diff --git a/extreme_data/meteo_france_data/mean_alps_temperature.py b/extreme_data/meteo_france_data/mean_alps_temperature.py
new file mode 100644
index 0000000000000000000000000000000000000000..4256c05468905babced7ea90deb9f160513df699
--- /dev/null
+++ b/extreme_data/meteo_france_data/mean_alps_temperature.py
@@ -0,0 +1,26 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranTemperature
+
+
+def show_year_to_mean_alps_temperatures():
+ ax = plt.gca()
+ for altitude in range(900, 3300, 300):
+ # for altitude in [900]:
+ year_to_mean_alps_temperature = load_year_to_mean_alps_temperatures(altitude)
+ ax.plot(year_to_mean_alps_temperature.keys(), year_to_mean_alps_temperature.values(), label=altitude)
+ ax.legend()
+ plt.show()
+
+
+def load_year_to_mean_alps_temperatures(altitude=900):
+ study = SafranTemperature(altitude=altitude)
+ df = pd.DataFrame.from_dict(data=study.year_to_annual_mean).transpose().mean(axis=1) # type: pd.Series
+ df.index = df.index.astype(float)
+ year_to_mean_alps_temperature = df.to_dict()
+ return year_to_mean_alps_temperature
+
+
+if __name__ == '__main__':
+ show_year_to_mean_alps_temperatures()
diff --git a/extreme_data/nasa_data/global_mean_temperature.py b/extreme_data/nasa_data/global_mean_temperature.py
index 8475b218138769ba5b799f2c23c7a3ce0989403d..2b98d317ef2f171139918244599fbe395126bf59 100644
--- a/extreme_data/nasa_data/global_mean_temperature.py
+++ b/extreme_data/nasa_data/global_mean_temperature.py
@@ -16,9 +16,9 @@ def load_year_to_mean_global_temperature():
df = pd.read_csv(edf_filepath)
df = df.astype({'Year': 'float'})
d = dict(zip(df['Year'], df['Actual Temp']))
- # Cheat for the last years
- print('Warning: using fake values for the last few years !!!')
- for idx in range(1, 5):
- d[2016 + idx] = d[2016]
+ # # Cheat for the last years
+ # print('Warning: using fake values for the last few years !!!')
+ # for idx in range(1, 5):
+ # d[2016 + idx] = d[2016]
return d
diff --git a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
index 8a73686eb5e93647c94b6e047762da2074d1e147..62661c2582c33782bee30bb57a8fce6c7bce30a9 100644
--- a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
+++ b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
@@ -2,6 +2,7 @@ from abc import ABC
import numpy.testing as npt
import numpy as np
+import pandas as pd
from cached_property import cached_property
from extreme_fit.estimator.abstract_estimator import AbstractEstimator
@@ -29,26 +30,29 @@ class LinearMarginEstimator(AbstractMarginEstimator):
self.margin_model = margin_model
def _fit(self) -> AbstractResultFromModelFit:
- return self.margin_model.fitmargin_from_maxima_gev(data=self.maxima_gev_train,
- df_coordinates_spat=self.df_coordinates_spat,
- df_coordinates_temp=self.df_coordinates_temp)
+ data = self.data(self.train_split)
+ df_coordinate_temp = self.df_coordinates_temp(self.train_split)
+ df_coordinate_spat = self.df_coordinates_spat(self.train_split)
+ return self.margin_model.fitmargin_from_maxima_gev(data=data,
+ df_coordinates_spat=df_coordinate_spat,
+ df_coordinates_temp=df_coordinate_temp)
- @property
- def df_coordinates_spat(self):
- return self.dataset.coordinates.df_spatial_coordinates(split=self.train_split,
+ def data(self, split):
+ return self._maxima_gev(split)
+
+ def _maxima_gev(self, split):
+ return self.dataset.maxima_gev_for_spatial_extremes_package(split)
+
+ def df_coordinates_spat(self, split):
+ return self.dataset.coordinates.df_spatial_coordinates(split=split,
drop_duplicates=self.margin_model.drop_duplicates)
- @property
- def df_coordinates_temp(self):
- return self.dataset.coordinates.df_temporal_coordinates_for_fit(split=self.train_split,
+ def df_coordinates_temp(self, split):
+ return self.dataset.coordinates.df_temporal_coordinates_for_fit(split=split,
temporal_covariate_for_fit=self.margin_model.temporal_covariate_for_fit,
starting_point=self.margin_model.starting_point,
drop_duplicates=self.margin_model.drop_duplicates)
- @property
- def maxima_gev_train(self):
- return self.dataset.maxima_gev_for_spatial_extremes_package(self.train_split)
-
@cached_property
def function_from_fit(self) -> LinearMarginFunction:
return load_margin_function(self, self.margin_model)
@@ -56,7 +60,7 @@ class LinearMarginEstimator(AbstractMarginEstimator):
def nllh(self, split=Split.all):
nllh = 0
maxima_values = self.dataset.maxima_gev(split=split)
- coordinate_values = self.dataset.coordinates_values(split=split)
+ coordinate_values = self.dataset.df_coordinates(split=split).values
for maximum, coordinate in zip(maxima_values, coordinate_values):
assert len(
maximum) == 1, 'So far, only one observation for each coordinate, but code would be easy to change'
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 b69a6b4375a2c075c74ea24f58287220fd30bc46..c02d1bd98f847699b81861feb758214407bd73f0 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
@@ -35,13 +35,15 @@ class AbstractTemporalLinearMarginModel(LinearMarginModel):
def fitmargin_from_maxima_gev(self, data: np.ndarray, df_coordinates_spat: pd.DataFrame,
df_coordinates_temp: pd.DataFrame) -> AbstractResultFromModelFit:
- if len(data) == 1:
- data = data[0]
- assert len(data) == len(df_coordinates_temp.values), 'len(data)={} != len(temp)={}'.format(len(data),
- len(
- df_coordinates_temp.values))
- else:
- data = data.flatten()
+ data = data.flatten()
+ # if len(data) == 1:
+ # data = data[0]
+ # assert len(data) == len(df_coordinates_temp.values), 'len(data)={} != len(temp)={}'.format(len(data),
+ # len(
+ # df_coordinates_temp.values))
+ # else:
+ # data = data.flatten()
+
x = ro.FloatVector(data)
if self.params_class is GevParams:
if self.fit_method == MarginFitMethod.is_mev_gev_fit:
diff --git a/projects/altitude_spatial_model/altitudes_fit/altitudes_studies.py b/projects/altitude_spatial_model/altitudes_fit/altitudes_studies.py
index 5bd6c2aeeab9af9486f34fd46601d3f9ddfc5244..940d4fa3f1bfd064ca00af9c507a17f49373717f 100644
--- a/projects/altitude_spatial_model/altitudes_fit/altitudes_studies.py
+++ b/projects/altitude_spatial_model/altitudes_fit/altitudes_studies.py
@@ -43,7 +43,7 @@ class AltitudesStudies(object):
# Dataset Loader
def spatio_temporal_dataset(self, massif_name, s_split_spatial: pd.Series = None,
- s_split_temporal: pd.Series = None):
+ s_split_temporal: pd.Series = None, top_n_values_to_remove=None):
coordinate_values_to_maxima = {}
massif_altitudes = self.massif_name_to_altitudes[massif_name]
for altitude in massif_altitudes:
diff --git a/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py b/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
index f22c1703dd40299744944672a84e58e7957f9305..aee48ba6151de3e16ac75dd1a28db49608dc6060 100644
--- a/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
+++ b/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
@@ -6,8 +6,7 @@ from extreme_fit.model.margin_model.polynomial_margin_model.utils import ALTITUD
ALTITUDINAL_GEV_MODELS_LOCATION_QUADRATIC_MINIMUM, ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES, ALTITUDINAL_GEV_MODELS_LOCATION
from projects.altitude_spatial_model.altitudes_fit.one_fold_analysis.plot_total_aic import plot_total_aic, \
plot_individual_aic
-from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
- MeanGlobalTemperatureCovariate
+from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import MeanAlpsTemperatureCovariate
mpl.rcParams['text.usetex'] = True
mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
@@ -45,7 +44,10 @@ def plot_altitudinal_fit(studies, massif_names=None):
model_classes=model_classes,
massif_names=massif_names,
show=False,
- temporal_covariate_for_fit=None)
+ temporal_covariate_for_fit=None,
+ # temporal_covariate_for_fit=MeanAlpsTemperatureCovariate,
+ top_n_values_to_remove=None,
+ )
# Plot the results for the model that minimizes the individual aic
plot_individual_aic(visualizer)
# Plot the results for the model that minimizes the total aic
diff --git a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py
index 1bce4578aae56629bb8f06edba7d433603b81b78..b4aca0e71a9092491936a506d77b2f1ea0d9fbd2 100644
--- a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py
+++ b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/altitudes_studies_visualizer_for_non_stationary_models.py
@@ -29,7 +29,8 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
massif_names=None,
fit_method=MarginFitMethod.extremes_fevd_mle,
temporal_covariate_for_fit=None,
- display_only_model_that_pass_anderson_test=True):
+ display_only_model_that_pass_anderson_test=True,
+ top_n_values_to_remove=None):
super().__init__(studies.study, show=show, save_to_file=not show)
self.studies = studies
self.non_stationary_models = model_classes
@@ -41,7 +42,8 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
# Load one fold fit
self._massif_name_to_one_fold_fit = {}
for massif_name in self.massif_names:
- dataset = studies.spatio_temporal_dataset(massif_name=massif_name)
+ assert top_n_values_to_remove is None
+ dataset = studies.spatio_temporal_dataset(massif_name=massif_name, top_n_values_to_remove=top_n_values_to_remove)
old_fold_fit = OneFoldFit(massif_name, dataset, model_classes, self.fit_method,
self.temporal_covariate_for_fit)
self._massif_name_to_one_fold_fit[massif_name] = old_fold_fit
diff --git a/spatio_temporal_dataset/coordinates/abstract_coordinates.py b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
index 8d1539856dd06597bea6798f01daeec1c1996674..363063c3b9cd4a8b5c58a105ff9856e9d9569899 100644
--- a/spatio_temporal_dataset/coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/coordinates/abstract_coordinates.py
@@ -230,12 +230,6 @@ class AbstractCoordinates(object):
# Temporal attributes
- @property
- 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 []
diff --git a/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_covariate_for_fit.py b/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_covariate_for_fit.py
index 02777561c9ee68aa9f521f60712f8f718c5f508e..d1b3a6179f1101744a5e59fefb27069f3a1826c4 100644
--- a/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_covariate_for_fit.py
+++ b/spatio_temporal_dataset/coordinates/temporal_coordinates/abstract_temporal_covariate_for_fit.py
@@ -1,9 +1,3 @@
-import pandas as pd
-
-from extreme_data.nasa_data.global_mean_temperature import load_year_to_mean_global_temperature
-from root_utils import classproperty
-
-
class AbstractTemporalCovariateForFit(object):
@classmethod
@@ -18,19 +12,3 @@ class TimeTemporalCovariate(AbstractTemporalCovariateForFit):
return t
-class MeanGlobalTemperatureCovariate(AbstractTemporalCovariateForFit):
-
- _d = None
-
- @classproperty
- def year_to_global_mean(cls):
- if cls._d is None:
- cls._d = load_year_to_mean_global_temperature()
- return cls._d
-
- @classmethod
- def get_temporal_covariate(cls, t):
- try:
- return pd.Series(cls.year_to_global_mean[t])
- except KeyError:
- raise KeyError('Global mean temperature is not known for Year t={}'.format(t))
diff --git a/spatio_temporal_dataset/coordinates/temporal_coordinates/temperature_covariate.py b/spatio_temporal_dataset/coordinates/temporal_coordinates/temperature_covariate.py
new file mode 100644
index 0000000000000000000000000000000000000000..ca39e6f554955ee53eff380f1cb91cd59143928d
--- /dev/null
+++ b/spatio_temporal_dataset/coordinates/temporal_coordinates/temperature_covariate.py
@@ -0,0 +1,41 @@
+from extreme_data.meteo_france_data.mean_alps_temperature import load_year_to_mean_alps_temperatures
+from extreme_data.nasa_data.global_mean_temperature import load_year_to_mean_global_temperature
+from root_utils import classproperty
+from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
+ AbstractTemporalCovariateForFit
+import pandas as pd
+
+
+class AbstractTemperatureCovariate(AbstractTemporalCovariateForFit):
+ _d = None
+
+ @classproperty
+ def year_to_global_mean(cls):
+ if cls._d is None:
+ cls._d = cls.load_year_to_temperature_covariate()
+ return cls._d
+
+ @classmethod
+ def load_year_to_temperature_covariate(cls):
+ raise NotImplemented
+
+ @classmethod
+ def get_temporal_covariate(cls, t):
+ try:
+ return pd.Series(cls.year_to_global_mean[t])
+ except KeyError:
+ raise KeyError('Global mean temperature is not known for Year t={}'.format(t))
+
+
+class MeanGlobalTemperatureCovariate(AbstractTemperatureCovariate):
+
+ @classmethod
+ def load_year_to_temperature_covariate(cls):
+ return load_year_to_mean_global_temperature()
+
+
+class MeanAlpsTemperatureCovariate(AbstractTemperatureCovariate):
+
+ @classmethod
+ def load_year_to_temperature_covariate(cls):
+ return load_year_to_mean_alps_temperatures()
diff --git a/test/test_extreme_data/test_nasa_data/test_mean_global_temperature.py b/test/test_extreme_data/test_nasa_data/test_mean_global_temperature.py
index c91196b4fdb0c09c1e6dba4335ba8f37db7bed5f..45abe11af269cc084b03e6b5a19dfbb850f156ac 100644
--- a/test/test_extreme_data/test_nasa_data/test_mean_global_temperature.py
+++ b/test/test_extreme_data/test_nasa_data/test_mean_global_temperature.py
@@ -1,5 +1,6 @@
import unittest
+from extreme_data.meteo_france_data.mean_alps_temperature import load_year_to_mean_alps_temperatures
from extreme_data.nasa_data.global_mean_temperature import load_year_to_mean_global_temperature
@@ -14,6 +15,16 @@ class TestMeanGlobalTemperatures(unittest.TestCase):
value = list(d.values())[0]
self.assertIsInstance(value, float)
+ def test_year_to_mean_alps_temperatures(self):
+ d = load_year_to_mean_alps_temperatures()
+ self.assertIn(2019, d)
+ self.assertNotIn(2020, d)
+ self.assertIn(1959, d)
+ key = list(d.keys())[0]
+ self.assertIsInstance(key, float)
+ value = list(d.values())[0]
+ self.assertIsInstance(value, float)
+
if __name__ == '__main__':
unittest.main()
diff --git a/test/test_spatio_temporal_dataset/test_coordinates.py b/test/test_spatio_temporal_dataset/test_coordinates.py
index bd5a883d566eb8f94e3aced52e2e6419029e942f..ce5365378835b0ded31d011ac946ef03803c5e35 100644
--- a/test/test_spatio_temporal_dataset/test_coordinates.py
+++ b/test/test_spatio_temporal_dataset/test_coordinates.py
@@ -18,9 +18,11 @@ from spatio_temporal_dataset.coordinates.spatial_coordinates.alps_station_3D_coo
from spatio_temporal_dataset.coordinates.spatial_coordinates.generated_spatial_coordinates import \
CircleSpatialCoordinates
from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
- AbstractTemporalCovariateForFit, TimeTemporalCovariate, MeanGlobalTemperatureCovariate
+ AbstractTemporalCovariateForFit, TimeTemporalCovariate
from spatio_temporal_dataset.coordinates.temporal_coordinates.generated_temporal_coordinates import \
ConsecutiveTemporalCoordinates
+from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
+ MeanGlobalTemperatureCovariate
from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.abstract_transformation import \
CenteredScaledNormalization
from spatio_temporal_dataset.coordinates.transformed_coordinates.transformation.uniform_normalization import \