From f4639557bf56e0a4eff829157eb162d60df2481b Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 29 May 2019 09:40:26 +0200
Subject: [PATCH] [EXTREME ESTIMATOR][MAX STABLE] add test that check the
possibility to fit max stable with 3D coordinates. This is working with all
the max stable structure except Smith structure (see max_stable_fit.R for an
example of the returned error)
---
.../max_stable_model/max_stable_fit.R | 101 +++++++++++++++++-
.../abstract_spatial_coordinates.py | 2 -
.../test_max_stable_estimators.py | 48 ++++++++-
test/test_utils.py | 6 +-
4 files changed, 146 insertions(+), 11 deletions(-)
diff --git a/extreme_estimator/extreme_models/max_stable_model/max_stable_fit.R b/extreme_estimator/extreme_models/max_stable_model/max_stable_fit.R
index 74195512..9f7635cb 100644
--- a/extreme_estimator/extreme_models/max_stable_model/max_stable_fit.R
+++ b/extreme_estimator/extreme_models/max_stable_model/max_stable_fit.R
@@ -24,11 +24,103 @@ rmaxstab2D <- function (n.obs){
scale.form = scale ~ 1
shape.form = shape ~ 1
- namedlist = list(cov11 = 1.0, cov12 = 1.2, cov22 = 2.2, locCoeff1=1.0, locCoeff2=1.0, scaleCoeff1=1.0, shapeCoeff1=1.0)
+ namedlist = list(cov11 = 1.0, cov12 = 1.2, cov22 = 2.2, locCoeff1=1.0, locCoeff2=1.0, scaleCoeff1=2.0, shapeCoeff1=0.1)
res = fitmaxstab(data=data, coord=coord, cov.mod="gauss", start=namedlist, fit.marge=TRUE, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form)
print(res['fitted.values'])
}
+# rmaxstab with 3D data
+rmaxstab3Dimprovedgauss <- function (n.obs){
+ n.site = 2
+ coord_sample <- matrix(rnorm(2*n.site, sd = sqrt(.2)), ncol = 2)
+ colnames(coord_sample) = c("E", "N")
+
+ # Generate the data
+ data <- rmaxstab(n.obs, coord_sample, "gauss", cov11 = 100, cov12 = 25, cov22 = 220)
+ # data <- rmaxstab(n.obs, coord, "brown", range = 3, smooth = 0.5)
+ # data <- rmaxstab(n.obs, coord, "whitmat", nugget = 0.0, range = 3, smooth = 0.5)
+ # Fit back the data
+ # print(data)n
+ # res = fitmaxstab(data, coord, "gauss", fit.marge=FALSE, )
+ # res = fitmaxstab(data, coord, "brown")
+ # res = fitmaxstab(data, coord, "whitmat", start=)
+
+ coord_fit <- matrix(rnorm(3*n.site, sd = sqrt(.2)), ncol = 3)
+ colnames(coord_fit) = c("E", "N", "A")
+
+ print(class(coord_fit))
+ print(colnames(coord_fit))
+
+ loc.form = loc ~ N
+ scale.form = scale ~ 1
+ shape.form = shape ~ 1
+
+ namedlist = list(cov11 = 1.0, cov12 = 1.2, cov22 = 2.2, cov13 = 1.0, cov23 = 1.2, cov33 = 2.2, locCoeff1=1.0, locCoeff2=1.0, scaleCoeff1=2.0, shapeCoeff1=0.1)
+ res = fitmaxstab(data=data, coord=coord_fit, cov.mod="gauss", start=namedlist, fit.marge=TRUE, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form)
+ print(res['fitted.values'])
+}
+
+rmaxstab3Dimprovedbrown <- function (n.obs){
+ n.site = 2
+ coord_sample <- matrix(rnorm(2*n.site, sd = sqrt(.2)), ncol = 2)
+ colnames(coord_sample) = c("E", "N")
+
+ # Generate the data
+ data <- rmaxstab(n.obs, coord_sample, "gauss", cov11 = 100, cov12 = 25, cov22 = 220)
+ # data <- rmaxstab(n.obs, coord, "brown", range = 3, smooth = 0.5)
+ # data <- rmaxstab(n.obs, coord, "whitmat", nugget = 0.0, range = 3, smooth = 0.5)
+ # Fit back the data
+ # print(data)n
+ # res = fitmaxstab(data, coord, "gauss", fit.marge=FALSE, )
+ # res = fitmaxstab(data, coord, "brown")
+ # res = fitmaxstab(data, coord, "whitmat", start=)
+
+ coord_fit <- matrix(rnorm(3*n.site, sd = sqrt(.2)), ncol = 3)
+ colnames(coord_fit) = c("E", "N", "A")
+
+ print(class(coord_fit))
+ print(colnames(coord_fit))
+
+ loc.form = loc ~ N
+ scale.form = scale ~ 1
+ shape.form = shape ~ 1
+
+ # namedlist = list(cov11 = 1.0, cov12 = 1.2, cov22 = 2.2, cov13 = 1.0, cov23 = 1.2, cov33 = 2.2, locCoeff1=1.0, locCoeff2=1.0, scaleCoeff1=2.0, shapeCoeff1=0.1)
+ res = fitmaxstab(data=data, coord=coord_fit, cov.mod="brown", fit.marge=TRUE, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form)
+ print(res['fitted.values'])
+}
+
+rmaxstab3Dimprovedtpowexp <- function (n.obs){
+ n.site = 2
+ coord_sample <- matrix(rnorm(2*n.site, sd = sqrt(.2)), ncol = 2)
+ colnames(coord_sample) = c("E", "N")
+
+ # Generate the data
+ data <- rmaxstab(n.obs, coord_sample, "gauss", cov11 = 100, cov12 = 25, cov22 = 220)
+ # data <- rmaxstab(n.obs, coord, "brown", range = 3, smooth = 0.5)
+ # data <- rmaxstab(n.obs, coord, "whitmat", nugget = 0.0, range = 3, smooth = 0.5)
+ # Fit back the data
+ # print(data)n
+ # res = fitmaxstab(data, coord, "gauss", fit.marge=FALSE, )
+ # res = fitmaxstab(data, coord, "brown")
+ # res = fitmaxstab(data, coord, "whitmat", start=)
+
+ coord_fit <- matrix(rnorm(3*n.site, sd = sqrt(.2)), ncol = 3)
+ colnames(coord_fit) = c("E", "N", "A")
+
+ print(class(coord_fit))
+ print(colnames(coord_fit))
+
+ loc.form = loc ~ N
+ scale.form = scale ~ 1
+ shape.form = shape ~ 1
+
+ # namedlist = list(cov11 = 1.0, cov12 = 1.2, cov22 = 2.2, cov13 = 1.0, cov23 = 1.2, cov33 = 2.2, locCoeff1=1.0, locCoeff2=1.0, scaleCoeff1=2.0, shapeCoeff1=0.1)
+ res = fitmaxstab(data=data, coord=coord_fit, cov.mod="tpowexp", fit.marge=TRUE, loc.form=loc.form, scale.form=scale.form,shape.form=shape.form)
+ print(res['fitted.values'])
+}
+
+
# rmaxstab with 3D data
# rmaxstab3D <- function (n.obs){
@@ -106,10 +198,13 @@ rmaxstab1D <- function (n.obs){
call_main = !exists("python_wrapping")
if (call_main) {
set.seed(42)
- n.obs = 500
+ n.obs = 50
+ rmaxstab3Dimprovedgauss(n.obs)
+ # rmaxstab3Dimprovedbrown(n.obs)
+ # rmaxstab3Dimprovedtpowexp(n.obs)
# rmaxstab2D(n.obs)
# rmaxstab3D(n.obs)
- rmaxstab1D(n.obs)
+ # rmaxstab1D(n.obs)
# namedlist = list(cov11 = 1.0, cov12 = 1.2, cov22 = 2.2)
# res = fitmaxstab(data=data, coord=coord, cov.mod="gauss", start=namedlist)
diff --git a/spatio_temporal_dataset/coordinates/spatial_coordinates/abstract_spatial_coordinates.py b/spatio_temporal_dataset/coordinates/spatial_coordinates/abstract_spatial_coordinates.py
index bb27d6da..f6b3daec 100644
--- a/spatio_temporal_dataset/coordinates/spatial_coordinates/abstract_spatial_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/spatial_coordinates/abstract_spatial_coordinates.py
@@ -1,8 +1,6 @@
import pandas as pd
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
-from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.abstract_transformation import \
- AbstractTransformation
from spatio_temporal_dataset.slicer.spatial_slicer import SpatialSlicer
diff --git a/test/test_extreme_estimator/test_estimator/test_max_stable_estimators.py b/test/test_extreme_estimator/test_estimator/test_max_stable_estimators.py
index c8efd51c..6c7fa025 100644
--- a/test/test_extreme_estimator/test_estimator/test_max_stable_estimators.py
+++ b/test/test_extreme_estimator/test_estimator/test_max_stable_estimators.py
@@ -1,8 +1,11 @@
import unittest
+from extreme_estimator.extreme_models.utils import SafeRunException
+from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.uniform_normalization import \
+ BetweenZeroAndOneNormalization
from spatio_temporal_dataset.dataset.simulation_dataset import MaxStableDataset
from test.test_utils import load_test_max_stable_models, load_test_1D_and_2D_spatial_coordinates, \
- load_test_max_stable_estimators
+ load_test_max_stable_estimators, load_test_3D_spatial_coordinates
class TestMaxStableEstimators(unittest.TestCase):
@@ -13,22 +16,59 @@ class TestMaxStableEstimators(unittest.TestCase):
def setUp(self):
super().setUp()
self.coordinates = load_test_1D_and_2D_spatial_coordinates(nb_points=self.nb_points)
+
self.max_stable_models = load_test_max_stable_models()
def test_max_stable_estimators(self):
+ self.fit_max_stable_estimator_for_all_coordinates()
+ self.assertTrue(True)
+
+ def fit_max_stable_estimator_for_all_coordinates(self):
for coordinates in self.coordinates:
for max_stable_model in self.max_stable_models:
+ use_rmaxstab_with_2_coordinates = coordinates.nb_coordinates_spatial > 2
dataset = MaxStableDataset.from_sampling(nb_obs=self.nb_obs,
max_stable_model=max_stable_model,
- coordinates=coordinates)
-
+ coordinates=coordinates,
+ use_rmaxstab_with_2_coordinates=use_rmaxstab_with_2_coordinates)
for max_stable_estimator in load_test_max_stable_estimators(dataset, max_stable_model):
max_stable_estimator.fit()
if self.DISPLAY:
print(type(max_stable_model))
print(dataset.df_dataset.head())
print(max_stable_estimator.additional_information)
- self.assertTrue(True)
+
+
+class TestMaxStableEstimatorWorkingFor3DCoordinates(TestMaxStableEstimators):
+
+ def setUp(self):
+ super().setUp()
+ self.coordinates = load_test_3D_spatial_coordinates(nb_points=self.nb_points,
+ transformation_class=BetweenZeroAndOneNormalization)
+ # Select only the max stable structure that work with 3D coordinates
+ self.max_stable_models = load_test_max_stable_models()[1:]
+
+
+class TestMaxStableEstimatorGaussFor3DCoordinates(TestMaxStableEstimators):
+ """
+ See the fhe function rmaxstab3Dimprovedgauss in my file max_stable_fit.R
+ it returns the following error when we try to fit a 3D smipth process:
+
+ Error in nplk(p[1], p[2], p[3], p[4], p[5], p[6], p[7], p[8], p[9], p[10], :
+ objet 'C_smithdsgnmat3d' introuvable
+ Calls: source ... rmaxstab3Dimprovedgauss -> fitmaxstab -> smithform -> do.call -> nllh -> nplk
+ Exécution arrêtée
+ """
+
+ def setUp(self):
+ super().setUp()
+ self.coordinates = load_test_3D_spatial_coordinates(nb_points=self.nb_points,
+ transformation_class=BetweenZeroAndOneNormalization)
+ self.max_stable_models = load_test_max_stable_models()[:1]
+
+ def test_max_stable_estimators(self):
+ with self.assertRaises(SafeRunException):
+ self.fit_max_stable_estimator_for_all_coordinates()
if __name__ == '__main__':
diff --git a/test/test_utils.py b/test/test_utils.py
index 25596f3b..df8d68c3 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -16,6 +16,8 @@ from extreme_estimator.extreme_models.max_stable_model.max_stable_models import
Geometric, ExtremalT, ISchlather
from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall, Safran, SafranRainfall, \
SafranTemperature, SafranTotalPrecip
+from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
+ AbstractSpatialCoordinates
from spatio_temporal_dataset.coordinates.spatial_coordinates.alps_station_3D_coordinates import \
AlpsStation3DCoordinatesWithAnisotropy
from spatio_temporal_dataset.coordinates.spatial_coordinates.generated_spatial_coordinates import \
@@ -82,13 +84,13 @@ def load_test_spatial_coordinates(nb_points, coordinate_types, train_split_ratio
for coordinate_class in coordinate_types]
-def load_test_1D_and_2D_spatial_coordinates(nb_points, train_split_ratio=None, transformation_class=None):
+def load_test_1D_and_2D_spatial_coordinates(nb_points, train_split_ratio=None, transformation_class=None) -> List[AbstractSpatialCoordinates]:
return load_test_spatial_coordinates(nb_points, TEST_1D_AND_2D_SPATIAL_COORDINATES,
train_split_ratio=train_split_ratio,
transformation_class=transformation_class)
-def load_test_3D_spatial_coordinates(nb_points, transformation_class=None):
+def load_test_3D_spatial_coordinates(nb_points, transformation_class=None) -> List[AbstractSpatialCoordinates]:
return load_test_spatial_coordinates(nb_points, TEST_3D_SPATIAL_COORDINATES, transformation_class=transformation_class)
--
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