diff --git a/extreme_fit/function/abstract_function.py b/extreme_fit/function/abstract_function.py
index e563c3d0ddd0e6107f6ecbceeabad4d0bce2dffe..4a337b0a0bdb4d30bb05e42e9a445fd1bac6ce8b 100644
--- a/extreme_fit/function/abstract_function.py
+++ b/extreme_fit/function/abstract_function.py
@@ -1,3 +1,5 @@
+import numpy as np
+
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
@@ -6,3 +8,5 @@ class AbstractFunction(object):
def __init__(self, coordinates: AbstractCoordinates):
self.coordinates = coordinates
+ def transform(self, coordinate: np.ndarray) -> np.ndarray:
+ return self.coordinates.transformation.transform_array(coordinate)
diff --git a/extreme_fit/function/abstract_quantile_function.py b/extreme_fit/function/abstract_quantile_function.py
index d86b85550e337dfae006db3adbeb73e67924687c..e1f4b9f4d7650e7390d40b37fa231c38fcf8514e 100644
--- a/extreme_fit/function/abstract_quantile_function.py
+++ b/extreme_fit/function/abstract_quantile_function.py
@@ -10,7 +10,11 @@ from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoo
class AbstractQuantileFunction(AbstractFunction):
- def get_quantile(self, coordinate: np.ndarray) -> float:
+ def get_quantile(self, coordinate: np.ndarray, is_transformed: bool = True) -> float:
+ transformed_coordinate = coordinate if is_transformed else self.transform(coordinate)
+ return self._get_quantile(transformed_coordinate)
+
+ def _get_quantile(self, coordinate: np.ndarray):
raise NotImplementedError
def visualize(self, show=True):
@@ -43,7 +47,7 @@ class QuantileFunctionFromParamFunction(AbstractQuantileFunction):
super().__init__(coordinates)
self.param_function = param_function
- def get_quantile(self, coordinate: np.ndarray) -> float:
+ def _get_quantile(self, coordinate: np.ndarray) -> float:
return self.param_function.get_param_value(coordinate)
@@ -54,6 +58,6 @@ class QuantileFunctionFromMarginFunction(AbstractQuantileFunction):
self.margin_function = margin_function
self.quantile = quantile
- def get_quantile(self, coordinate: np.ndarray) -> float:
+ def _get_quantile(self, coordinate: np.ndarray) -> float:
gev_params = self.margin_function.get_gev_params(coordinate)
return gev_params.quantile(self.quantile)
diff --git a/extreme_fit/function/margin_function/independent_margin_function.py b/extreme_fit/function/margin_function/independent_margin_function.py
index ab8f7917edd1fc25c9b1df7719e9c9abf225f9d0..ccb6dba83812a9265443acce3c0e90e49c72ab7a 100644
--- a/extreme_fit/function/margin_function/independent_margin_function.py
+++ b/extreme_fit/function/margin_function/independent_margin_function.py
@@ -32,8 +32,7 @@ class IndependentMarginFunction(AbstractMarginFunction):
gev_params[gev_param_name] = param_function.get_param_value(transformed_coordinate)
return GevParams.from_dict(gev_params)
- def transform(self, coordinate: np.ndarray) -> np.ndarray:
- return self.coordinates.transformation.transform_array(coordinate)
+
diff --git a/projects/quantile_regression_vs_evt/AbstractSimulation.py b/projects/quantile_regression_vs_evt/AbstractSimulation.py
index a757e77e3ffc39f07537ed8df213a70d0a045021..bb35b5184f6b3a85fbcaeebcb5d6367be0b7b0f7 100644
--- a/projects/quantile_regression_vs_evt/AbstractSimulation.py
+++ b/projects/quantile_regression_vs_evt/AbstractSimulation.py
@@ -16,16 +16,12 @@ from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoo
from spatio_temporal_dataset.coordinates.temporal_coordinates.generated_temporal_coordinates import \
ConsecutiveTemporalCoordinates
from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.abstract_transformation import \
- CenteredScaledNormalization, IdentityTransformation
+ CenteredScaledNormalization
from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
from spatio_temporal_dataset.spatio_temporal_observations.abstract_spatio_temporal_observations import \
AbstractSpatioTemporalObservations
-class Coordinates(object):
- pass
-
-
class AbstractSimulation(object):
def __init__(self, nb_time_series, quantile, time_series_lengths=None, multiprocessing=False,
@@ -41,31 +37,31 @@ class AbstractSimulation(object):
raise NotImplementedError
@cached_property
- def time_serie_length_to_observation_list(self) -> Dict[int, List[AbstractSpatioTemporalObservations]]:
+ def time_series_length_to_observation_list(self) -> Dict[int, List[AbstractSpatioTemporalObservations]]:
d = OrderedDict()
for length in self.time_series_lengths:
d[length] = self.generate_all_observation(self.nb_time_series, length)
return d
@cached_property
- def time_serie_length_to_coordinates(self) -> Dict[int, AbstractCoordinates]:
+ def time_series_length_to_coordinates(self) -> Dict[int, AbstractCoordinates]:
d = OrderedDict()
for length in self.time_series_lengths:
- d[length] = ConsecutiveTemporalCoordinates.from_nb_temporal_steps(length,
- transformation_class=self.transformation_class)
+ d[length] = ConsecutiveTemporalCoordinates.\
+ from_nb_temporal_steps(length, transformation_class=self.transformation_class)
return d
@cached_property
- def model_class_to_time_serie_length_to_estimator_fitted(self):
+ def model_class_to_time_series_length_to_estimators(self):
d = OrderedDict()
for model_class in self.models_classes:
d_sub = OrderedDict()
- for time_serie_length, observation_list in self.time_serie_length_to_observation_list.items():
- coordinates = self.time_serie_length_to_coordinates[time_serie_length]
- estimators_fitted = []
+ for time_series_length, observation_list in self.time_series_length_to_observation_list.items():
+ coordinates = self.time_series_length_to_coordinates[time_series_length]
+ estimators = []
for observations in observation_list:
- estimators_fitted.append(self.get_fitted_quantile_estimator(model_class, observations, coordinates))
- d_sub[time_serie_length] = estimators_fitted
+ estimators.append(self.get_fitted_quantile_estimator(model_class, observations, coordinates))
+ d_sub[time_series_length] = estimators
d[model_class] = d_sub
return d
@@ -83,7 +79,7 @@ class AbstractSimulation(object):
@cached_property
def model_class_to_error_last_year_quantile(self):
d = OrderedDict()
- for model_class, d_sub in self.model_class_to_time_serie_length_to_estimator_fitted.items():
+ for model_class, d_sub in self.model_class_to_time_series_length_to_estimators.items():
length_to_error_values = OrderedDict()
for length, estimators_fitted in d_sub.items():
errors = self.compute_errors(length, estimators_fitted)
diff --git a/projects/quantile_regression_vs_evt/GevSimulation.py b/projects/quantile_regression_vs_evt/GevSimulation.py
index 62109e0ed9e5fc6d562e32c1cb2023da27687750..a1dc5697ecd0fd3ed91d1c6e6cba312f1b1235e7 100644
--- a/projects/quantile_regression_vs_evt/GevSimulation.py
+++ b/projects/quantile_regression_vs_evt/GevSimulation.py
@@ -23,7 +23,7 @@ class GevSimulation(AbstractSimulation):
def time_series_lengths_to_margin_model(self) -> Dict[int, AbstractMarginModel]:
d = OrderedDict()
for length in self.time_series_lengths:
- coordinates = self.time_serie_length_to_coordinates[length]
+ coordinates = self.time_series_length_to_coordinates[length]
d[length] = self.create_model(coordinates)
return d
@@ -31,13 +31,13 @@ class GevSimulation(AbstractSimulation):
raise NotImplementedError
def generate_all_observation(self, nb_time_series, length) -> List[AbstractSpatioTemporalObservations]:
- coordinates = self.time_serie_length_to_coordinates[length]
+ coordinates = self.time_series_length_to_coordinates[length]
margin_model = self.time_series_lengths_to_margin_model[length]
return [MarginAnnualMaxima.from_sampling(nb_obs=1, coordinates=coordinates, margin_model=margin_model)
for _ in range(nb_time_series)]
def compute_errors(self, length: int, estimators: List[AbstractQuantileEstimator]):
- coordinates = self.time_serie_length_to_coordinates[length]
+ coordinates = self.time_series_length_to_coordinates[length]
last_coordinate = coordinates.coordinates_values()[-1]
# Compute true value
margin_model = self.time_series_lengths_to_margin_model[length]