From cee0c1f79f1e9a4c44db664bbf8ec0eafcb30f43 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 15 Apr 2020 15:15:55 +0200
Subject: [PATCH] [contrasting project] move and rename TemporalMarginFitMethod
---
.../abstract_temporal_linear_margin_model.py | 30 ++++++++-----------
extreme_fit/model/margin_model/utils.py | 9 ++++++
2 files changed, 21 insertions(+), 18 deletions(-)
diff --git a/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py b/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py
index 36a7ab01..b7b198b9 100644
--- a/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py
+++ b/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py
@@ -6,7 +6,8 @@ import pandas as pd
from extreme_fit.distribution.exp_params import ExpParams
from extreme_fit.distribution.gev.gev_params import GevParams
from extreme_fit.model.margin_model.linear_margin_model.linear_margin_model import LinearMarginModel
-from extreme_fit.model.margin_model.utils import MarginFitMethod, fitmethod_to_str
+from extreme_fit.model.margin_model.utils import MarginFitMethod, fitmethod_to_str, FEVD_MARGIN_FIT_METHODS, \
+ FEVD_MARGIN_FIT_METHOD_TO_ARGUMENT_STR
from extreme_fit.model.result_from_model_fit.abstract_result_from_model_fit import AbstractResultFromModelFit
from extreme_fit.model.result_from_model_fit.result_from_extremes.result_from_bayesian_extremes import \
AbstractResultFromExtremes, ResultFromBayesianExtremes
@@ -47,13 +48,8 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
if self.params_class is GevParams:
if self.fit_method == MarginFitMethod.is_mev_gev_fit:
return self.ismev_gev_fit(x, df_coordinates_temp)
- elif self.fit_method == MarginFitMethod.extremes_fevd_bayesian:
- return self.extremes_fevd_bayesian_fit(x, df_coordinates_temp)
- elif self.fit_method in [MarginFitMethod.extremes_fevd_mle,
- MarginFitMethod.extremes_fevd_gmle,
- MarginFitMethod.extremes_fevd_l_moments,
- ]:
- return self.extremes_fevd_mle_related_fit(x, df_coordinates_temp)
+ elif self.fit_method in FEVD_MARGIN_FIT_METHODS:
+ return self.extremes_fevd_fit(x, df_coordinates_temp)
else:
raise NotImplementedError
elif self.params_class is ExpParams:
@@ -72,22 +68,20 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
# Gev fit with extRemes package
- def extremes_fevd_mle_related_fit(self, x, df_coordinates_temp) -> AbstractResultFromExtremes:
- if self.fit_method == MarginFitMethod.extremes_fevd_mle:
- method = "MLE"
- elif self.fit_method == MarginFitMethod.extremes_fevd_gmle:
- method = "GMLE"
- elif self.fit_method == MarginFitMethod.extremes_fevd_l_moments:
- method = "Lmoments"
- assert self.margin_function_start_fit.is_a_stationary_model
+ def extremes_fevd_fit(self, x, df_coordinates_temp) -> AbstractResultFromExtremes:
+ assert self.fit_method in FEVD_MARGIN_FIT_METHODS
+ if self.fit_method == MarginFitMethod.extremes_fevd_bayesian:
+ return self.extremes_fevd_bayesian_fit(x, df_coordinates_temp)
else:
- raise ValueError('wrong method')
- return self.run_fevd_fixed(df_coordinates_temp, method, x)
+ return self.run_fevd_fixed(df_coordinates_temp=df_coordinates_temp,
+ method=FEVD_MARGIN_FIT_METHOD_TO_ARGUMENT_STR[self.fit_method], x=x)
def extreme_fevd_mle_exp_fit(self, x, df_coordinates_temp):
return self.run_fevd_fixed(df_coordinates_temp, "Exponential", x)
def run_fevd_fixed(self, df_coordinates_temp, method, x):
+ if self.fit_method == MarginFitMethod.extremes_fevd_l_moments:
+ assert self.margin_function_start_fit.is_a_stationary_model
r_type_argument_kwargs, y = self.extreme_arguments(df_coordinates_temp)
res = safe_run_r_estimator(function=r('fevd_fixed'),
x=x,
diff --git a/extreme_fit/model/margin_model/utils.py b/extreme_fit/model/margin_model/utils.py
index d511d1ec..95763162 100644
--- a/extreme_fit/model/margin_model/utils.py
+++ b/extreme_fit/model/margin_model/utils.py
@@ -8,5 +8,14 @@ class MarginFitMethod(Enum):
extremes_fevd_gmle = 3
extremes_fevd_l_moments = 4
+
+FEVD_MARGIN_FIT_METHOD_TO_ARGUMENT_STR = {
+ MarginFitMethod.extremes_fevd_mle: "MLE",
+ MarginFitMethod.extremes_fevd_gmle: "GMLE",
+ MarginFitMethod.extremes_fevd_l_moments: "Lmoments",
+ MarginFitMethod.extremes_fevd_bayesian: "Bayesian"
+}
+FEVD_MARGIN_FIT_METHODS = set(FEVD_MARGIN_FIT_METHOD_TO_ARGUMENT_STR.keys())
+
def fitmethod_to_str(fit_method):
return str(fit_method).split('.')[-1]
--
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