diff --git a/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py b/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py
index b7b198b9105b972591f8427a77254d069d4dfa3d..b0179e88b5613bfac9318660ec4c08280329ce36 100644
--- a/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py
+++ b/extreme_fit/model/margin_model/linear_margin_model/abstract_temporal_linear_margin_model.py
@@ -1,5 +1,3 @@
-from enum import Enum
-
import numpy as np
import pandas as pd
@@ -73,7 +71,7 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
if self.fit_method == MarginFitMethod.extremes_fevd_bayesian:
return self.extremes_fevd_bayesian_fit(x, df_coordinates_temp)
else:
- return self.run_fevd_fixed(df_coordinates_temp=df_coordinates_temp,
+ return self.run_fevd_fixed(df_coordinates_temp=df_coordinates_temp,
method=FEVD_MARGIN_FIT_METHOD_TO_ARGUMENT_STR[self.fit_method], x=x)
def extreme_fevd_mle_exp_fit(self, x, df_coordinates_temp):
diff --git a/projects/contrasting_trends_in_snow_loads/altitunal_fit/altitudes_studies.py b/projects/contrasting_trends_in_snow_loads/altitunal_fit/altitudes_studies.py
new file mode 100644
index 0000000000000000000000000000000000000000..308394641054f3cbc455cc3d0b6f3b4a89f9deb2
--- /dev/null
+++ b/projects/contrasting_trends_in_snow_loads/altitunal_fit/altitudes_studies.py
@@ -0,0 +1,58 @@
+import pandas as pd
+from collections import OrderedDict
+
+from cached_property import cached_property
+
+from extreme_data.meteo_france_data.scm_models_data.abstract_study import AbstractStudy
+from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
+ AbstractSpatialCoordinates
+from spatio_temporal_dataset.coordinates.spatio_temporal_coordinates.abstract_spatio_temporal_coordinates import \
+ AbstractSpatioTemporalCoordinates
+from spatio_temporal_dataset.coordinates.temporal_coordinates.generated_temporal_coordinates import \
+ ConsecutiveTemporalCoordinates
+from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
+
+
+class AltitudesStudies(object):
+
+ def __init__(self, study_class, altitudes, transformation_class=None, **kwargs_study):
+ self.transformation_class = transformation_class
+ self.altitudes = altitudes
+ self.altitude_to_study = OrderedDict()
+ for altitude in self.altitudes:
+ study = study_class(altitude=altitude, **kwargs_study)
+ self.altitude_to_study[altitude] = study
+
+ @cached_property
+ def study(self) -> AbstractStudy:
+ return list(self.altitude_to_study.values())[0]
+
+ def get_dataset(self, massif_name, slicer) -> AbstractDataset:
+ pass
+
+ # Coordinates Loader
+
+ @cached_property
+ def temporal_coordinates(self):
+ return ConsecutiveTemporalCoordinates.from_nb_temporal_steps(nb_temporal_steps=self.study.nb_years,
+ start=self.study.year_min,
+ transformation_class=self.transformation_class)
+
+ @cached_property
+ def spatial_coordinates(self):
+ return AbstractSpatialCoordinates.from_list_x_coordinates(x_coordinates=self.altitudes,
+ transformation_class=self.transformation_class)
+
+ def random_s_split_temporal(self, train_split_ratio):
+ return AbstractSpatioTemporalCoordinates.get_random_s_split_temporal(
+ spatial_coordinates=self.spatial_coordinates,
+ temporal_coordinates=self.temporal_coordinates,
+ train_split_ratio=train_split_ratio)
+
+ def spatio_temporal_coordinates(self, slicer_class: type, s_split_spatial: pd.Series = None,
+ s_split_temporal: pd.Series = None):
+ return AbstractSpatioTemporalCoordinates(slicer_class=slicer_class, s_split_spatial=s_split_spatial,
+ s_split_temporal=s_split_temporal,
+ transformation_class=self.transformation_class,
+ spatial_coordinates=self.spatial_coordinates,
+ temporal_coordinates=self.temporal_coordinates)
diff --git a/projects/contrasting_trends_in_snow_loads/altitunal_fit/two_fold_estimation.py b/projects/contrasting_trends_in_snow_loads/altitunal_fit/two_fold_estimation.py
new file mode 100644
index 0000000000000000000000000000000000000000..8ac122df6edcedb2a2707c24d7e730a8e394e7e5
--- /dev/null
+++ b/projects/contrasting_trends_in_snow_loads/altitunal_fit/two_fold_estimation.py
@@ -0,0 +1,6 @@
+
+class TwoFoldEstimation(object):
+
+
+ def __init__(self):
+ pass
diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index 76a211f1d2055e7964d72cde18c8894eb18b03e4..ae69b412c953f4b82a3d7a9cfc6298a39907f7c4 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -108,11 +108,15 @@ class AbstractCoordinates(object):
# Create a spatial split
s_split_spatial = s_split_from_df(df, cls.COORDINATE_X, cls.SPATIAL_SPLIT, train_split_ratio, True)
# Create a temporal split
- s_split_temporal = s_split_from_df(df, cls.COORDINATE_T, cls.TEMPORAL_SPLIT, train_split_ratio, False)
+ s_split_temporal = cls.temporal_s_split_from_df(df, train_split_ratio)
return cls(df=df, slicer_class=slicer_class, s_split_spatial=s_split_spatial, s_split_temporal=s_split_temporal,
transformation_class=transformation_class)
+ @classmethod
+ def temporal_s_split_from_df(cls, df, train_split_ratio):
+ return s_split_from_df(df, cls.COORDINATE_T, cls.TEMPORAL_SPLIT, train_split_ratio, False)
+
@classmethod
def from_csv(cls, csv_path: str = None):
assert csv_path is not None
@@ -266,8 +270,7 @@ class AbstractCoordinates(object):
# Modify the temporal coordinates to enforce the stationarity
df_temporal_coordinates.loc[ind_to_modify] = starting_point
# Load the temporal transformation object
- temporal_transformation = self.temporal_coordinates.transformation_class(
- df_temporal_coordinates) # type: AbstractTransformation
+ temporal_transformation = self.temporal_coordinates.transformation_class(df_temporal_coordinates) # type: AbstractTransformation
# Return the result of the temporal transformation
df = temporal_transformation.transform_df(df_temporal_coordinates)
# Potentially transform the time covariate into another covariate
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 f6b3daec64d87f148ebade5b256a2cbfb2bba5dd..21d12f35525a9d6ce0e5623f5a534c36e292c9ce 100644
--- a/spatio_temporal_dataset/coordinates/spatial_coordinates/abstract_spatial_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/spatial_coordinates/abstract_spatial_coordinates.py
@@ -6,6 +6,11 @@ from spatio_temporal_dataset.slicer.spatial_slicer import SpatialSlicer
class AbstractSpatialCoordinates(AbstractCoordinates):
+ @classmethod
+ def from_list_x_coordinates(cls, x_coordinates, train_split_ratio: float = None, transformation_class: type = None):
+ df = pd.DataFrame({cls.COORDINATE_X: x_coordinates})
+ return cls.from_df(df, train_split_ratio, transformation_class)
+
@classmethod
def from_df(cls, df: pd.DataFrame, train_split_ratio: float = None, transformation_class: type = None):
assert cls.COORDINATE_X in df.columns
diff --git a/spatio_temporal_dataset/coordinates/spatio_temporal_coordinates/abstract_spatio_temporal_coordinates.py b/spatio_temporal_dataset/coordinates/spatio_temporal_coordinates/abstract_spatio_temporal_coordinates.py
index 14c0b01aea0cd40eba13e42ad68129fe245f3c81..1d7985541a5dc1fe2fe6906a3c9a0f39f3d8145a 100644
--- a/spatio_temporal_dataset/coordinates/spatio_temporal_coordinates/abstract_spatio_temporal_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/spatio_temporal_coordinates/abstract_spatio_temporal_coordinates.py
@@ -14,11 +14,14 @@ from spatio_temporal_dataset.slicer.spatio_temporal_slicer import SpatioTemporal
class AbstractSpatioTemporalCoordinates(AbstractCoordinates):
- def __init__(self, df: pd.DataFrame, slicer_class: type,
+ def __init__(self, df: pd.DataFrame = None, slicer_class: type = SpatioTemporalSlicer,
s_split_spatial: pd.Series = None, s_split_temporal: pd.Series = None,
transformation_class: type = None,
spatial_coordinates: AbstractSpatialCoordinates = None,
temporal_coordinates: AbstractTemporalCoordinates = None):
+ if df is None:
+ assert spatial_coordinates is not None and temporal_coordinates is not None
+ df = self.get_df_from_spatial_and_temporal_coordinates(spatial_coordinates, temporal_coordinates)
super().__init__(df, slicer_class, s_split_spatial, s_split_temporal, None)
# Spatial coordinates'
if spatial_coordinates is None:
@@ -47,6 +50,20 @@ class AbstractSpatioTemporalCoordinates(AbstractCoordinates):
def temporal_coordinates(self):
return self._temporal_coordinates
+ @classmethod
+ def from_spatial_coordinates_and_temporal_coordinates(cls, spatial_coordinates: AbstractSpatialCoordinates,
+ temporal_coordinates: AbstractTemporalCoordinates):
+ df = cls.get_df_from_spatial_and_temporal_coordinates(spatial_coordinates, temporal_coordinates)
+ return cls(df=df, slicer_class=SpatioTemporalSlicer,
+ spatial_coordinates=spatial_coordinates, temporal_coordinates=temporal_coordinates)
+
+ @classmethod
+ def get_random_s_split_temporal(cls, spatial_coordinates: AbstractSpatialCoordinates,
+ temporal_coordinates: AbstractTemporalCoordinates,
+ train_split_ratio):
+ df = cls.get_df_from_spatial_and_temporal_coordinates(spatial_coordinates, temporal_coordinates)
+ return cls.temporal_s_split_from_df(df, train_split_ratio)
+
@classmethod
def get_df_from_df_spatial_and_coordinate_t_values(cls, coordinate_t_values, df_spatial):
df_time_steps = []
@@ -59,14 +76,13 @@ class AbstractSpatioTemporalCoordinates(AbstractCoordinates):
return df_time_steps
@classmethod
- def from_spatial_coordinates_and_temporal_coordinates(cls, spatial_coordinates: AbstractSpatialCoordinates,
- temporal_coordinates: AbstractTemporalCoordinates):
- df_spatial = spatial_coordinates.df_spatial_coordinates(transformed=False)
- coordinate_t_values = temporal_coordinates.df_temporal_coordinates(transformed=False).iloc[:, 0].values
+ def get_df_from_spatial_and_temporal_coordinates(cls, spatial_coordinates, temporal_coordinates, transformed=False):
+ # Transformed is False, so that the value in the spatio temporal datasets are still readable
+ df_spatial = spatial_coordinates.df_spatial_coordinates(transformed=transformed)
+ coordinate_t_values = temporal_coordinates.df_temporal_coordinates(transformed=transformed).iloc[:, 0].values
df = cls.get_df_from_df_spatial_and_coordinate_t_values(df_spatial=df_spatial,
coordinate_t_values=coordinate_t_values)
- return cls(df=df, slicer_class=SpatioTemporalSlicer,
- spatial_coordinates=spatial_coordinates, temporal_coordinates=temporal_coordinates)
+ return df
@classmethod
def from_df(cls, df: pd.DataFrame, train_split_ratio: float = None, transformation_class: type = None):
diff --git a/test/test_projects/test_contrasting/__init__.py b/test/test_projects/test_contrasting/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/test/test_projects/test_contrasting/test_altitudes_studies.py b/test/test_projects/test_contrasting/test_altitudes_studies.py
new file mode 100644
index 0000000000000000000000000000000000000000..be3fe72b6f9d4fbae7184fadac582f492a66af89
--- /dev/null
+++ b/test/test_projects/test_contrasting/test_altitudes_studies.py
@@ -0,0 +1,29 @@
+import unittest
+
+from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day
+from projects.contrasting_trends_in_snow_loads.altitunal_fit.altitudes_studies import AltitudesStudies
+from spatio_temporal_dataset.slicer.split import Split, small_s_split_from_ratio
+from spatio_temporal_dataset.slicer.temporal_slicer import TemporalSlicer
+import pandas as pd
+
+
+class TestAltitudesStudies(unittest.TestCase):
+
+ def setUp(self) -> None:
+ super().setUp()
+ altitudes = [900, 1200]
+ study_class = SafranSnowfall1Day
+ self.studies = AltitudesStudies(study_class, altitudes, year_min=1959, year_max=1962)
+
+ def test_spatio_temporal_coordinates_with_temporal_split(self):
+ s_split_temporal = self.studies.random_s_split_temporal(train_split_ratio=0.75)
+ coordinates = self.studies.spatio_temporal_coordinates(slicer_class=TemporalSlicer,
+ s_split_temporal=s_split_temporal)
+ train_values = coordinates.coordinates_values(split=Split.train_temporal)
+ self.assertEqual(train_values.shape, (6, 2))
+ test_values = coordinates.coordinates_values(split=Split.test_temporal)
+ self.assertEqual(test_values.shape, (2, 2))
+
+
+if __name__ == '__main__':
+ unittest.main()
\ No newline at end of file