diff --git a/extreme_fit/estimator/abstract_estimator.py b/extreme_fit/estimator/abstract_estimator.py
index c8e93cad38e6a333e301105a652b9dfb7a053577..39a695afe6b7d77ffcb6f52791547582d85f644f 100644
--- a/extreme_fit/estimator/abstract_estimator.py
+++ b/extreme_fit/estimator/abstract_estimator.py
@@ -11,7 +11,7 @@ from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
class AbstractEstimator(object):
- def __init__(self, dataset: AbstractDataset):
+ def __init__(self, dataset: AbstractDataset, **kwargs):
self.dataset = dataset # type: AbstractDataset
self._result_from_fit = None # type: Union[None, AbstractResultFromModelFit]
diff --git a/extreme_fit/estimator/quantile_estimator/abstract_quantile_estimator.py b/extreme_fit/estimator/quantile_estimator/abstract_quantile_estimator.py
index d43aae929945e9ec8b9f27b4a4c9cf657017b57c..5f0966b57abab724449247424b0424ecfda5775a 100644
--- a/extreme_fit/estimator/quantile_estimator/abstract_quantile_estimator.py
+++ b/extreme_fit/estimator/quantile_estimator/abstract_quantile_estimator.py
@@ -3,14 +3,17 @@ from cached_property import cached_property
from extreme_fit.estimator.abstract_estimator import AbstractEstimator
from extreme_fit.estimator.margin_estimator.abstract_margin_estimator import LinearMarginEstimator
from extreme_fit.function.abstract_quantile_function import AbstractQuantileFunction
+from extreme_fit.function.margin_function.abstract_margin_function import AbstractMarginFunction
from extreme_fit.model.margin_model.linear_margin_model.linear_margin_model import LinearMarginModel
+from extreme_fit.model.quantile_model.quantile_regression_model import AbstractQuantileRegressionModel
+from extreme_fit.model.result_from_model_fit.abstract_result_from_model_fit import AbstractResultFromModelFit
from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
class AbstractQuantileEstimator(AbstractEstimator):
- def __init__(self, quantile: float, **kwargs):
- super().__init__(**kwargs)
+ def __init__(self, dataset: AbstractDataset, quantile: float, **kwargs):
+ super().__init__(dataset, **kwargs)
assert 0 < quantile < 1
self.quantile = quantile
@@ -26,5 +29,19 @@ class QuantileEstimatorFromMargin(AbstractQuantileEstimator, LinearMarginEstimat
@cached_property
def quantile_function_from_fit(self) -> AbstractQuantileFunction:
- linear_margin_function = super().function_from_fit
+ linear_margin_function = super().function_from_fit # type: AbstractMarginFunction
return AbstractQuantileFunction(linear_margin_function, self.quantile)
+
+
+class QuantileRegressionEstimator(AbstractQuantileEstimator):
+
+ def __init__(self, dataset: AbstractDataset, quantile: float, quantile_regression_model_class: type, **kwargs):
+ super().__init__(dataset, quantile, **kwargs)
+ self.quantile_regression_model = quantile_regression_model_class(dataset, quantile) # type: AbstractQuantileRegressionModel
+
+ def _fit(self) -> AbstractResultFromModelFit:
+ return self.quantile_regression_model.fit()
+
+ @cached_property
+ def quantile_function_from_fit(self) -> AbstractQuantileFunction:
+ return self.result_from_model_fit.quantile_function
diff --git a/extreme_fit/function/abstract_quantile_function.py b/extreme_fit/function/abstract_quantile_function.py
index 4c06c95ec5f30bbc8ab287cbc517a73674faaf84..62596039e775d38726f1cf04600857ae3c7afbe6 100644
--- a/extreme_fit/function/abstract_quantile_function.py
+++ b/extreme_fit/function/abstract_quantile_function.py
@@ -12,4 +12,9 @@ class AbstractQuantileFunction(AbstractFunction):
def get_quantile(self, coordinate: np.ndarray) -> float:
gev_params = self.margin_function.get_gev_params(coordinate)
- return gev_params.quantile(self.quantile)
\ No newline at end of file
+ return gev_params.quantile(self.quantile)
+
+ def visualize(self):
+ pass
+ # for coordine
+ # self.margin_function.
\ No newline at end of file
diff --git a/extreme_fit/model/quantile_model/quantile_regression_model.py b/extreme_fit/model/quantile_model/quantile_regression_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..2652d5bbc843e30507fd7f4e052c0f0fc9e0dc80
--- /dev/null
+++ b/extreme_fit/model/quantile_model/quantile_regression_model.py
@@ -0,0 +1,57 @@
+import numpy as np
+from rpy2 import robjects
+
+from extreme_fit.model.abstract_model import AbstractModel
+from extreme_fit.model.result_from_model_fit.result_from_quantilreg import ResultFromQuantreg
+from extreme_fit.model.utils import r, safe_run_r_estimator, get_coord_df
+from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
+
+
+class AbstractQuantileRegressionModel(AbstractModel):
+
+ def __init__(self, dataset: AbstractDataset, quantile: float):
+ self.dataset = dataset
+ self.quantile = quantile
+
+ @property
+ def data(self):
+ return get_coord_df(self.dataset.df_dataset)
+
+ @property
+ def first_column_of_observation(self):
+ return self.data.colnames[1]
+ # print(self.dataset.df_dataset.columns)
+ # return str(self.dataset.df_dataset.columns[0])
+
+ def fit(self):
+ print(self.data)
+ parameters = {
+ 'tau': self.quantile,
+ 'data': self.data,
+ 'formula': self.formula
+
+ }
+ res = safe_run_r_estimator(r.rq, **parameters)
+ return ResultFromQuantreg(res)
+
+ @property
+ def formula_str(self):
+ raise NotImplementedError
+
+ @property
+ def formula(self):
+ return robjects.Formula(self.first_column_of_observation + '~ ' + self.formula_str)
+
+
+class ConstantQuantileRegressionModel(AbstractQuantileRegressionModel):
+
+ @property
+ def formula_str(self):
+ return '1'
+
+
+class AllCoordinatesQuantileRegressionModel(AbstractQuantileRegressionModel):
+
+ @property
+ def formula_str(self):
+ return '+'.join(self.dataset.coordinates.coordinates_names[-1:])
diff --git a/extreme_fit/model/result_from_model_fit/result_from_quantilreg.py b/extreme_fit/model/result_from_model_fit/result_from_quantilreg.py
new file mode 100644
index 0000000000000000000000000000000000000000..2be5c564daeb1c67c20f60bbae58a67891a5eb86
--- /dev/null
+++ b/extreme_fit/model/result_from_model_fit/result_from_quantilreg.py
@@ -0,0 +1,14 @@
+from cached_property import cached_property
+
+from extreme_fit.model.result_from_model_fit.abstract_result_from_model_fit import AbstractResultFromModelFit
+
+
+class ResultFromQuantreg(AbstractResultFromModelFit):
+
+ @property
+ def coefficients(self):
+ return self.name_to_value['coefficients']
+
+ @cached_property
+ def quantile_function(self):
+ print(self.coefficients)
\ No newline at end of file
diff --git a/extreme_fit/model/utils.py b/extreme_fit/model/utils.py
index 658c2fcbade7865c3538945c60baac81638f665d..1582cf336f615ef09692bb4cc3ac06b8c305bfc1 100644
--- a/extreme_fit/model/utils.py
+++ b/extreme_fit/model/utils.py
@@ -23,6 +23,7 @@ numpy2ri.activate()
pandas2ri.activate()
r.library('SpatialExtremes')
r.library('data.table')
+r.library('quantreg')
# Desactivate temporarily warnings
default_filters = warnings.filters.copy()
warnings.filterwarnings("ignore")
@@ -125,12 +126,11 @@ def get_coord(df_coordinates: pd.DataFrame):
def get_coord_df(df_coordinates: pd.DataFrame):
coord = pandas2ri.py2ri_pandasdataframe(df_coordinates)
# coord = r.transpose(coord)
- colname = df_coordinates.columns[0]
+ colname = df_coordinates.columns
coord.colnames = r.c(colname)
coord = r('data.frame')(coord, stringsAsFactors=True)
return coord
-
def get_null():
as_null = r['as.null']
return as_null(1.0)
diff --git a/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py b/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py
index fe599b2c50a3b11e965a1a216b4aa24f1c253327..0b009da9e4aa7b152362e0e46399870d115a7354 100644
--- a/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py
+++ b/spatio_temporal_dataset/spatio_temporal_observations/abstract_spatio_temporal_observations.py
@@ -53,7 +53,7 @@ class AbstractSpatioTemporalObservations(object):
(self.df_maxima_frech, self.OBSERVATIONS_FRECH)]:
if df is not None:
df_maxima = df.copy()
- df_maxima.columns = [str(c) + ' ' + suffix for c in df_maxima.columns]
+ df_maxima.columns = [str(c) for c in df_maxima.columns]
df_maxima_list.append(df_maxima)
return pd.concat(df_maxima_list, axis=1)
diff --git a/test/test_extreme_fit/test_estimator/test_quantile_estimator.py b/test/test_extreme_fit/test_estimator/test_quantile_estimator.py
index bd517938b1dec9cb8c69ad594b9407b084942552..0a304b2750be3d1c1110ab154a41997da58c21e5 100644
--- a/test/test_extreme_fit/test_estimator/test_quantile_estimator.py
+++ b/test/test_extreme_fit/test_estimator/test_quantile_estimator.py
@@ -1,17 +1,18 @@
import unittest
-from extreme_fit.estimator.quantile_estimator.abstract_quantile_estimator import QuantileEstimatorFromMargin
+from extreme_fit.estimator.quantile_estimator.abstract_quantile_estimator import QuantileEstimatorFromMargin, \
+ QuantileRegressionEstimator
from spatio_temporal_dataset.dataset.simulation_dataset import MarginDataset
from test.test_utils import load_test_1D_and_2D_spatial_coordinates, load_test_spatiotemporal_coordinates, \
- load_smooth_margin_models
+ load_smooth_margin_models, load_smooth_quantile_model_classes
-class TestSmoothMarginEstimator(unittest.TestCase):
+class TestQuantileEstimator(unittest.TestCase):
DISPLAY = False
def test_smooth_margin_estimator_spatial(self):
- self.nb_points = 2
- self.nb_obs = 2
+ self.nb_points = 20
+ self.nb_obs = 1
self.coordinates = load_test_1D_and_2D_spatial_coordinates(nb_points=self.nb_points)
def test_smooth_margin_estimator_spatio_temporal(self):
@@ -21,21 +22,28 @@ class TestSmoothMarginEstimator(unittest.TestCase):
self.coordinates = load_test_spatiotemporal_coordinates(nb_steps=self.nb_steps, nb_points=self.nb_points)
def tearDown(self) -> None:
- quantile = 0.98
+ quantile = 0.5
for coordinates in self.coordinates:
constant_margin_model = load_smooth_margin_models(coordinates=coordinates)[0]
dataset = MarginDataset.from_sampling(nb_obs=self.nb_obs,
margin_model=constant_margin_model,
coordinates=coordinates)
- quantile_estimators = [QuantileEstimatorFromMargin(dataset, constant_margin_model, quantile)]
- help(QuantileEstimatorFromMargin)
-
+ print(dataset)
+ # Load quantile estimators
+ quantile_estimators = [
+ QuantileEstimatorFromMargin(dataset, constant_margin_model, quantile),
+ ]
+ for quantile_model_class in load_smooth_quantile_model_classes()[:1]:
+ quantile_estimator = QuantileRegressionEstimator(dataset, quantile, quantile_model_class)
+ quantile_estimators.append(quantile_estimator)
+
+ # Fit quantile estimators
for quantile_estimator in quantile_estimators:
quantile_estimator.fit()
- print(quantile_estimator.function_from_fit)
+ print(quantile_estimator.quantile_function_from_fit)
- # self.assertTrue(True)
+ self.assertTrue(True)
if __name__ == '__main__':
- unittest.main()
\ No newline at end of file
+ unittest.main()
diff --git a/test/test_utils.py b/test/test_utils.py
index d5fe754c500eac5abe2bbd6e7372eb2e618dc6b3..bc2bf761591cb65a65c758c5a646395ce8a711d2 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -6,7 +6,8 @@ from experiment.meteo_france_data.scm_models_data.crocus.crocus import Crocus, C
from extreme_fit.estimator.full_estimator.abstract_full_estimator import SmoothMarginalsThenUnitaryMsp, \
FullEstimatorInASingleStepWithSmoothMargin
from extreme_fit.estimator.max_stable_estimator.abstract_max_stable_estimator import MaxStableEstimator
-from extreme_fit.model.margin_model.linear_margin_model.linear_margin_model import LinearAllParametersAllDimsMarginModel, \
+from extreme_fit.model.margin_model.linear_margin_model.linear_margin_model import \
+ LinearAllParametersAllDimsMarginModel, \
ConstantMarginModel
from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import \
NonStationaryLocationTemporalModel, NonStationaryScaleTemporalModel, NonStationaryShapeTemporalModel
@@ -16,6 +17,8 @@ from extreme_fit.model.max_stable_model.max_stable_models import Smith, BrownRes
Geometric, ExtremalT, ISchlather
from experiment.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall, Safran, SafranRainfall, \
SafranTemperature, SafranPrecipitation
+from extreme_fit.model.quantile_model.quantile_regression_model import ConstantQuantileRegressionModel, \
+ AllCoordinatesQuantileRegressionModel
from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
AbstractSpatialCoordinates
from spatio_temporal_dataset.coordinates.spatial_coordinates.alps_station_3D_coordinates import \
@@ -40,7 +43,9 @@ TEST_3D_SPATIAL_COORDINATES = [AlpsStation3DCoordinatesWithAnisotropy]
TEST_TEMPORAL_COORDINATES = [ConsecutiveTemporalCoordinates]
TEST_SPATIO_TEMPORAL_COORDINATES = [UniformSpatioTemporalCoordinates, LinSpaceSpatial2DSpatioTemporalCoordinates]
TEST_MARGIN_TYPES = [ConstantMarginModel, LinearAllParametersAllDimsMarginModel][:]
-TEST_NON_STATIONARY_TEMPORAL_MARGIN_TYPES = [NonStationaryLocationTemporalModel, NonStationaryScaleTemporalModel, NonStationaryShapeTemporalModel]
+TEST_QUANTILES_TYPES = [ConstantQuantileRegressionModel, AllCoordinatesQuantileRegressionModel][:]
+TEST_NON_STATIONARY_TEMPORAL_MARGIN_TYPES = [NonStationaryLocationTemporalModel, NonStationaryScaleTemporalModel,
+ NonStationaryShapeTemporalModel]
TEST_MAX_STABLE_ESTIMATOR = [MaxStableEstimator]
TEST_FULL_ESTIMATORS = [SmoothMarginalsThenUnitaryMsp, FullEstimatorInASingleStepWithSmoothMargin][:]
@@ -62,6 +67,10 @@ def load_smooth_margin_models(coordinates):
return [margin_class(coordinates=coordinates) for margin_class in TEST_MARGIN_TYPES]
+def load_smooth_quantile_model_classes():
+ return [quantile_reg_class for quantile_reg_class in TEST_QUANTILES_TYPES]
+
+
def load_test_max_stable_models(default_covariance_function=None):
# Load all max stable model
max_stable_models = []
@@ -84,14 +93,16 @@ 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) -> List[AbstractSpatialCoordinates]:
+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) -> List[AbstractSpatialCoordinates]:
- return load_test_spatial_coordinates(nb_points, TEST_3D_SPATIAL_COORDINATES, transformation_class=transformation_class)
+ return load_test_spatial_coordinates(nb_points, TEST_3D_SPATIAL_COORDINATES,
+ transformation_class=transformation_class)
def load_test_temporal_coordinates(nb_steps, train_split_ratio=None, transformation_class=None):