From dbe4a717e11c937419c9a80e7fbf294d1f2a03be Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Fri, 9 Apr 2021 20:04:34 +0200
Subject: [PATCH] [projection snowfall] refactor nb_params. so that is it
associated to the margin_function rather than to the margin_model.
---
.../margin_estimator/abstract_margin_estimator.py | 13 +++++++++++--
.../margin_function/abstract_margin_function.py | 4 ++++
.../margin_function/linear_margin_function.py | 4 ++++
.../margin_function/polynomial_margin_function.py | 4 ++++
.../margin_function/spline_margin_function.py | 4 ++++
.../abstract_temporal_linear_margin_model.py | 4 ++++
.../linear_margin_model/linear_margin_model.py | 2 +-
.../temporal_linear_margin_models.py | 5 -----
.../gumbel_altitudinal_models.py | 5 -----
.../polynomial_margin_model.py | 4 ----
.../spline_margin_model/spline_margin_model.py | 4 ----
11 files changed, 32 insertions(+), 21 deletions(-)
diff --git a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
index 47aa7b4f..463778f8 100644
--- a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
+++ b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
@@ -7,6 +7,8 @@ from cached_property import cached_property
from extreme_fit.estimator.abstract_estimator import AbstractEstimator
from extreme_fit.estimator.utils import load_margin_function
+from extreme_fit.model.margin_model.linear_margin_model.abstract_temporal_linear_margin_model import \
+ AbstractTemporalLinearMarginModel
from extreme_fit.model.margin_model.linear_margin_model.linear_margin_model import LinearMarginModel
from extreme_fit.function.margin_function.linear_margin_function import LinearMarginFunction
from extreme_fit.model.margin_model.utils import MarginFitMethod
@@ -103,15 +105,22 @@ class LinearMarginEstimator(AbstractMarginEstimator):
return 2 * self.nllh(split=split)
def aic(self, split=Split.all):
- aic = 2 * self.margin_model.nb_params + 2 * self.nllh(split=split)
+ aic = 2 * self.nb_params + 2 * self.nllh(split=split)
npt.assert_almost_equal(self.result_from_model_fit.aic, aic, decimal=0)
return aic
def n(self, split=Split.all):
return len(self.dataset.maxima_gev(split=split))
+ @property
+ def nb_params(self):
+ nb_params = self.function_from_fit.nb_params
+ if isinstance(self.margin_model, AbstractTemporalLinearMarginModel) and self.margin_model.is_gumbel_model:
+ nb_params -= 1
+ return nb_params
+
def bic(self, split=Split.all):
- return np.log(self.n(split=split)) * self.margin_model.nb_params + 2 * self.nllh(split=split)
+ return np.log(self.n(split=split)) * self.nb_params + 2 * self.nllh(split=split)
def compute_nllh(coordinate_values, maxima_values, function_from_fit, maximum_from_obs=True, assertion_for_inf=True):
diff --git a/extreme_fit/function/margin_function/abstract_margin_function.py b/extreme_fit/function/margin_function/abstract_margin_function.py
index 8f3a7b14..e3e70aa1 100644
--- a/extreme_fit/function/margin_function/abstract_margin_function.py
+++ b/extreme_fit/function/margin_function/abstract_margin_function.py
@@ -57,6 +57,10 @@ class AbstractMarginFunction(AbstractFunction):
"""Main method that maps each coordinate to its distribution parameters"""
raise NotImplementedError
+ @property
+ def nb_params(self):
+ raise NotImplementedError
+
@property
def gev_value_name_to_serie(self) -> Dict[str, pd.Series]:
# Load the gev_params
diff --git a/extreme_fit/function/margin_function/linear_margin_function.py b/extreme_fit/function/margin_function/linear_margin_function.py
index d387341f..59065da1 100644
--- a/extreme_fit/function/margin_function/linear_margin_function.py
+++ b/extreme_fit/function/margin_function/linear_margin_function.py
@@ -49,6 +49,10 @@ class LinearMarginFunction(ParametricMarginFunction):
def coefficient_name_to_dim(cls, coordinates: AbstractCoordinates) -> Dict[int, str]:
return {v: k for k, v in cls.idx_to_coefficient_name(coordinates).items()}
+ @property
+ def nb_params(self):
+ return len(self.coef_dict)
+
@property
def coef_dict(self) -> Dict[str, float]:
coef_dict = {}
diff --git a/extreme_fit/function/margin_function/polynomial_margin_function.py b/extreme_fit/function/margin_function/polynomial_margin_function.py
index e7814ed7..5863802a 100644
--- a/extreme_fit/function/margin_function/polynomial_margin_function.py
+++ b/extreme_fit/function/margin_function/polynomial_margin_function.py
@@ -31,6 +31,10 @@ class PolynomialMarginFunction(LinearMarginFunction):
def get_params(self, coordinate: np.ndarray, is_transformed: bool = True) -> GevParams:
return super().get_params(coordinate, is_transformed)
+ @property
+ def nb_params(self):
+ return sum([c.nb_params for c in self.param_name_to_coef.values()])
+
@classmethod
def from_coef_dict(cls, coordinates: AbstractCoordinates, param_name_to_dims: Dict[str, List[Tuple[int, int]]],
coef_dict: Dict[str, float], starting_point: Union[None, int] = None, log_scale=None):
diff --git a/extreme_fit/function/margin_function/spline_margin_function.py b/extreme_fit/function/margin_function/spline_margin_function.py
index 5ac8a21e..7b6755bd 100644
--- a/extreme_fit/function/margin_function/spline_margin_function.py
+++ b/extreme_fit/function/margin_function/spline_margin_function.py
@@ -39,6 +39,10 @@ class SplineMarginFunction(LinearMarginFunction):
def get_params(self, coordinate: np.ndarray, is_transformed: bool = True) -> GevParams:
return super().get_params(coordinate, is_transformed)
+ @property
+ def nb_params(self):
+ return sum([c.nb_params for c in self.param_name_to_coef.values()])
+
@classmethod
def from_coef_dict(cls, coordinates: AbstractCoordinates, param_name_to_dims: Dict[str, List[Tuple[int, int]]],
coef_dict: Dict[str, float], starting_point: Union[None, int] = None, log_scale=None):
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 85506f5b..337073bf 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
@@ -169,3 +169,7 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
@property
def siglink(self):
return r('identity')
+
+ @property
+ def is_gumbel_model(self):
+ return self.type_for_mle == "Gumbel"
\ No newline at end of file
diff --git a/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py b/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py
index a8f5af99..90fb6963 100644
--- a/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py
+++ b/extreme_fit/model/margin_model/linear_margin_model/linear_margin_model.py
@@ -37,7 +37,7 @@ class LinearMarginModel(ParametricMarginModel):
@property
def nb_params(self):
- return len(self.margin_function.coef_dict)
+ return self.margin_function.nb_params
def param_name_to_linear_coef(self, param_name_and_dim_to_coef):
param_name_to_linear_coef = {}
diff --git a/extreme_fit/model/margin_model/linear_margin_model/temporal_linear_margin_models.py b/extreme_fit/model/margin_model/linear_margin_model/temporal_linear_margin_models.py
index fde5b9c6..08e3cdff 100644
--- a/extreme_fit/model/margin_model/linear_margin_model/temporal_linear_margin_models.py
+++ b/extreme_fit/model/margin_model/linear_margin_model/temporal_linear_margin_models.py
@@ -126,11 +126,6 @@ class GumbelTemporalModel(StationaryTemporalModel):
super().__init__(coordinates, params_user, starting_point, fit_method,
nb_iterations_for_bayesian_fit, params_initial_fit_bayesian, type_for_MLE="Gumbel")
- @property
- def nb_params(self):
- return super().nb_params - 1
-
-
class NonStationaryLocationGumbelModel(GumbelTemporalModel, NonStationaryLocationTemporalModel):
pass
diff --git a/extreme_fit/model/margin_model/polynomial_margin_model/gumbel_altitudinal_models.py b/extreme_fit/model/margin_model/polynomial_margin_model/gumbel_altitudinal_models.py
index e95056a3..0b2753d6 100644
--- a/extreme_fit/model/margin_model/polynomial_margin_model/gumbel_altitudinal_models.py
+++ b/extreme_fit/model/margin_model/polynomial_margin_model/gumbel_altitudinal_models.py
@@ -24,11 +24,6 @@ class AbstractGumbelAltitudinalModel(AbstractAltitudinalModel):
super().__init__(coordinates, params_user, starting_point, fit_method, nb_iterations_for_bayesian_fit,
params_initial_fit_bayesian, "Gumbel", params_class, max_degree)
- @property
- def nb_params(self):
- return super().nb_params - 1
-
-
class StationaryGumbelAltitudinal(AbstractGumbelAltitudinalModel, StationaryAltitudinal):
pass
diff --git a/extreme_fit/model/margin_model/polynomial_margin_model/polynomial_margin_model.py b/extreme_fit/model/margin_model/polynomial_margin_model/polynomial_margin_model.py
index 7357cf84..a4567548 100644
--- a/extreme_fit/model/margin_model/polynomial_margin_model/polynomial_margin_model.py
+++ b/extreme_fit/model/margin_model/polynomial_margin_model/polynomial_margin_model.py
@@ -23,10 +23,6 @@ class PolynomialMarginModel(AbstractTemporalLinearMarginModel):
params_initial_fit_bayesian, type_for_MLE, params_class, temporal_covariate_for_fit)
self.max_degree = max_degree
- @property
- def nb_params(self):
- return sum([c.nb_params for c in self.margin_function.param_name_to_coef.values()])
-
@cached_property
def margin_function(self) -> PolynomialMarginFunction:
return super().margin_function
diff --git a/extreme_fit/model/margin_model/spline_margin_model/spline_margin_model.py b/extreme_fit/model/margin_model/spline_margin_model/spline_margin_model.py
index d13e746e..15c439b6 100644
--- a/extreme_fit/model/margin_model/spline_margin_model/spline_margin_model.py
+++ b/extreme_fit/model/margin_model/spline_margin_model/spline_margin_model.py
@@ -23,10 +23,6 @@ class SplineMarginModel(AbstractTemporalLinearMarginModel):
params_initial_fit_bayesian, type_for_MLE, params_class, temporal_covariate_for_fit)
self.max_degree = max_degree
- @property
- def nb_params(self):
- return sum([c.nb_params for c in self.margin_function.param_name_to_coef.values()])
-
@cached_property
def margin_function(self) -> SplineMarginFunction:
return super().margin_function
--
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