From 9341832a4c102d0d01015cc88d5ec25f216f01ae Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 14 Nov 2018 13:39:01 +0100
Subject: [PATCH] [R Model] transform gev2frech to a class method
---
extreme_estimator/R_model/abstract_model.py | 5 +++--
.../R_model/margin_model/abstract_margin_model.py | 5 +++--
extreme_estimator/estimator/full_estimator.py | 4 ++--
3 files changed, 8 insertions(+), 6 deletions(-)
diff --git a/extreme_estimator/R_model/abstract_model.py b/extreme_estimator/R_model/abstract_model.py
index 00673d98..304ca708 100644
--- a/extreme_estimator/R_model/abstract_model.py
+++ b/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
diff --git a/extreme_estimator/R_model/margin_model/abstract_margin_model.py b/extreme_estimator/R_model/margin_model/abstract_margin_model.py
index 644ef37d..25e59524 100644
--- a/extreme_estimator/R_model/margin_model/abstract_margin_model.py
+++ b/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)
diff --git a/extreme_estimator/estimator/full_estimator.py b/extreme_estimator/estimator/full_estimator.py
index cec7a3ce..3d31d97f 100644
--- a/extreme_estimator/estimator/full_estimator.py
+++ b/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
--
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