diff --git a/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/__init__.py b/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/abstract_margin_model_with_effect.py b/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/abstract_margin_model_with_effect.py
new file mode 100644
index 0000000000000000000000000000000000000000..72552ac741149d19a47ea5fa7eb0573923391111
--- /dev/null
+++ b/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/abstract_margin_model_with_effect.py
@@ -0,0 +1,5 @@
+
+
+class AbstractMarginModelWithEffect(object):
+ pass
+
diff --git a/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/margin_model_with_gcm_effect.py b/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/margin_model_with_gcm_effect.py
new file mode 100644
index 0000000000000000000000000000000000000000..79e5361073091baa96ee385d16133bbac1934f14
--- /dev/null
+++ b/extreme_fit/model/margin_model/linear_margin_model/margin_model_with_effect/margin_model_with_gcm_effect.py
@@ -0,0 +1,11 @@
+from extreme_fit.model.margin_model.linear_margin_model.margin_model_with_effect.abstract_margin_model_with_effect import \
+ AbstractMarginModelWithEffect
+from extreme_fit.model.margin_model.polynomial_margin_model.gev_altitudinal_models import StationaryAltitudinal
+
+
+class MarginModelWithGcmEffect(AbstractMarginModelWithEffect):
+ pass
+
+
+class StationaryAltitudinalWithGCMEffect(MarginModelWithGcmEffect, StationaryAltitudinal):
+ pass
diff --git a/extreme_fit/model/margin_model/polynomial_margin_model/gev_altitudinal_models.py b/extreme_fit/model/margin_model/polynomial_margin_model/gev_altitudinal_models.py
index 4ec8e20909dcad0a0677cb54bad519e69a867de4..57319c1051e4dfe90516af127ffacc0672861291 100644
--- a/extreme_fit/model/margin_model/polynomial_margin_model/gev_altitudinal_models.py
+++ b/extreme_fit/model/margin_model/polynomial_margin_model/gev_altitudinal_models.py
@@ -56,27 +56,8 @@ class AbstractAltitudinalModel(AbstractSpatioTemporalPolynomialModel):
s = '0'
else:
s = ','.join(l)
- # return '$ \\boldsymbol{ \\mathcal{M}_{%s} }$' % s
return '$ \\boldsymbol{%s}$' % s
-
- # @property
- # def name_str(self):
- # name = ''
- # for coordinate_name, idx in zip(['s', 't'], [self.coordinates.idx_x_coordinates, self.coordinates.idx_temporal_coordinates]):
- # name += coordinate_name
- # for param_name in GevParams.PARAM_NAMES:
- # name += self.dim_to_str_number(param_name, idx)
- # if isinstance(self, AbstractAddCrossTerm):
- # name += 'sxt'
- # for c in [AbstractAddCrossTermForLocation, AbstractAddCrossTermForScale, AbstractAddCrossTermForShape]:
- # if isinstance(self, c):
- # name += '1'
- # else:
- # name += '0'
- # return name
-
-
class StationaryAltitudinal(AbstractAltitudinalModel):
@property
diff --git a/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py b/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py
index bf53041dbfd38615ca988f9e9ec5143fd5a6207b..a75e81b0cc7e3bfb5221e430694a8ae48e0ea727 100644
--- a/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py
+++ b/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py
@@ -156,10 +156,11 @@ class VisualizerForProjectionEnsemble(object):
for ensemble_fit in self.ensemble_fits(IndependentEnsembleFit):
for gcm_rcm_couple in self.gcm_rcm_couples:
visualizer = ensemble_fit.gcm_rcm_couple_to_visualizer[gcm_rcm_couple]
- one_fold_fit = visualizer.massif_name_to_one_fold_fit[massif_name]
- coef = one_fold_fit.best_coef(param_name, 0, degree)
- altitude = visualizer.altitude_group.reference_altitude
- gcm_rcm_couple_to_data[gcm_rcm_couple].append((altitude, coef))
+ if massif_name in visualizer.massif_name_to_one_fold_fit:
+ one_fold_fit = visualizer.massif_name_to_one_fold_fit[massif_name]
+ coef = one_fold_fit.best_coef(param_name, 0, degree)
+ altitude = visualizer.altitude_group.reference_altitude
+ gcm_rcm_couple_to_data[gcm_rcm_couple].append((altitude, coef))
# Plot
ax = plt.gca()
for gcm_rcm_couple, data in gcm_rcm_couple_to_data.items():
diff --git a/projects/projected_extreme_snowfall/results/main_projections_ensemble.py b/projects/projected_extreme_snowfall/results/main_projections_ensemble.py
index 3de38f49dff14dff77e1f80d963fab3bf1136921..01b209111a8d57add86c500a062b87fd4cfbed72 100644
--- a/projects/projected_extreme_snowfall/results/main_projections_ensemble.py
+++ b/projects/projected_extreme_snowfall/results/main_projections_ensemble.py
@@ -41,7 +41,7 @@ def main():
study_class = AdamontSnowfall
ensemble_fit_classes = [IndependentEnsembleFit, TogetherEnsembleFit][1:]
temporal_covariate_for_fit = [TimeTemporalCovariate,
- AnomalyTemperatureWithSplineTemporalCovariate][0]
+ AnomalyTemperatureWithSplineTemporalCovariate][1]
set_seed_for_test()
AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
@@ -61,8 +61,8 @@ def main():
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
altitudes_list = altitudes_for_groups[:1]
else:
- massif_names = None
- altitudes_list = altitudes_for_groups[:]
+ massif_names = ['Vanoise']
+ altitudes_list = altitudes_for_groups[3:]
assert isinstance(gcm_rcm_couples, list)
diff --git a/test/test_extreme_trend/test_ensemble_fit.py b/test/test_extreme_trend/test_ensemble_fit.py
new file mode 100644
index 0000000000000000000000000000000000000000..beab3a9889379a60a5a79bf640143be02f16153b
--- /dev/null
+++ b/test/test_extreme_trend/test_ensemble_fit.py
@@ -0,0 +1,80 @@
+import unittest
+
+from extreme_data.meteo_france_data.adamont_data.adamont.adamont_safran import AdamontSnowfall
+from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario
+from extreme_data.meteo_france_data.scm_models_data.altitudes_studies import AltitudesStudies
+from extreme_fit.model.margin_model.linear_margin_model.margin_model_with_effect.margin_model_with_gcm_effect import \
+ StationaryAltitudinalWithGCMEffect
+from extreme_fit.model.margin_model.polynomial_margin_model.gev_altitudinal_models import StationaryAltitudinal
+from extreme_fit.model.margin_model.polynomial_margin_model.models_based_on_pariwise_analysis.gev_with_constant_shape_wrt_altitude import \
+ AltitudinalShapeConstantTimeLocationLinear, AltitudinalShapeConstantTimeScaleLinear, \
+ AltitudinalShapeConstantTimeLocScaleLinear
+from extreme_trend.ensemble_fit.together_ensemble_fit.together_ensemble_fit import TogetherEnsembleFit
+from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
+ TimeTemporalCovariate
+from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
+ AnomalyTemperatureWithSplineTemporalCovariate
+
+
+class TestEnsembleFit(unittest.TestCase):
+
+ def setUp(self) -> None:
+ super().setUp()
+ self.altitudes = [1200, 1500, 1800]
+ self.massif_names = ["Vanoise"]
+ study_class = AdamontSnowfall
+ gcm_rcm_couples = [('CNRM-CM5', 'ALADIN53'), ('EC-EARTH', 'CCLM4-8-17')]
+ scenario = AdamontScenario.rcp85
+ self.gcm_rcm_couple_to_altitude_studies = {
+ c: AltitudesStudies(study_class, self.altitudes,
+ gcm_rcm_couple=c, scenario=scenario) for c in gcm_rcm_couples
+ }
+
+ def test_basic_ensemble_together_fit(self):
+ model_classes = [StationaryAltitudinal,
+ AltitudinalShapeConstantTimeLocationLinear,
+ AltitudinalShapeConstantTimeScaleLinear,
+ AltitudinalShapeConstantTimeLocScaleLinear
+ ][:]
+
+ for temporal_covariate in [TimeTemporalCovariate,
+ AnomalyTemperatureWithSplineTemporalCovariate]:
+ ensemble_fit = TogetherEnsembleFit(massif_names=self.massif_names,
+ gcm_rcm_couple_to_altitude_studies=self.gcm_rcm_couple_to_altitude_studies,
+ models_classes=model_classes,
+ temporal_covariate_for_fit=temporal_covariate,
+ only_models_that_pass_goodness_of_fit_test=False)
+
+ _ = ensemble_fit.visualizer.massif_name_to_one_fold_fit[self.massif_names[0]].best_function_from_fit
+ self.assertTrue(True)
+
+ def test_ensembe_fit_with_effect(self):
+ model_classes = [StationaryAltitudinal,
+ StationaryAltitudinalWithGCMEffect][:1]
+
+ for temporal_covariate in [TimeTemporalCovariate,
+ AnomalyTemperatureWithSplineTemporalCovariate]:
+ ensemble_fit = TogetherEnsembleFit(massif_names=self.massif_names,
+ gcm_rcm_couple_to_altitude_studies=self.gcm_rcm_couple_to_altitude_studies,
+ models_classes=model_classes,
+ temporal_covariate_for_fit=temporal_covariate,
+ only_models_that_pass_goodness_of_fit_test=False)
+
+ model_class_to_estimator = ensemble_fit.visualizer.massif_name_to_one_fold_fit[self.massif_names[0]].model_class_to_estimator
+ model_class_to_expected_number_params = {
+ StationaryAltitudinal: 5,
+ StationaryAltitudinalWithGCMEffect: 6,
+ }
+ for model_class in model_classes:
+ expected = model_class_to_expected_number_params[model_class]
+ found = model_class_to_estimator[model_class].margin_model.nb_params
+ self.assertEqual(expected, found)
+
+ # _ = ensemble_fit.visualizer.massif_name_to_one_fold_fit[self.massif_names[0]].best_function_from_fit
+
+
+ self.assertTrue(True)
+
+
+if __name__ == '__main__':
+ unittest.main()