[Temporal fit] add fit method parameter to all init methods

experiment/paper_past_snow_loads/paper_main_utils.py

@@ -9,7 +9,7 @@ from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear
 def load_altitude_to_visualizer(altitudes, massif_names, non_stationary_uncertainty, study_class, uncertainty_methods,
                                 study_visualizer_class=StudyVisualizerForNonStationaryTrends,
                                 save_to_file=True):
-    fit_method = TemporalMarginFitMethod.extremes_fevd_gmle
+    fit_method = TemporalMarginFitMethod.extremes_fevd_mle
     altitude_to_visualizer = OrderedDict()
     for altitude in altitudes:
         altitude_to_visualizer[altitude] = study_visualizer_class(

experiment/paper_past_snow_loads/result_trends_and_return_levels/main_result_trends_and_return_levels.py

@@ -94,12 +94,12 @@ def major_result():
 
 
 if __name__ == '__main__':
-    major_result()
-    # intermediate_result(altitudes=[900, 1200], massif_names=['Vercors'],
-    #                     uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
-    #                                          ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
-    #                     non_stationary_uncertainty=[False, True][1:],
-    #                     multiprocessing=True)
+    # major_result()
+    intermediate_result(altitudes=[900, 1200], massif_names=['Vercors'],
+                        uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
+                                             ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
+                        non_stationary_uncertainty=[False, True][1:],
+                        multiprocessing=True)
     # intermediate_result(altitudes=[900, 1200], massif_names=['Maurienne'],
     #                     uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.my_bayes,
     #                                          ConfidenceIntervalMethodFromExtremes.ci_mle][1:],
@@ -125,4 +125,4 @@ if __name__ == '__main__':
     #                     non_stationary_uncertainty=[False, True])
     # intermediate_result(altitudes=[300, 600, 900], massif_names=None,
     #                     uncertainty_methods=[ConfidenceIntervalMethodFromExtremes.ci_mle],
-    #                     non_stationary_uncertainty=[False, True])
+    #                     non_stationary_uncertainty=[False, True])
\ No newline at end of file

experiment/paper_past_snow_loads/study_visualizer_for_non_stationary_trends.py

@@ -119,13 +119,10 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
         for massif_name, (x, y) in self.massif_name_to_non_null_years_and_maxima.items():
             quantile_level = self.massif_name_to_eurocode_quantile_level_in_practice[massif_name]
             non_stationary_trend_test = [
-                t(years=x, maxima=y, starting_year=starting_year, quantile_level=quantile_level)
+                t(years=x, maxima=y, starting_year=starting_year, quantile_level=quantile_level,
+                  fit_method=self.fit_method)
                 for t in self.non_stationary_trend_test]  # type: List[AbstractGevTrendTest]
-            # Set appropriate fit method for all objects (#todo: set this parameter directly in the init function)
-            if self.fit_method is not None:
-                for t in non_stationary_trend_test:
-                    t.fit_method = self.fit_method
-            # Extract
+            # Extract the model with minimized AIC
             trend_test_that_minimized_aic = sorted(non_stationary_trend_test, key=lambda t: t.aic)[0]
             massif_name_to_trend_test_that_minimized_aic[massif_name] = trend_test_that_minimized_aic
         return massif_name_to_trend_test_that_minimized_aic

experiment/trend_analysis/univariate_test/extreme_trend_test/abstract_gev_trend_test.py

@@ -25,12 +25,12 @@ class AbstractGevTrendTest(AbstractUnivariateTest):
     def __init__(self, years, maxima, starting_year, unconstrained_model_class,
                  constrained_model_class=StationaryTemporalModel,
                  quantile_level=EUROCODE_QUANTILE,
-                 ):
+                 fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year)
-        self.quantile_level = quantile_level
         self.unconstrained_model_class = unconstrained_model_class
         self.constrained_model_class = constrained_model_class
-        self.fit_method = TemporalMarginFitMethod.extremes_fevd_mle
+        self.quantile_level = quantile_level
+        self.fit_method = fit_method
         # Load observations, coordinates and datasets
         self.coordinates, self.dataset = load_temporal_coordinates_and_dataset(maxima, years)
         # By default crashed boolean is False

experiment/trend_analysis/univariate_test/extreme_trend_test/trend_test_one_parameter/abstract_comparison_non_stationary_model.py

@@ -3,6 +3,8 @@ from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_t
 from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gev_trend_test_one_parameter import \
     GevTrendTestOneParameter
 from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import GevLocationAndScaleTrendTest
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+    TemporalMarginFitMethod
 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import \
     NonStationaryLocationTemporalModel, NonStationaryScaleTemporalModel
 import numpy as np
@@ -19,13 +21,13 @@ class AbstractComparisonNonStationaryModelOneParameter(GevTrendTestOneParameter)
 
 class ComparisonAgainstMu(AbstractComparisonNonStationaryModelOneParameter, GevLocationAndScaleTrendTest):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year, constrained_model_class=NonStationaryLocationTemporalModel,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level, fit_method=fit_method)
 
 
 class ComparisonAgainstSigma(AbstractComparisonNonStationaryModelOneParameter, GevLocationAndScaleTrendTest):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year, constrained_model_class=NonStationaryScaleTemporalModel,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level, fit_method=fit_method)

experiment/trend_analysis/univariate_test/extreme_trend_test/trend_test_one_parameter/gev_trend_test_one_parameter.py

 from experiment.eurocode_data.utils import EUROCODE_QUANTILE
 from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import AbstractGevTrendTest
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+    TemporalMarginFitMethod
 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import \
     NonStationaryLocationTemporalModel, NonStationaryScaleTemporalModel, NonStationaryShapeTemporalModel, \
     StationaryTemporalModel
@@ -18,11 +20,13 @@ class GevTrendTestOneParameterAgainstStationary(GevTrendTestOneParameter):
 
     def __init__(self, years, maxima, starting_year, unconstrained_model_class, gev_param_name,
                  quantile_level=EUROCODE_QUANTILE,
-                 constrained_model_class=StationaryTemporalModel):
+                 constrained_model_class=StationaryTemporalModel,
+                 fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=unconstrained_model_class,
                          quantile_level=quantile_level,
-                         constrained_model_class=constrained_model_class)
+                         constrained_model_class=constrained_model_class,
+                         fit_method=fit_method)
         self.gev_param_name = gev_param_name
 
     @property
@@ -32,12 +36,14 @@ class GevTrendTestOneParameterAgainstStationary(GevTrendTestOneParameter):
 
 class GevLocationTrendTest(GevTrendTestOneParameterAgainstStationary):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, constrained_model_class=StationaryTemporalModel):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, constrained_model_class=StationaryTemporalModel,
+                 fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryLocationTemporalModel,
                          constrained_model_class=constrained_model_class,
                          gev_param_name=GevParams.LOC,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     def _slope_strength(self):
         return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(p=self.quantile_level,
@@ -55,12 +61,14 @@ class GevLocationTrendTest(GevTrendTestOneParameterAgainstStationary):
 
 class GevScaleTrendTest(GevTrendTestOneParameterAgainstStationary):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, constrained_model_class=StationaryTemporalModel):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, constrained_model_class=StationaryTemporalModel,
+                 fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryScaleTemporalModel,
                          constrained_model_class=constrained_model_class,
                          gev_param_name=GevParams.SCALE,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     def _slope_strength(self):
         return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(
@@ -81,10 +89,11 @@ class GevScaleTrendTest(GevTrendTestOneParameterAgainstStationary):
 
 class GevShapeTrendTest(GevTrendTestOneParameterAgainstStationary):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryShapeTemporalModel,
                          gev_param_name=GevParams.SHAPE,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
 

experiment/trend_analysis/univariate_test/extreme_trend_test/trend_test_one_parameter/gumbel_trend_test_one_parameter.py

@@ -3,6 +3,8 @@ from experiment.eurocode_data.utils import EUROCODE_QUANTILE
 from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gev_trend_test_one_parameter import \
     GevTrendTestOneParameter, GevTrendTestOneParameterAgainstStationary
 from extreme_fit.distribution.gev.gev_params import GevParams
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+    TemporalMarginFitMethod
 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import StationaryTemporalModel, \
     GumbelTemporalModel, NonStationaryLocationGumbelModel, NonStationaryScaleGumbelModel
 from root_utils import classproperty
@@ -10,11 +12,12 @@ from root_utils import classproperty
 
 class GumbelVersusGumbel(GevTrendTestOneParameter):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=GumbelTemporalModel,
                          constrained_model_class=GumbelTemporalModel,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     @property
     def is_significant(self) -> bool:
@@ -38,11 +41,13 @@ class GumbelVersusGumbel(GevTrendTestOneParameter):
 
 class GevStationaryVersusGumbel(GevTrendTestOneParameter):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE,
+                  fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=StationaryTemporalModel,
                          constrained_model_class=GumbelTemporalModel,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     @property
     def total_number_of_parameters_for_unconstrained_model(self) -> int:
@@ -62,12 +67,12 @@ class GevStationaryVersusGumbel(GevTrendTestOneParameter):
 
 class GumbelLocationTrendTest(GevTrendTestOneParameterAgainstStationary):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryLocationGumbelModel,
                          gev_param_name=GevParams.LOC,
                          quantile_level=quantile_level,
-                         constrained_model_class=GumbelTemporalModel)
+                         constrained_model_class=GumbelTemporalModel, fit_method=fit_method)
 
     @property
     def total_number_of_parameters_for_unconstrained_model(self) -> int:
@@ -88,12 +93,14 @@ class GumbelLocationTrendTest(GevTrendTestOneParameterAgainstStationary):
 
 class GumbelScaleTrendTest(GevTrendTestOneParameterAgainstStationary):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE,
+                 fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryScaleGumbelModel,
                          gev_param_name=GevParams.SCALE,
                          quantile_level=quantile_level,
-                         constrained_model_class=GumbelTemporalModel)
+                         constrained_model_class=GumbelTemporalModel,
+                         fit_method=fit_method)
 
     def _slope_strength(self):
         return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(

experiment/trend_analysis/univariate_test/extreme_trend_test/trend_test_three_parameters/gev_trend_test_three_parameters.py

 from experiment.eurocode_data.utils import EUROCODE_QUANTILE
 from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import \
     GevLocationAndScaleTrendTest
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+    TemporalMarginFitMethod
 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import StationaryTemporalModel
 from experiment.eurocode_data.utils import EUROCODE_QUANTILE
 from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import AbstractGevTrendTest
@@ -20,11 +22,12 @@ class GevTrendTestThreeParameters(AbstractGevTrendTest):
 
 class GevLocationAndScaleTrendTestAgainstGumbel(GevTrendTestThreeParameters):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryLocationAndScaleTemporalModel,
                          constrained_model_class=GumbelTemporalModel,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     @property
     def mu1(self):

experiment/trend_analysis/univariate_test/extreme_trend_test/trend_test_two_parameters/gev_trend_test_two_parameters.py

@@ -2,6 +2,8 @@ from experiment.eurocode_data.utils import EUROCODE_QUANTILE
 from experiment.trend_analysis.univariate_test.extreme_trend_test.abstract_gev_trend_test import AbstractGevTrendTest
 from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_one_parameter.gev_trend_test_one_parameter import \
     GevLocationTrendTest, GevScaleTrendTest
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+    TemporalMarginFitMethod
 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import \
     NonStationaryLocationAndScaleTemporalModel, StationaryTemporalModel, NonStationaryLocationAndScaleGumbelModel, \
     GumbelTemporalModel
@@ -19,11 +21,12 @@ class GevTrendTestTwoParameters(AbstractGevTrendTest):
 class GevLocationAndScaleTrendTest(GevTrendTestTwoParameters):
 
     def __init__(self, years, maxima, starting_year, constrained_model_class=StationaryTemporalModel,
-                 quantile_level=EUROCODE_QUANTILE):
+                 quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryLocationAndScaleTemporalModel,
                          constrained_model_class=constrained_model_class,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     @property
     def mu1(self):
@@ -51,8 +54,8 @@ class GevLocationAndScaleTrendTest(GevTrendTestTwoParameters):
 
 class GevLocationAgainstGumbel(GevTrendTestTwoParameters, GevLocationTrendTest):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
-        super().__init__(years, maxima, starting_year, quantile_level, GumbelTemporalModel)
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
+        super().__init__(years, maxima, starting_year, quantile_level, GumbelTemporalModel, fit_method=fit_method)
 
     @classproperty
     def label(self):
@@ -69,8 +72,8 @@ class GevLocationAgainstGumbel(GevTrendTestTwoParameters, GevLocationTrendTest):
 
 class GevScaleAgainstGumbel(GevTrendTestTwoParameters, GevScaleTrendTest):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
-        super().__init__(years, maxima, starting_year, quantile_level, GumbelTemporalModel)
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
+        super().__init__(years, maxima, starting_year, quantile_level, GumbelTemporalModel, fit_method=fit_method)
 
     @classproperty
     def label(self):

experiment/trend_analysis/univariate_test/extreme_trend_test/trend_test_two_parameters/gumbel_test_two_parameters.py

@@ -2,6 +2,8 @@ from experiment.eurocode_data.utils import EUROCODE_QUANTILE
 from experiment.trend_analysis.univariate_test.extreme_trend_test.trend_test_two_parameters.gev_trend_test_two_parameters import \
     GevTrendTestTwoParameters
 from extreme_fit.distribution.gev.gev_params import GevParams
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+    TemporalMarginFitMethod
 from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import \
     NonStationaryLocationAndScaleGumbelModel, GumbelTemporalModel
 from root_utils import classproperty
@@ -9,11 +11,12 @@ from root_utils import classproperty
 
 class GumbelLocationAndScaleTrendTest(GevTrendTestTwoParameters):
 
-    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE):
+    def __init__(self, years, maxima, starting_year, quantile_level=EUROCODE_QUANTILE, fit_method=TemporalMarginFitMethod.extremes_fevd_mle):
         super().__init__(years, maxima, starting_year,
                          unconstrained_model_class=NonStationaryLocationAndScaleGumbelModel,
                          constrained_model_class=GumbelTemporalModel,
-                         quantile_level=quantile_level)
+                         quantile_level=quantile_level,
+                         fit_method=fit_method)
 
     @property
     def total_number_of_parameters_for_unconstrained_model(self) -> int: