diff --git a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py index f6455310da7afc09b4d448aa4f2f7ca74692b7ca..591130ef3d6c7d24991a797d5931bd85bbd23ef5 100644 --- a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py +++ b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py @@ -66,7 +66,7 @@ class LinearMarginEstimator(AbstractMarginEstimator): def coordinates_for_nllh(self): return pd.concat([self.df_coordinates_spat, self.df_coordinates_temp], axis=1).values - @property + @cached_property def nllh(self): maxima_values = self.dataset.maxima_gev coordinate_values = self.coordinates_for_nllh @@ -118,7 +118,7 @@ class LinearMarginEstimator(AbstractMarginEstimator): @property def nb_params(self): - nb_params = self.margin_function_from_fit.nb_params + nb_params = self.margin_function_from_fit.nb_params_for_margin_function nb_params += self.margin_function_from_fit.nb_params_for_climate_effects if isinstance(self.margin_model, AbstractTemporalLinearMarginModel) and self.margin_model.is_gumbel_model: nb_params -= 1 diff --git a/extreme_fit/function/margin_function/abstract_margin_function.py b/extreme_fit/function/margin_function/abstract_margin_function.py index cd2e71c2013a5309ec41cd9866ef5e429bfccc5a..0bfc893b9c76de7390f240eca64529f9918d0940 100644 --- a/extreme_fit/function/margin_function/abstract_margin_function.py +++ b/extreme_fit/function/margin_function/abstract_margin_function.py @@ -56,7 +56,7 @@ class AbstractMarginFunction(AbstractFunction): raise NotImplementedError @property - def nb_params(self): + def nb_params_for_margin_function(self): raise NotImplementedError @property diff --git a/extreme_fit/function/margin_function/linear_margin_function.py b/extreme_fit/function/margin_function/linear_margin_function.py index 59065da1f82b8f9b590b4101f1a0e10eca84e106..315fd2786ad000073ea6f7ac186721b48a349267 100644 --- a/extreme_fit/function/margin_function/linear_margin_function.py +++ b/extreme_fit/function/margin_function/linear_margin_function.py @@ -50,7 +50,7 @@ class LinearMarginFunction(ParametricMarginFunction): return {v: k for k, v in cls.idx_to_coefficient_name(coordinates).items()} @property - def nb_params(self): + def nb_params_for_margin_function(self): return len(self.coef_dict) @property diff --git a/extreme_fit/function/margin_function/polynomial_margin_function.py b/extreme_fit/function/margin_function/polynomial_margin_function.py index f08ec0f91800f931c919482d7d28efb4a4bfdafe..1dbbedb09ed35fe2e45b4b56147e98e385d9c5c8 100644 --- a/extreme_fit/function/margin_function/polynomial_margin_function.py +++ b/extreme_fit/function/margin_function/polynomial_margin_function.py @@ -34,7 +34,7 @@ class PolynomialMarginFunction(LinearMarginFunction): return super().get_params(coordinate, is_transformed) @property - def nb_params(self): + def nb_params_for_margin_function(self): return sum([c.nb_params for c in self.param_name_to_coef.values()]) @classmethod diff --git a/extreme_fit/function/margin_function/spline_margin_function.py b/extreme_fit/function/margin_function/spline_margin_function.py index 917ee326c6ebbcfb2501caeba268ff6b382907a4..b86d5cc3bb9a2d062febbb0bd712290e7791e569 100644 --- a/extreme_fit/function/margin_function/spline_margin_function.py +++ b/extreme_fit/function/margin_function/spline_margin_function.py @@ -42,7 +42,7 @@ class SplineMarginFunction(LinearMarginFunction): return super().get_params(coordinate, is_transformed) @property - def nb_params(self): + def nb_params_for_margin_function(self): return sum([c.nb_params for c in self.param_name_to_coef.values()]) @classmethod diff --git a/extreme_trend/trend_test/abstract_gev_trend_test.py b/extreme_trend/trend_test/abstract_gev_trend_test.py index b60b2d8c7cc8e37d9b4fcbc56eee442bca47f2b2..fe84e69ae25a0fcc5ccbb65753cefe0ad71331c8 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.nb_params) + assert np.equal(self.total_number_of_parameters_for_unconstrained_model, self.unconstrained_estimator.nb_params_for_margin_function) 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