.py

@@ -31,7 +31,7 @@ from extreme_trend.one_fold_fit.altitude_group import DefaultAltitudeGroup, alti
 from root_utils import NB_CORES, batch
 from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import TimeTemporalCovariate
 from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
-    AnomalyTemperatureTemporalCovariate
+    AnomalyTemperatureWithSplineTemporalCovariate
 from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
 from spatio_temporal_dataset.slicer.split import Split
 from spatio_temporal_dataset.spatio_temporal_observations.annual_maxima_observations import AnnualMaxima
@@ -133,7 +133,7 @@ class OneFoldFit(object):
     def _covariate_before_and_after(self):
         if self.temporal_covariate_for_fit in [None, TimeTemporalCovariate]:
             return self.last_year - self.nb_years, self.last_year
-        elif self.temporal_covariate_for_fit is AnomalyTemperatureTemporalCovariate:
+        elif self.temporal_covariate_for_fit is AnomalyTemperatureWithSplineTemporalCovariate:
             # In 2020, we are roughly at 1 degree. Thus it natural to see the augmentation from 1 to 2 degree.
             return 1, self.last_anomaly
         else:
@@ -142,7 +142,7 @@ class OneFoldFit(object):
     @property
     def between_covariate_str(self):
         d_temperature = {'C': '{C}'}
-        s = ' between +${}^o\mathrm{C}$ and +${}^o\mathrm{C}$' if self.temporal_covariate_for_fit is AnomalyTemperatureTemporalCovariate \
+        s = ' between +${}^o\mathrm{C}$ and +${}^o\mathrm{C}$' if self.temporal_covariate_for_fit is AnomalyTemperatureWithSplineTemporalCovariate \
             else ' between {} and {}'
         s = s.format(self.covariate_before, self.covariate_after,
                      **d_temperature)

projects/projected_extreme_snowfall/main_elevation_temporal_for_projections_ensemble.py

@@ -8,16 +8,15 @@ from extreme_trend.elevation_temporal_model_for_projections.visualizer_for_sensi
     VisualizerForSensivity
 
 from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fit import IndependentEnsembleFit
+from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
 from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
-    AnomalyTemperatureTemporalCovariate
+    AnomalyTemperatureWithSplineTemporalCovariate
 
 mpl.rcParams['text.usetex'] = True
 mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
 
 from extreme_fit.model.margin_model.polynomial_margin_model.utils import \
     ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
-from extreme_trend.elevation_temporal_model_for_projections.visualizer_for_projection_ensemble import \
-    VisualizerForProjectionEnsemble
 import matplotlib
 from extreme_fit.model.utils import set_seed_for_test
 
@@ -40,7 +39,7 @@ def main():
     start = time.time()
     study_class = AdamontSnowfall
     ensemble_fit_class = [IndependentEnsembleFit]
-    temporal_covariate_for_fit = [TimeTemporalCovariate, AnomalyTemperatureTemporalCovariate][1]
+    temporal_covariate_for_fit = [TimeTemporalCovariate, AnomalyTemperatureWithSplineTemporalCovariate][1]
     set_seed_for_test()
     AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
 

spatio_temporal_dataset/coordinates/temporal_coordinates/temperature_covariate.py

@@ -44,7 +44,7 @@ class MeanAlpsTemperatureCovariate(AbstractTemperatureCovariate):
     def load_year_to_temperature_covariate(cls):
         return load_year_to_mean_alps_temperatures()
 
-class AnomalyTemperatureTemporalCovariate(AbstractTemporalCovariateForFit):
+class AnomalyTemperatureWithSplineTemporalCovariate(AbstractTemporalCovariateForFit):
     gcm_and_scenario_to_d = {}
 
     @classmethod
@@ -54,7 +54,7 @@ class AnomalyTemperatureTemporalCovariate(AbstractTemporalCovariateForFit):
         scenario_str = row[AbstractCoordinates.COORDINATE_RCP]
         scenario = str_to_scenario(scenario_str)
         if (gcm, scenario) not in cls.gcm_and_scenario_to_d:
-            d = year_to_global_mean_temp(gcm, scenario, anomaly=True)
+            d = year_to_global_mean_temp(gcm, scenario, anomaly=True, spline=True)
             cls.gcm_and_scenario_to_d[(gcm, scenario)] = d
         d = cls.gcm_and_scenario_to_d[(gcm, scenario)]
         global_mean_temp = d[year]

test/test_extreme_trend/test_one_fold_fit.py

@@ -16,7 +16,7 @@ from extreme_trend.one_fold_fit.one_fold_fit import OneFoldFit
 from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
     TimeTemporalCovariate
 from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
-    AnomalyTemperatureTemporalCovariate
+    AnomalyTemperatureWithSplineTemporalCovariate
 
 
 class TestOneFoldFit(unittest.TestCase):
@@ -60,7 +60,7 @@ class TestOneFoldFit(unittest.TestCase):
             dataset = self.load_dataset(study_class, scenario=AdamontScenario.rcp85)
             one_fold_fit = OneFoldFit(self.massif_name, dataset,
                                       models_classes=self.model_classes,
-                                      temporal_covariate_for_fit=AnomalyTemperatureTemporalCovariate,
+                                      temporal_covariate_for_fit=AnomalyTemperatureWithSplineTemporalCovariate,
                                       only_models_that_pass_goodness_of_fit_test=False)
             _ = one_fold_fit.best_estimator.margin_model
         self.assertTrue(True)
@@ -91,7 +91,7 @@ class TestOneFoldFit(unittest.TestCase):
                                     year_min=year_min, year_max=year_max)
         one_fold_fit = OneFoldFit(self.massif_name, dataset,
                                   models_classes=self.model_classes,
-                                  temporal_covariate_for_fit=AnomalyTemperatureTemporalCovariate,
+                                  temporal_covariate_for_fit=AnomalyTemperatureWithSplineTemporalCovariate,
                                   altitude_class=VeyHighAltitudeGroup,
                                   only_models_that_pass_goodness_of_fit_test=False,
                                   remove_physically_implausible_models=True)