From debd8cafd3eae21d9192bae38d305812c12dd8c9 Mon Sep 17 00:00:00 2001 From: Le Roux Erwan <erwan.le-roux@irstea.fr> Date: Fri, 9 Apr 2021 20:15:49 +0200 Subject: [PATCH] [projection snowfall] refactor nb_params. --- .../margin_model/linear_margin_model/linear_margin_model.py | 4 ---- extreme_trend/one_fold_fit/one_fold_fit.py | 2 +- extreme_trend/trend_test/abstract_gev_trend_test.py | 2 +- test/test_extreme_trend/test_ensemble_fit.py | 2 +- 4 files changed, 3 insertions(+), 7 deletions(-) diff --git a/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py b/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py index 90fb6963..6f30175e 100644 --- a/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py +++ b/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py @@ -35,10 +35,6 @@ class LinearMarginModel(ParametricMarginModel): param_name_and_dim_to_coef[(param_name, dim)] = default_slope return param_name_and_dim_to_coef - @property - def nb_params(self): - return self.margin_function.nb_params - def param_name_to_linear_coef(self, param_name_and_dim_to_coef): param_name_to_linear_coef = {} param_names = list(set([e[0] for e in param_name_and_dim_to_coef.keys()])) diff --git a/extreme_trend/one_fold_fit/one_fold_fit.py b/extreme_trend/one_fold_fit/one_fold_fit.py index 7fe04a0a..6faf8010 100644 --- a/extreme_trend/one_fold_fit/one_fold_fit.py +++ b/extreme_trend/one_fold_fit/one_fold_fit.py @@ -296,7 +296,7 @@ class OneFoldFit(object): @property def degree_freedom_chi2(self): - return self.best_estimator.margin_model.nb_params - self.stationary_estimator.margin_model.nb_params + return self.best_estimator.nb_params - self.stationary_estimator.nb_params @cached_property def is_significant(self) -> bool: diff --git a/extreme_trend/trend_test/abstract_gev_trend_test.py b/extreme_trend/trend_test/abstract_gev_trend_test.py index d3c33e61..8807a8a8 100644 --- a/extreme_trend/trend_test/abstract_gev_trend_test.py +++ b/extreme_trend/trend_test/abstract_gev_trend_test.py @@ -101,7 +101,7 @@ class AbstractGevTrendTest(object): @property def aic(self): aic = 2 * self.total_number_of_parameters_for_unconstrained_model + self.unconstrained_model_deviance - assert np.equal(self.total_number_of_parameters_for_unconstrained_model, self.unconstrained_estimator.margin_model.nb_params) + assert np.equal(self.total_number_of_parameters_for_unconstrained_model, self.unconstrained_estimator.nb_params) npt.assert_almost_equal(self.unconstrained_estimator.result_from_model_fit.aic, aic, decimal=5) npt.assert_almost_equal(self.unconstrained_estimator.aic(), aic, decimal=5) return aic diff --git a/test/test_extreme_trend/test_ensemble_fit.py b/test/test_extreme_trend/test_ensemble_fit.py index a393174a..4ef9d104 100644 --- a/test/test_extreme_trend/test_ensemble_fit.py +++ b/test/test_extreme_trend/test_ensemble_fit.py @@ -63,7 +63,7 @@ class TestEnsembleFit(unittest.TestCase): } 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 + found = model_class_to_estimator[model_class].nb_params self.assertEqual(expected, found) # _ = ensemble_fit.visualizer.massif_name_to_one_fold_fit[self.massif_names[0]].best_function_from_fit -- GitLab