diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index 5ced1941e489870e84b4a19b7a4978b51ea8b173..1a22f3961ea2805e47c5d891c9462004ed9cc6a5 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -215,6 +215,9 @@ class AbstractCoordinates(object):
def spatio_temporal_shape(self, split: Split.all) -> Tuple[int, int]:
return len(self.df_spatial_coordinates(split)), len(self.df_temporal_coordinates(split))
+ def ind_of_df_all_coordinates(self, coordinate_name, value):
+ return self.df_all_coordinates.loc[:, coordinate_name] == value
+
# Visualization
@property
diff --git a/spatio_temporal_dataset/dataset/abstract_dataset.py b/spatio_temporal_dataset/dataset/abstract_dataset.py
index 7370746e604e441dbad855812f0fbd885327e07b..1b2996c8df6f9a71413150727c1d84c0e2368b71 100644
--- a/spatio_temporal_dataset/dataset/abstract_dataset.py
+++ b/spatio_temporal_dataset/dataset/abstract_dataset.py
@@ -56,8 +56,9 @@ class AbstractDataset(object):
def transform_maxima_for_spatial_extreme_package(self, maxima_function, split) -> np.ndarray:
array = maxima_function(split)
if self.coordinates.has_spatio_temporal_coordinates:
- array = array.reshape(self.coordinates.spatio_temporal_shape(split))
- return np.transpose(array)
+ return array.reshape(self.coordinates.spatio_temporal_shape(split)[::-1])
+ else:
+ return np.transpose(array)
def maxima_gev_for_spatial_extremes_package(self, split: Split = Split.all) -> np.ndarray:
return self.transform_maxima_for_spatial_extreme_package(self.maxima_gev, split)
@@ -105,7 +106,7 @@ class AbstractDataset(object):
# Special methods
def __str__(self) -> str:
- return 'coordinates: {}\nobservations: {}'.format(self.coordinates.__str__(), self.observations.__str__())
+ return 'coordinates:\n{}\nobservations:\n{}'.format(self.coordinates.__str__(), self.observations.__str__())
def get_subset_dataset(dataset: AbstractDataset, subset_id) -> AbstractDataset:
diff --git a/test/test_extreme_estimator/test_extreme_models/test_margin_temporal.py b/test/test_extreme_estimator/test_extreme_models/test_margin_temporal.py
index 4107e4b9234de11fcdeb4262e32aee34e4f450b1..a533903e721490d7c3fb8f11461917df4385b93b 100644
--- a/test/test_extreme_estimator/test_extreme_models/test_margin_temporal.py
+++ b/test/test_extreme_estimator/test_extreme_models/test_margin_temporal.py
@@ -31,10 +31,10 @@ class TestMarginTemporal(unittest.TestCase):
self.nb_obs = 1
# Load some 2D spatial coordinates
self.coordinates = load_test_spatiotemporal_coordinates(nb_steps=self.nb_steps, nb_points=self.nb_points)[1]
- smooth_margin_model = LinearNonStationaryLocationMarginModel(coordinates=self.coordinates,
- starting_point=2)
+ self.smooth_margin_model = LinearNonStationaryLocationMarginModel(coordinates=self.coordinates,
+ starting_point=2)
self.dataset = MarginDataset.from_sampling(nb_obs=self.nb_obs,
- margin_model=smooth_margin_model,
+ margin_model=self.smooth_margin_model,
coordinates=self.coordinates)
def test_margin_fit_stationary(self):
@@ -42,7 +42,7 @@ class TestMarginTemporal(unittest.TestCase):
margin_model = LinearStationaryMarginModel(self.coordinates)
estimator = LinearMarginEstimator(self.dataset, margin_model)
estimator.fit()
- ref = {'loc': 1.3403346591679877, 'scale': 1.054867229157924, 'shape': 0.713700960727747}
+ ref = {'loc': 1.3456595684773085, 'scale': 1.090369430386199, 'shape': 0.6845422250749476}
for year in range(1, 3):
coordinate = np.array([0.0, 0.0, year])
mle_params_estimated = estimator.margin_function_fitted.get_gev_params(coordinate).to_dict()
@@ -65,8 +65,11 @@ class TestMarginTemporal(unittest.TestCase):
def test_margin_fit_nonstationary_with_start_point(self):
# Create estimator
estimator = self.fit_non_stationary_estimator(starting_point=2)
- print(estimator.margin_function_fitted.mu1_temporal_trend)
+ # By default, estimator find the good margin
self.assertNotEqual(estimator.margin_function_fitted.mu1_temporal_trend, 0.0)
+ self.assertAlmostEqual(estimator.margin_function_fitted.mu1_temporal_trend,
+ self.smooth_margin_model.margin_function_sample.mu1_temporal_trend,
+ places=3)
# Checks starting point parameter are well passed
self.assertEqual(2, estimator.margin_function_fitted.starting_point)
# Checks that parameters returned are indeed different
diff --git a/test/test_spatio_temporal_dataset/test_dataset.py b/test/test_spatio_temporal_dataset/test_dataset.py
index cefdced8fdaebfe5d25b9de16d7173ec35264bec..3c97f370ca2df967a953b0dd679f2778d643cd14 100644
--- a/test/test_spatio_temporal_dataset/test_dataset.py
+++ b/test/test_spatio_temporal_dataset/test_dataset.py
@@ -1,11 +1,15 @@
-from rpy2.rinterface import RRuntimeError
import unittest
from itertools import product
-from spatio_temporal_dataset.dataset.simulation_dataset import MaxStableDataset
-from test.test_utils import load_test_max_stable_models, load_test_spatial_coordinates, \
- load_test_3D_spatial_coordinates, \
- load_test_1D_and_2D_spatial_coordinates
+import numpy as np
+from rpy2.rinterface import RRuntimeError
+
+from extreme_estimator.extreme_models.margin_model.linear_margin_model import LinearNonStationaryLocationMarginModel
+from extreme_estimator.extreme_models.utils import set_seed_for_test
+from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
+from spatio_temporal_dataset.dataset.simulation_dataset import MaxStableDataset, MarginDataset
+from test.test_utils import load_test_max_stable_models, load_test_3D_spatial_coordinates, \
+ load_test_1D_and_2D_spatial_coordinates, load_test_spatiotemporal_coordinates
class TestDataset(unittest.TestCase):
@@ -32,5 +36,43 @@ class TestDataset(unittest.TestCase):
coordinates=coordinates)
+class TestSpatioTemporalDataset(unittest.TestCase):
+ nb_obs = 2
+ nb_points = 3
+ nb_steps = 2
+
+ def setUp(self) -> None:
+ set_seed_for_test(seed=42)
+ self.coordinates = load_test_spatiotemporal_coordinates(nb_steps=self.nb_steps, nb_points=self.nb_points)[1]
+
+ def load_dataset(self, nb_obs):
+ smooth_margin_model = LinearNonStationaryLocationMarginModel(coordinates=self.coordinates,
+ starting_point=1)
+ self.dataset = MarginDataset.from_sampling(nb_obs=nb_obs,
+ margin_model=smooth_margin_model,
+ coordinates=self.coordinates)
+
+ def test_spatio_temporal_array(self):
+ self.load_dataset(nb_obs=1)
+
+ # Load observation for time 0
+ ind_time_0 = self.dataset.coordinates.ind_of_df_all_coordinates(coordinate_name=AbstractCoordinates.COORDINATE_T,
+ value=0)
+ observation_at_time_0_v1 = self.dataset.observations.df_maxima_gev.loc[ind_time_0].values.flatten()
+
+ # Load observation correspond to time 0
+ maxima_gev = self.dataset.maxima_gev_for_spatial_extremes_package()
+ maxima_gev = np.transpose(maxima_gev)
+ self.assertEqual(maxima_gev.shape, (3, 2))
+ observation_at_time_0_v2 = maxima_gev[:, 0]
+ equality = np.equal(observation_at_time_0_v1, observation_at_time_0_v2).all()
+ self.assertTrue(equality, msg='v1={} is different from v2={}'.format(observation_at_time_0_v1,
+ observation_at_time_0_v2))
+
+ def test_spatio_temporal_case_to_resolve(self):
+ self.load_dataset(nb_obs=2)
+ print(self.dataset.maxima_gev_for_spatial_extremes_package())
+
+
if __name__ == '__main__':
unittest.main()