From ce5ac52b75635561df90f067efeb986775a3004c Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 18 Dec 2019 15:35:55 +0100
Subject: [PATCH] [Temporal fit] add gmle fit method in for
temporal_linear_margin_model
---
.../abstract_temporal_linear_margin_model.py | 15 +++++++++----
.../test_model/test_confidence_interval.py | 21 ++++++++++++++++---
2 files changed, 29 insertions(+), 7 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 08700dfa..94011d95 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
@@ -18,6 +18,7 @@ class TemporalMarginFitMethod(Enum):
is_mev_gev_fit = 0
extremes_fevd_bayesian = 1
extremes_fevd_mle = 2
+ extremes_fevd_gmle = 3
class AbstractTemporalLinearMarginModel(LinearMarginModel):
@@ -42,8 +43,8 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
return self.ismev_gev_fit(x, df_coordinates_temp)
if self.fit_method == TemporalMarginFitMethod.extremes_fevd_bayesian:
return self.extremes_fevd_bayesian_fit(x, df_coordinates_temp)
- if self.fit_method == TemporalMarginFitMethod.extremes_fevd_mle:
- return self.extremes_fevd_mle_fit(x, df_coordinates_temp)
+ if self.fit_method in [TemporalMarginFitMethod.extremes_fevd_mle, TemporalMarginFitMethod.extremes_fevd_gmle]:
+ return self.extremes_fevd_mle_related_fit(x, df_coordinates_temp)
# Gev Fit with isMev package
@@ -56,13 +57,19 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
# Gev fit with extRemes package
- def extremes_fevd_mle_fit(self, x, df_coordinates_temp) -> AbstractResultFromExtremes:
+ def extremes_fevd_mle_related_fit(self, x, df_coordinates_temp) -> AbstractResultFromExtremes:
r_type_argument_kwargs, y = self.extreme_arguments(df_coordinates_temp)
+ if self.fit_method == TemporalMarginFitMethod.extremes_fevd_mle:
+ method = "MLE"
+ elif self.fit_method == TemporalMarginFitMethod.extremes_fevd_gmle:
+ method = "GMLE"
+ else:
+ raise ValueError('wrong method')
res = safe_run_r_estimator(function=r('fevd_fixed'),
x=x,
data=y,
type=self.type_for_mle,
- method="MLE",
+ method=method,
**r_type_argument_kwargs
)
return ResultFromMleExtremes(res, self.margin_function_start_fit.gev_param_name_to_dims,
diff --git a/test/test_extreme_fit/test_model/test_confidence_interval.py b/test/test_extreme_fit/test_model/test_confidence_interval.py
index 6922b113..0f52b44d 100644
--- a/test/test_extreme_fit/test_model/test_confidence_interval.py
+++ b/test/test_extreme_fit/test_model/test_confidence_interval.py
@@ -78,7 +78,7 @@ class TestConfidenceInterval(unittest.TestCase):
self.ci_method = ConfidenceIntervalMethodFromExtremes.ci_bayes
self.model_class_to_triplet = self.bayesian_ci
- def test_ci_normal(self):
+ def test_ci_normal_mle(self):
self.fit_method = TemporalMarginFitMethod.extremes_fevd_mle
self.ci_method = ConfidenceIntervalMethodFromExtremes.ci_mle
self.model_class_to_triplet = {
@@ -89,6 +89,17 @@ class TestConfidenceInterval(unittest.TestCase):
NonStationaryLocationAndScaleGumbelModel: (6.0605675256893, 10.512751341145462, 14.964935156601623),
}
+ def test_ci_normal_gmle(self):
+ self.fit_method = TemporalMarginFitMethod.extremes_fevd_gmle
+ self.ci_method = ConfidenceIntervalMethodFromExtremes.ci_mle
+ self.model_class_to_triplet = {
+ # Test only for the GEV cases (for the Gumbel cases results are just the same, since there is no shape parameter)
+ StationaryTemporalModel: (4.178088363735904, 15.27540259902303, 26.372716834310154),
+ NonStationaryLocationTemporalModel: (-6.716723409668982, 4.168288167650933, 15.053299744970847),
+ NonStationaryLocationAndScaleTemporalModel: (-12.226312466874123, 5.680769391219823, 23.58785124931377),
+ }
+
+
def test_ci_boot(self):
self.fit_method = TemporalMarginFitMethod.extremes_fevd_mle
self.ci_method = ConfidenceIntervalMethodFromExtremes.ci_boot
@@ -113,7 +124,7 @@ class TestConfidenceInterval(unittest.TestCase):
eurocode_ci = self.compute_eurocode_ci(model_class)
found_triplet = eurocode_ci.triplet
for a, b in zip(expected_triplet, found_triplet):
- self.assertAlmostEqual(a, b, msg="{} \n{}".format(model_class, found_triplet))
+ self.assertAlmostEqual(a, b, msg="\n{} \nfound_triplet: {}".format(model_class, found_triplet))
class TestConfidenceIntervalModifiedCoordinates(TestConfidenceInterval):
@@ -136,7 +147,11 @@ class TestConfidenceIntervalModifiedCoordinates(TestConfidenceInterval):
def test_ci_bayes(self):
super().test_ci_bayes()
- def test_ci_normal(self):
+ def test_ci_normal_mle(self):
+ self.model_class_to_triplet = {}
+ self.assertTrue(True)
+
+ def test_ci_normal_gmle(self):
self.model_class_to_triplet = {}
self.assertTrue(True)
--
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