[R Model] transform gev2frech to a class method

extreme_estimator/R_model/abstract_model.py

@@ -3,9 +3,10 @@ from extreme_estimator.R_model.utils import get_loaded_r
 
 class AbstractModel(object):
 
+    r = get_loaded_r()
+
     def __init__(self, params_start_fit=None, params_sample=None):
         self.default_params_start_fit = None
         self.default_params_sample = None
         self.user_params_start_fit = params_start_fit
-        self.user_params_sample = params_sample
-        self.r = get_loaded_r()
\ No newline at end of file
+        self.user_params_sample = params_sample
\ No newline at end of file

extreme_estimator/R_model/margin_model/abstract_margin_model.py

@@ -49,13 +49,14 @@ class AbstractMarginModel(AbstractModel):
             maxima_gev.append(x_gev)
         return np.array(maxima_gev)
 
-    def gev2frech(self, maxima_gev: np.ndarray, df_gev_params: pd.DataFrame):
+    @classmethod
+    def gev2frech(cls, maxima_gev: np.ndarray, df_gev_params: pd.DataFrame):
         assert len(maxima_gev) == len(df_gev_params)
         maxima_frech = []
         for x_gev, (_, s_gev_params) in zip(maxima_gev, df_gev_params.iterrows()):
             gev_params = dict(s_gev_params)
             gev2frech_param = {'emp': False}
-            x_frech = self.r.gev2frech(x_gev, **gev_params, **gev2frech_param)
+            x_frech = cls.r.gev2frech(x_gev, **gev_params, **gev2frech_param)
             maxima_frech.append(x_frech)
         return np.array(maxima_frech)
 

extreme_estimator/estimator/full_estimator.py

@@ -23,8 +23,8 @@ class SmoothMarginalsThenUnitaryMsp(AbstractFullEstimator):
         # Estimate the margin parameters
         self.margin_estimator.fit()
         # Compute the maxima_frech
-        maxima_frech = self.margin_estimator.margin_model.gev2frech(maxima_gev=self.dataset.maxima_gev,
-                                                                    df_gev_params=self.margin_estimator.df_gev_params)
+        maxima_frech = AbstractMarginModel.gev2frech(maxima_gev=self.dataset.maxima_gev,
+                                                     df_gev_params=self.margin_estimator.df_gev_params)
         # Update maxima frech field through the dataset object
         self.dataset.maxima_frech = maxima_frech
         # Estimate the max stable parameters