[contrasting] display individual model fitted with all data (300-4800)....

[contrasting] display individual model fitted with all data (300-4800). Display only the best non-stationary model if it passes the Anderson fit test.

extreme_fit/model/margin_model/polynomial_margin_model/gev_altitudinal_models.py

@@ -37,6 +37,9 @@ class AbstractAltitudinalModel(AbstractSpatioTemporalPolynomialModel):
         name = self.DISTRIBUTION_STR
         name += self.dim_to_str_number(GevParams.LOC, self.coordinates.idx_temporal_coordinates)
         name += self.dim_to_str_number(GevParams.SCALE, self.coordinates.idx_temporal_coordinates)
+        shape_str_number = self.dim_to_str_number(GevParams.SHAPE, self.coordinates.idx_temporal_coordinates)
+        if shape_str_number != '0':
+            name += shape_str_number
         if isinstance(self, AbstractAddCrossTermForLocation):
             name += 'x'
         if isinstance(self, AbstractAddCrossTermForScale):
@@ -126,6 +129,14 @@ class NonStationaryAltitudinalLocationQuadraticScaleLinear(AbstractAltitudinalMo
 
 class AbstractAddCrossTermForLocation(AbstractAltitudinalModel):
 
+    # @property
+    # def param_name_to_list_dim_and_degree_for_margin_function(self):
+    #     d = self.param_name_to_list_dim_and_degree
+    #     assert 1 <= len(d[GevParams.LOC]) <= 2
+    #     assert self.coordinates.idx_x_coordinates == d[GevParams.LOC][0][0]
+    #     d[GevParams.LOC].insert(1, ((self.coordinates.idx_x_coordinates, self.coordinates.idx_temporal_coordinates), 1))
+    #     return d
+
     @property
     def param_name_to_list_dim_and_degree_for_margin_function(self):
         d = self.param_name_to_list_dim_and_degree

extreme_fit/model/margin_model/polynomial_margin_model/gev_altitudinal_models_with_scale_2.py

+from extreme_fit.distribution.gev.gev_params import GevParams
+from extreme_fit.model.margin_model.polynomial_margin_model.gev_altitudinal_models import AbstractAltitudinalModel, \
+    AbstractAddCrossTermForLocation
+from extreme_fit.model.margin_model.polynomial_margin_model.polynomial_margin_model import PolynomialMarginModel
+from extreme_fit.model.margin_model.polynomial_margin_model.spatio_temporal_polynomial_model import \
+    AbstractSpatioTemporalPolynomialModel
+
+
+
+
+
+
+class NonStationaryAltitudinalScaleLinear(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1),  (self.coordinates.idx_temporal_coordinates, 1)],
+        }
+
+class NonStationaryAltitudinalScaleQuadratic(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1),  (self.coordinates.idx_temporal_coordinates, 2)],
+        }
+
+
+class NonStationaryAltitudinalScaleLinearLocationLinear(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+        }
+
+class NonStationaryAltitudinalScaleQuadraticLocationLinear(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+        }
+
+
+class NonStationaryAltitudinalLocationQuadraticScaleLinear(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+        }
+
+class NonStationaryAltitudinalLocationQuadraticScaleQuadratic(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+        }
+
+class NonStationaryAltitudinalLocationCubicScaleLinear(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 3)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+        }
+
+class NonStationaryAltitudinalLocationCubicScaleQuadratic(AbstractAltitudinalModel):
+
+    @property
+    def param_name_to_list_dim_and_degree(self):
+        return {
+            GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 3)],
+            GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+        }
+
+# Add cross terms
+
+
+
+class NonStationaryAltitudinalScaleLinearCrossTermForLocation(AbstractAddCrossTermForLocation, NonStationaryAltitudinalScaleLinear):
+    pass
+
+
+class NonStationaryAltitudinalScaleLinearLocationLinearCrossTermForLocation(AbstractAddCrossTermForLocation,
+                                                                            NonStationaryAltitudinalScaleLinearLocationLinear):
+    pass
+
+
+class NonStationaryAltitudinalLocationQuadraticScaleLinearCrossTermForLocation(AbstractAddCrossTermForLocation,
+                                                                               NonStationaryAltitudinalLocationQuadraticScaleLinear):
+    pass
+class NonStationaryAltitudinalLocationCubicScaleLinearCrossTermForLocation(AbstractAddCrossTermForLocation,
+                                                                               NonStationaryAltitudinalLocationCubicScaleLinear):
+    pass
+
+
+
+
+class NonStationaryAltitudinalScaleQuadraticCrossTermForLocation(AbstractAddCrossTermForLocation, NonStationaryAltitudinalScaleQuadratic):
+    pass
+
+
+class NonStationaryAltitudinalScaleQuadraticLocationLinearCrossTermForLocation(AbstractAddCrossTermForLocation,
+                                                                            NonStationaryAltitudinalScaleQuadraticLocationLinear):
+    pass
+
+
+
+class NonStationaryAltitudinalLocationQuadraticScaleQuadraticCrossTermForLocation(AbstractAddCrossTermForLocation,
+                                                                               NonStationaryAltitudinalLocationQuadraticScaleQuadratic):
+    pass
+
+
+class NonStationaryAltitudinalLocationCubicScaleQuadraticCrossTermForLocation(AbstractAddCrossTermForLocation,
+                                                                               NonStationaryAltitudinalLocationCubicScaleQuadratic):
+    pass
+
+

extreme_fit/model/margin_model/polynomial_margin_model/utils.py

@@ -28,6 +28,13 @@ from extreme_fit.model.margin_model.polynomial_margin_model.gev_altitudinal_mode
     NonStationaryAltitudinalLocationLinearScaleQuadratic, NonStationaryAltitudinalLocationQuadraticScaleQuadratic, \
     NonStationaryAltitudinalLocationLinearScaleQuadraticCrossTermForLocation, \
     NonStationaryAltitudinalLocationQuadraticScaleQuadraticCrossTermForLocation
+from extreme_fit.model.margin_model.polynomial_margin_model.gev_altitudinal_models_with_scale_2 import \
+    NonStationaryAltitudinalScaleLinearCrossTermForLocation, \
+    NonStationaryAltitudinalScaleLinearLocationLinearCrossTermForLocation, \
+    NonStationaryAltitudinalLocationQuadraticScaleLinearCrossTermForLocation, \
+    NonStationaryAltitudinalScaleQuadraticLocationLinearCrossTermForLocation, \
+    NonStationaryAltitudinalLocationCubicScaleQuadraticCrossTermForLocation, \
+    NonStationaryAltitudinalLocationCubicScaleLinearCrossTermForLocation
 from extreme_fit.model.margin_model.polynomial_margin_model.gumbel_altitudinal_models import \
     StationaryGumbelAltitudinal, NonStationaryGumbelAltitudinalScaleLinear, \
     NonStationaryGumbelAltitudinalLocationLinear, NonStationaryGumbelAltitudinalLocationQuadratic, \
@@ -44,37 +51,61 @@ from extreme_fit.model.margin_model.polynomial_margin_model.spatio_temporal_poly
     NonStationaryLocationSpatioTemporalLinearityModelAssertError2, \
     NonStationaryLocationSpatioTemporalLinearityModelAssertError3, NonStationaryLocationSpatioTemporalLinearityModel6
 
-
 ALTITUDINAL_GEV_MODELS_LOCATION = [
     StationaryAltitudinal,
-    NonStationaryAltitudinalLocationLinear,
+    # NonStationaryAltitudinalLocationLinear,
+    # NonStationaryAltitudinalLocationQuadratic,
+    # NonStationaryAltitudinalLocationCubic,
+    # NonStationaryAltitudinalLocationOrder4,
+    # # First order cross term
+    # NonStationaryCrossTermForLocation,
+
+    # NonStationaryAltitudinalLocationLinearCrossTermForLocation,
+    NonStationaryAltitudinalLocationQuadraticCrossTermForLocation,
+    NonStationaryAltitudinalLocationCubicCrossTermForLocation,
+    # NonStationaryAltitudinalLocationOrder4CrossTermForLocation,
+    # NonStationaryAltitudinalScaleLinearCrossTermForLocation,
+    # NonStationaryAltitudinalScaleLinearLocationLinearCrossTermForLocation,
+
+    # NonStationaryAltitudinalScaleQuadraticCrossTermForLocation,
+    # NonStationaryAltitudinalScaleQuadraticLocationLinearCrossTermForLocation,
+
+    # NonStationaryAltitudinalLocationQuadraticScaleLinearCrossTermForLocation,
+    # NonStationaryAltitudinalLocationCubicScaleLinearCrossTermForLocation,
+    # NonStationaryAltitudinalLocationQuadraticScaleQuadraticCrossTermForLocation,
+    # NonStationaryAltitudinalLocationCubicScaleQuadraticCrossTermForLocation,
+
+]
+ALTITUDINAL_GEV_MODELS_LOCATION_QUADRATIC_MINIMUM = [
+    StationaryAltitudinal,
+    # NonStationaryAltitudinalLocationLinear,
     NonStationaryAltitudinalLocationQuadratic,
     NonStationaryAltitudinalLocationCubic,
     NonStationaryAltitudinalLocationOrder4,
-    # First order cross term
-    NonStationaryCrossTermForLocation,
-    NonStationaryAltitudinalLocationLinearCrossTermForLocation,
+    # # First order cross term
+    # NonStationaryCrossTermForLocation,
+    # NonStationaryAltitudinalLocationLinearCrossTermForLocation,
     NonStationaryAltitudinalLocationQuadraticCrossTermForLocation,
     NonStationaryAltitudinalLocationCubicCrossTermForLocation,
     NonStationaryAltitudinalLocationOrder4CrossTermForLocation,
 
 ]
 
+
 ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES = [
-StationaryAltitudinalOnlyScale,
-NonStationaryAltitudinalOnlyScaleLocationLinear,
-NonStationaryAltitudinalOnlyScaleLocationQuadratic,
-NonStationaryAltitudinalOnlyScaleLocationCubic,
-NonStationaryAltitudinalOnlyScaleLocationOrder4,
-# Cross terms
-NonStationaryOnlyScaleCrossTermForLocation,
-NonStationaryAltitudinalOnlyScaleLocationLinearCrossTermForLocation,
-NonStationaryAltitudinalOnlyScaleLocationQuadraticCrossTermForLocation,
-NonStationaryAltitudinalOnlyScaleLocationCubicCrossTermForLocation,
-NonStationaryAltitudinalOnlyScaleLocationOrder4CrossTermForLocation,
+    StationaryAltitudinalOnlyScale,
+    NonStationaryAltitudinalOnlyScaleLocationLinear,
+    NonStationaryAltitudinalOnlyScaleLocationQuadratic,
+    NonStationaryAltitudinalOnlyScaleLocationCubic,
+    NonStationaryAltitudinalOnlyScaleLocationOrder4,
+    # Cross terms
+    NonStationaryOnlyScaleCrossTermForLocation,
+    NonStationaryAltitudinalOnlyScaleLocationLinearCrossTermForLocation,
+    NonStationaryAltitudinalOnlyScaleLocationQuadraticCrossTermForLocation,
+    NonStationaryAltitudinalOnlyScaleLocationCubicCrossTermForLocation,
+    NonStationaryAltitudinalOnlyScaleLocationOrder4CrossTermForLocation,
 ]
 
-
 ALTITUDINAL_GEV_MODELS = [
                              StationaryAltitudinal,
                              NonStationaryAltitudinalScaleLinear,
@@ -108,7 +139,6 @@ ALTITUDINAL_GEV_MODELS = [
 
                          ][:]
 
-
 ALTITUDINAL_GUMBEL_MODELS = [
                                 StationaryGumbelAltitudinal,
                                 NonStationaryGumbelAltitudinalScaleLinear,

projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py

@@ -3,7 +3,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 
 from extreme_fit.model.margin_model.polynomial_margin_model.utils import ALTITUDINAL_GEV_MODELS, \
-    ALTITUDINAL_GEV_MODELS_LOCATION, ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES
+    ALTITUDINAL_GEV_MODELS_LOCATION_QUADRATIC_MINIMUM, ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES, ALTITUDINAL_GEV_MODELS_LOCATION
 from projects.altitude_spatial_model.altitudes_fit.one_fold_analysis.plot_total_aic import plot_total_aic, \
     plot_individual_aic
 
@@ -35,16 +35,18 @@ def plot_moments(studies, massif_names=None):
 
 def plot_altitudinal_fit(studies, massif_names=None):
     # model_classes = ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES
+    # model_classes = ALTITUDINAL_GEV_MODELS_LOCATION_QUADRATIC_MINIMUM
     model_classes = ALTITUDINAL_GEV_MODELS_LOCATION
+    # model_classes = ALTITUDINAL_GEV_MODELS_LOCATION_CUBIC_MINIMUM
     # model_classes = ALTITUDINAL_GEV_MODELS_QUADRATIC
     visualizer = AltitudesStudiesVisualizerForNonStationaryModels(studies=studies,
                                                                   model_classes=model_classes,
                                                                   massif_names=massif_names,
                                                                   show=False)
     # Plot the results for the model that minimizes the individual aic
-    # plot_individual_aic(visualizer)
+    plot_individual_aic(visualizer)
     # Plot the results for the model that minimizes the total aic
-    plot_total_aic(model_classes, visualizer)
+    # plot_total_aic(model_classes, visualizer)
 
 
 def main():
@@ -54,6 +56,9 @@ def main():
     # mais pris en compte pour le calcul de mon aic
     # altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000][:]
     altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900, 4200, 4500, 4800][:]
+    # altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900][:]
+    # altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000][:]
+    # altitudes = [600, 900, 1200, 1500, 1800, 2100][:]
     # altitudes = [1500, 1800][:]
     study_classes = [SafranSnowfall1Day, SafranSnowfall3Days, SafranSnowfall5Days, SafranSnowfall7Days][:2]
     study_classes = [SafranPrecipitation1Day, SafranPrecipitation3Days, SafranPrecipitation5Days,

projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py

@@ -26,7 +26,7 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
                  show=False,
                  massif_names=None,
                  fit_method=MarginFitMethod.extremes_fevd_mle,
-                 display_only_model_that_pass_anderson_test=False):
+                 display_only_model_that_pass_anderson_test=True):
         super().__init__(studies.study, show=show, save_to_file=not show)
         self.studies = studies
         self.non_stationary_models = model_classes
@@ -100,7 +100,7 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
             dim_to_coordinate_name = dict(zip([0, 1], coordinate_names))
             for dim in [0, 1, (0, 1)]:
                 coordinate_name = LinearCoef.coefficient_name(dim, dim_to_coordinate_name)
-                for degree in range(3):
+                for degree in range(4):
                     coef_name = ' '.join([param_name + coordinate_name + str(degree)])
                     massif_name_to_best_coef = {}
                     for massif_name, one_fold_fit in self.massif_name_to_one_fold_fit.items():
@@ -109,7 +109,7 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
                             massif_name_to_best_coef[massif_name] = best_coef
 
                     if len(massif_name_to_best_coef) > 0:
-                        for evaluate_coordinate in [False, True]:
+                        for evaluate_coordinate in [False, True][:1]:
                             if evaluate_coordinate:
                                 coef_name += 'evaluated at coordinates'
                                 for massif_name in massif_name_to_best_coef.keys():
@@ -144,10 +144,11 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
 
     def plot_year_for_the_peak(self):
         t_list = 1959 + np.arange(141)
+        # t_list = 1800 + np.arange(400)
         for massif_name, one_fold_fit in self.massif_name_to_one_fold_fit.items():
             ax = plt.gca()
             # One plot for each altitude
-            altitudes = np.arange(500, 3000, 500)
+            altitudes = np.arange(500, min(3000, max(self.studies.altitudes)), 500)
             for altitude in altitudes:
                 i = 0
                 while self.studies.altitudes[i] < altitude:
@@ -163,6 +164,10 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
                     label = '{} m'.format(altitude)
                     ax.plot(t_list, mean_list, label=label)
             ax.legend()
+            # Modify the limits of the y axis
+            lim_down, lim_up = ax.get_ylim()
+            ax_lim = (0, lim_up)
+            ax.set_ylim(ax_lim)
             ax.set_xlabel('Year')
             ax.set_ylabel('Mean annual maxima of {}'.format(SCM_STUDY_CLASS_TO_ABBREVIATION[type(self.study)]))
             plot_name = '{}/{}/Peak year for {}'.format(OneFoldFit.folder_for_plots, 'Peak year', massif_name.replace('_', ''))

projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/one_fold_fit.py

@@ -97,6 +97,10 @@ class OneFoldFit(object):
         sorted_estimators = sorted([estimator for estimator in estimators], key=lambda e: e.aic())
         return sorted_estimators
 
+    @cached_property
+    def sorted_estimators_without_stationary(self):
+        return [e for e in self.sorted_estimators if not isinstance(e.margin_model, StationaryAltitudinal)]
+
     @property
     def model_class_to_estimator_with_finite_aic(self):
         return {type(estimator.margin_model): estimator for estimator in self.sorted_estimators}
@@ -106,7 +110,8 @@ class OneFoldFit(object):
         if self.best_estimator_minimizes_total_aic and self.best_estimator_class_for_total_aic is not None:
             return self.model_class_to_estimator[self.best_estimator_class_for_total_aic]
         else:
-            return self.sorted_estimators[0]
+            best_estimator = self.sorted_estimators_without_stationary[0]
+            return best_estimator
 
     @property
     def best_margin_model(self):