diff --git a/experiment/trend_analysis/non_stationary_trends.py b/experiment/trend_analysis/non_stationary_trends.py
index b3a5b920a09b7ac721497f694dbf707fa490a147..e1eecad912e836392c57448ea886427cd2819bd4 100644
--- a/experiment/trend_analysis/non_stationary_trends.py
+++ b/experiment/trend_analysis/non_stationary_trends.py
@@ -11,7 +11,6 @@ from extreme_estimator.estimator.full_estimator.abstract_full_estimator import \
from extreme_estimator.estimator.margin_estimator.abstract_margin_estimator import LinearMarginEstimator, \
AbstractMarginEstimator
from extreme_estimator.extreme_models.margin_model.linear_margin_model import \
- LinearAllParametersTwoFirstCoordinatesMarginModel, LinearAllTwoStatialCoordinatesLocationLinearMarginModel, \
LinearStationaryMarginModel, LinearNonStationaryLocationMarginModel
from extreme_estimator.extreme_models.margin_model.margin_function.linear_margin_function import LinearMarginFunction
from extreme_estimator.extreme_models.margin_model.temporal_linear_margin_model import StationaryStationModel, \
@@ -46,8 +45,7 @@ class AbstractNonStationaryTrendTest(object):
self._starting_point_to_estimator[starting_point] = estimator
return self._starting_point_to_estimator[starting_point]
- def load_estimator(self, starting_point) -> Union[
- AbstractFullEstimator, AbstractMarginEstimator]:
+ def load_estimator(self, starting_point) -> Union[AbstractFullEstimator, AbstractMarginEstimator]:
margin_model_class = self.stationary_margin_model_class if starting_point is None else self.non_stationary_margin_model_class
assert starting_point not in self._starting_point_to_estimator
margin_model = margin_model_class(coordinates=self.dataset.coordinates, starting_point=starting_point)
diff --git a/extreme_estimator/extreme_models/margin_model/linear_margin_model.py b/extreme_estimator/extreme_models/margin_model/linear_margin_model.py
index 7956be5c2c7546ac626b3495760bcf7b0cd7e999..1cf924def4a29307e88ee41cc8bbba007c289e95 100644
--- a/extreme_estimator/extreme_models/margin_model/linear_margin_model.py
+++ b/extreme_estimator/extreme_models/margin_model/linear_margin_model.py
@@ -118,26 +118,17 @@ class LinearAllParametersAllDimsMarginModel(LinearMarginModel):
GevParams.SCALE: self.coordinates.coordinates_dims})
-class LinearAllParametersTwoFirstCoordinatesMarginModel(LinearMarginModel):
+class LinearStationaryMarginModel(LinearMarginModel):
def load_margin_functions(self, margin_function_class: type = None, gev_param_name_to_dims=None):
- super().load_margin_functions({GevParams.SHAPE: [0, 1],
- GevParams.LOC: [0, 1],
- GevParams.SCALE: [0, 1]})
+ super().load_margin_functions({GevParams.SHAPE: self.coordinates.spatial_coordinates_dims,
+ GevParams.LOC: self.coordinates.spatial_coordinates_dims,
+ GevParams.SCALE: self.coordinates.spatial_coordinates_dims})
-class LinearAllTwoStatialCoordinatesLocationLinearMarginModel(LinearMarginModel):
+class LinearNonStationaryLocationMarginModel(LinearMarginModel):
def load_margin_functions(self, margin_function_class: type = None, gev_param_name_to_dims=None):
- super().load_margin_functions({GevParams.SHAPE: [0, 1],
- GevParams.LOC: [0, 1, 2],
- GevParams.SCALE: [0, 1]})
-
-
-# Some renaming that defines the stationary and non-stationary models of reference
-class LinearStationaryMarginModel(LinearAllParametersTwoFirstCoordinatesMarginModel):
- pass
-
-
-class LinearNonStationaryLocationMarginModel(LinearAllTwoStatialCoordinatesLocationLinearMarginModel):
- pass
+ super().load_margin_functions({GevParams.SHAPE: self.coordinates.spatial_coordinates_dims,
+ GevParams.LOC: self.coordinates.coordinates_dims,
+ GevParams.SCALE: self.coordinates.spatial_coordinates_dims})
diff --git a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
index ada3da81f6f2f3112dda56942902b07c2d1d90eb..7d9c2a7af6d1cd7ed4c0c2992664cae008054bdb 100644
--- a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
+++ b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
@@ -103,7 +103,7 @@ class AbstractMarginFunction(object):
def visualize_single_param(self, gev_value_name=GevParams.LOC, ax=None, show=True):
assert gev_value_name in GevParams.SUMMARY_NAMES
- nb_coordinates_spatial = self.coordinates.nb_coordinates_spatial
+ nb_coordinates_spatial = self.coordinates.nb_spatial_coordinates
has_temporal_coordinates = self.coordinates.has_temporal_coordinates
if nb_coordinates_spatial == 1 and not has_temporal_coordinates:
self.visualize_1D(gev_value_name, ax, show)
diff --git a/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py b/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
index ad975235f95926f6b46f6221a53f4e17beded1e5..ac760eb6ec0685a3e099b03276ebe1a53e3b7ec5 100644
--- a/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
+++ b/extreme_estimator/extreme_models/margin_model/margin_function/linear_margin_function.py
@@ -65,14 +65,14 @@ class LinearMarginFunction(ParametricMarginFunction):
for gev_param_name in GevParams.PARAM_NAMES:
linear_dims = self.gev_param_name_to_dims.get(gev_param_name, [])
# Load spatial form_dict (only if we have some spatial coordinates)
- if self.coordinates.coordinates_spatial_names:
- spatial_names = [name for name in self.coordinates.coordinates_spatial_names
+ if self.coordinates.has_spatial_coordinates:
+ spatial_names = [name for name in self.coordinates.spatial_coordinates_names
if self.coefficient_name_to_dim(self.coordinates)[name] in linear_dims]
spatial_form = self.gev_param_name_to_coef[gev_param_name].spatial_form_dict(spatial_names)
form_dict.update(spatial_form)
# Load temporal form dict (only if we have some temporal coordinates)
- if self.coordinates.coordinates_temporal_names:
- temporal_names = [name for name in self.coordinates.coordinates_temporal_names
+ if self.coordinates.has_temporal_coordinates:
+ temporal_names = [name for name in self.coordinates.temporal_coordinates_names
if self.coefficient_name_to_dim(self.coordinates)[name] in linear_dims]
temporal_form = self.gev_param_name_to_coef[gev_param_name].temporal_form_dict(temporal_names)
# Specifying a formula '~ 1' creates a bug in fitspatgev of SpatialExtreme R package
diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index 1f1dd4f67267d483bf2edd9cd32f29530958699d..a4135fadfec26fc6a7631bda3baf52be6bfb2703 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -167,7 +167,7 @@ class AbstractCoordinates(object):
@property
def coordinates_names(self) -> List[str]:
- return self.coordinates_spatial_names + self.coordinates_temporal_names
+ return self.spatial_coordinates_names + self.temporal_coordinates_names
@property
def nb_coordinates(self) -> int:
@@ -180,22 +180,26 @@ class AbstractCoordinates(object):
# Spatial attributes
@property
- def coordinates_spatial_names(self) -> List[str]:
+ def spatial_coordinates_dims(self):
+ return list(range(self.nb_spatial_coordinates))
+
+ @property
+ def spatial_coordinates_names(self) -> List[str]:
return [name for name in self.COORDINATE_SPATIAL_NAMES if name in self.df_all_coordinates.columns]
@property
- def nb_coordinates_spatial(self) -> int:
- return len(self.coordinates_spatial_names)
+ def nb_spatial_coordinates(self) -> int:
+ return len(self.spatial_coordinates_names)
@property
def has_spatial_coordinates(self) -> bool:
- return self.nb_coordinates_spatial > 0
+ return self.nb_spatial_coordinates > 0
def df_spatial_coordinates(self, split: Split = Split.all, transformed=True) -> pd.DataFrame:
- if self.nb_coordinates_spatial == 0:
+ if self.nb_spatial_coordinates == 0:
return pd.DataFrame()
else:
- return self.df_coordinates(split, transformed).loc[:, self.coordinates_spatial_names].drop_duplicates()
+ return self.df_coordinates(split, transformed).loc[:, self.spatial_coordinates_names].drop_duplicates()
@property
def nb_stations(self, split: Split = Split.all) -> int:
@@ -212,22 +216,28 @@ class AbstractCoordinates(object):
# Temporal attributes
@property
- def coordinates_temporal_names(self) -> List[str]:
+ def temporal_dims(self):
+ start = self.nb_spatial_coordinates
+ end = start + self.nb_temporal_coordinates
+ return list(range(start, end))
+
+ @property
+ def temporal_coordinates_names(self) -> List[str]:
return [self.COORDINATE_T] if self.COORDINATE_T in self.df_all_coordinates else []
@property
- def nb_coordinates_temporal(self) -> int:
- return len(self.coordinates_temporal_names)
+ def nb_temporal_coordinates(self) -> int:
+ return len(self.temporal_coordinates_names)
@property
def has_temporal_coordinates(self) -> bool:
- return self.nb_coordinates_temporal > 0
+ return self.nb_temporal_coordinates > 0
def df_temporal_coordinates(self, split: Split = Split.all, transformed=True) -> pd.DataFrame:
- if self.nb_coordinates_temporal == 0:
+ if self.nb_temporal_coordinates == 0:
return pd.DataFrame()
else:
- return self.df_coordinates(split, transformed=transformed).loc[:, self.coordinates_temporal_names] \
+ return self.df_coordinates(split, transformed=transformed).loc[:, self.temporal_coordinates_names] \
.drop_duplicates()
def df_temporal_coordinates_for_fit(self, split=Split.all, starting_point=None) -> pd.DataFrame:
@@ -297,27 +307,27 @@ class AbstractCoordinates(object):
return self.df_all_coordinates[self.COORDINATE_T].values.copy()
def visualize(self):
- if self.nb_coordinates_spatial == 1:
+ if self.nb_spatial_coordinates == 1:
self.visualization_1D()
- elif self.nb_coordinates_spatial == 2:
+ elif self.nb_spatial_coordinates == 2:
self.visualization_2D()
else:
self.visualization_3D()
def visualization_1D(self):
- assert self.nb_coordinates_spatial >= 1
+ assert self.nb_spatial_coordinates >= 1
x = self.x_coordinates
y = np.zeros(len(x))
plt.scatter(x, y)
plt.show()
def visualization_2D(self):
- assert self.nb_coordinates_spatial >= 2
+ assert self.nb_spatial_coordinates >= 2
plt.scatter(self.x_coordinates, self.y_coordinates)
plt.show()
def visualization_3D(self):
- assert self.nb_coordinates_spatial == 3
+ assert self.nb_spatial_coordinates == 3
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d') # type: Axes3D
ax.scatter(self.x_coordinates, self.y_coordinates, self.z_coordinates, marker='^')
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 6c7fa02574bfe9ca7f1d70915b6e3106e2e12a0c..8ba17afc9435306d014bb0a006f6fb314750a6dc 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
@@ -26,7 +26,7 @@ class TestMaxStableEstimators(unittest.TestCase):
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
+ use_rmaxstab_with_2_coordinates = coordinates.nb_spatial_coordinates > 2
dataset = MaxStableDataset.from_sampling(nb_obs=self.nb_obs,
max_stable_model=max_stable_model,
coordinates=coordinates,