diff --git a/extreme_fit/function/param_function/polynomial_coef.py b/extreme_fit/function/param_function/polynomial_coef.py
index 6a81f2249b289cd37d6367ef74bc322e1404a4e1..5a1da889739a90209275061632746e96f90e10cd 100644
--- a/extreme_fit/function/param_function/polynomial_coef.py
+++ b/extreme_fit/function/param_function/polynomial_coef.py
@@ -52,7 +52,6 @@ class PolynomialAllCoef(LinearCoef):
coordinates: AbstractCoordinates):
degree0 = coef_dict[cls.coef_template_str(param_name, coefficient_name=cls.INTERCEPT_NAME).format(1)]
list_dim_and_max_degree = dims
- j = 2
if len(list_dim_and_max_degree) == 0:
dim_to_polynomial_coef = None
intercept = degree0
@@ -61,8 +60,7 @@ class PolynomialAllCoef(LinearCoef):
dim_to_polynomial_coef = {}
for dim, max_degree in list_dim_and_max_degree:
coefficient_name = coordinates.coordinates_names[dim]
- if coefficient_name == AbstractCoordinates.COORDINATE_T:
- j = 1
+ j = 1 if coefficient_name == AbstractCoordinates.COORDINATE_T else 2
degree_to_coef = {0: degree0}
for degree in range(1, max_degree + 1):
coef_value = coef_dict[cls.coef_template_str(param_name, coefficient_name).format(j)]
diff --git a/extreme_fit/model/margin_model/polynomial_margin_model/altitudinal_models.py b/extreme_fit/model/margin_model/polynomial_margin_model/altitudinal_models.py
new file mode 100644
index 0000000000000000000000000000000000000000..7b2c68d1b906516b53989f1ab2cb1c44b8205906
--- /dev/null
+++ b/extreme_fit/model/margin_model/polynomial_margin_model/altitudinal_models.py
@@ -0,0 +1,48 @@
+from extreme_fit.distribution.gev.gev_params import GevParams
+from extreme_fit.model.margin_model.polynomial_margin_model.spatio_temporal_polynomial_model import \
+ AbstractSpatioTemporalPolynomialModel
+
+
+class StationaryAltitudinal(AbstractSpatioTemporalPolynomialModel):
+
+ def load_margin_function(self, param_name_to_dims=None):
+ return super().load_margin_function({
+ GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1)],
+ GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1)]
+ })
+
+
+class NonStationaryAltitudinalLocationLinear(AbstractSpatioTemporalPolynomialModel):
+
+ def load_margin_function(self, param_name_to_dims=None):
+ return super().load_margin_function({
+ GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+ GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1)]
+ })
+
+
+class NonStationaryAltitudinalLocationQuadratic(AbstractSpatioTemporalPolynomialModel):
+
+ def load_margin_function(self, param_name_to_dims=None):
+ return super().load_margin_function({
+ GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+ GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1)]
+ })
+
+
+class NonStationaryAltitudinalLocationLinearScaleLinear(AbstractSpatioTemporalPolynomialModel):
+
+ def load_margin_function(self, param_name_to_dims=None):
+ return super().load_margin_function({
+ GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+ GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+ })
+
+
+class NonStationaryAltitudinalLocationQuadraticScaleLinear(AbstractSpatioTemporalPolynomialModel):
+
+ def load_margin_function(self, param_name_to_dims=None):
+ return super().load_margin_function({
+ GevParams.LOC: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 2)],
+ GevParams.SCALE: [(self.coordinates.idx_x_coordinates, 1), (self.coordinates.idx_temporal_coordinates, 1)],
+ })
diff --git a/extreme_fit/model/margin_model/polynomial_margin_model/spatio_temporal_polynomial_model.py b/extreme_fit/model/margin_model/polynomial_margin_model/spatio_temporal_polynomial_model.py
index 4f9cde3d24d1b35d0030f7542b5b02757d44e81f..b862e2abf8d70f3cc8d9cd6ad32931f783fa6a2e 100644
--- a/extreme_fit/model/margin_model/polynomial_margin_model/spatio_temporal_polynomial_model.py
+++ b/extreme_fit/model/margin_model/polynomial_margin_model/spatio_temporal_polynomial_model.py
@@ -21,3 +21,12 @@ class NonStationaryLocationSpatioTemporalLinearityModel(AbstractSpatioTemporalPo
(self.coordinates.idx_temporal_coordinates, 1),
(self.coordinates.idx_x_coordinates, 1),
]})
+
+
+class NonStationaryLocationSpatioTemporalLinearityModel2(AbstractSpatioTemporalPolynomialModel):
+
+ def load_margin_function(self, param_name_to_dims=None):
+ return super().load_margin_function({GevParams.LOC: [
+ (self.coordinates.idx_temporal_coordinates, 2),
+ (self.coordinates.idx_x_coordinates, 1),
+ ]})
diff --git a/extreme_fit/model/margin_model/polynomial_margin_model/utils.py b/extreme_fit/model/margin_model/polynomial_margin_model/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..acd15190a3f0f7a81ce9bbfa296b1043180b0d49
--- /dev/null
+++ b/extreme_fit/model/margin_model/polynomial_margin_model/utils.py
@@ -0,0 +1,11 @@
+from extreme_fit.model.margin_model.polynomial_margin_model.altitudinal_models import StationaryAltitudinal, \
+ NonStationaryAltitudinalLocationLinear, NonStationaryAltitudinalLocationQuadratic, \
+ NonStationaryAltitudinalLocationLinearScaleLinear, NonStationaryAltitudinalLocationQuadraticScaleLinear
+
+ALTITUDINAL_MODELS = [
+ StationaryAltitudinal,
+ NonStationaryAltitudinalLocationLinear,
+ NonStationaryAltitudinalLocationQuadratic,
+ NonStationaryAltitudinalLocationLinearScaleLinear,
+ NonStationaryAltitudinalLocationQuadraticScaleLinear
+][:]
diff --git a/extreme_fit/model/result_from_model_fit/utils.py b/extreme_fit/model/result_from_model_fit/utils.py
index 844639a5ece8bd899ce61fddd88a90e413ec7132..35c0dada51ecd79401d54709810c133fbab01764 100644
--- a/extreme_fit/model/result_from_model_fit/utils.py
+++ b/extreme_fit/model/result_from_model_fit/utils.py
@@ -33,8 +33,9 @@ def get_margin_coef_ordered_dict(param_name_to_dims, mle_values, type_for_mle="G
coef_dict[coef_name] = mle_values[i]
i += 1
else:
- # We assume that time was the first parameter
- inverted_dims = dims[::-1]
+ # We found (thanks to the test) that time was the first parameter when len(param_name_to_dims) == 1
+ # otherwise time is the second parameter in the order of the mle parameters
+ inverted_dims = dims[::-1] if len(param_name_to_dims) == 1 else dims
for dim, max_degree in inverted_dims:
coordinate_name = dim_to_coordinate_name[dim]
coef_template = LinearCoef.coef_template_str(param_name, coordinate_name)
diff --git a/test/test_extreme_fit/test_estimator/test_gev_spatio_temporal_extremes_mle.py b/test/test_extreme_fit/test_estimator/test_gev_spatio_temporal_extremes_mle.py
index cba6e6f96298736bc55b8d9c99ec0daa2b46ff4c..7d336ecdaee4f749876fb1e1dd99718fe1ce9fa9 100644
--- a/test/test_extreme_fit/test_estimator/test_gev_spatio_temporal_extremes_mle.py
+++ b/test/test_extreme_fit/test_estimator/test_gev_spatio_temporal_extremes_mle.py
@@ -9,7 +9,8 @@ from extreme_fit.model.margin_model.polynomial_margin_model.polynomial_margin_mo
NonStationaryQuadraticLocationModel, \
NonStationaryQuadraticScaleModel, NonStationaryQuadraticLocationGumbelModel, NonStationaryQuadraticScaleGumbelModel
from extreme_fit.model.margin_model.polynomial_margin_model.spatio_temporal_polynomial_model import \
- NonStationaryLocationSpatioTemporalLinearityModel
+ NonStationaryLocationSpatioTemporalLinearityModel, NonStationaryLocationSpatioTemporalLinearityModel2
+from extreme_fit.model.margin_model.polynomial_margin_model.utils import ALTITUDINAL_MODELS
from extreme_trend.abstract_gev_trend_test import fitted_linear_margin_estimator
from extreme_fit.model.margin_model.utils import \
MarginFitMethod
@@ -44,13 +45,22 @@ class TestGevTemporalQuadraticExtremesMle(unittest.TestCase):
estimator = model_fit.estimator_fold_1
return estimator
- def test_location_spatio_temporal_linearity(self):
- estimator = self.get_estimator_fitted(NonStationaryLocationSpatioTemporalLinearityModel)
+ def common_test(self, model_class):
+ estimator = self.get_estimator_fitted(model_class)
# Assert that indicators are correctly computed
self.assertAlmostEqual(estimator.result_from_model_fit.nllh, estimator.nllh(split=estimator.train_split))
self.assertAlmostEqual(estimator.result_from_model_fit.aic, estimator.aic(split=estimator.train_split))
self.assertAlmostEqual(estimator.result_from_model_fit.bic, estimator.bic(split=estimator.train_split))
+ def test_location_spatio_temporal_models(self):
+ for model_class in [NonStationaryLocationSpatioTemporalLinearityModel,
+ NonStationaryLocationSpatioTemporalLinearityModel2]:
+ self.common_test(model_class)
+
+ def test_altitudinal_models(self):
+ for model_class in ALTITUDINAL_MODELS:
+ self.common_test(model_class)
+
if __name__ == '__main__':
unittest.main()