diff --git a/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py b/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
index 4b5d8a8d42e3037a14df5a2290f431a3dcae7897..bf9a6f4a3189b40c06ff0a08a80e78e732b4f0e3 100644
--- a/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
+++ b/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
@@ -90,7 +90,7 @@ def dat_to_csv(csv_filepath, txt_filepath):
assert len(df_temp_until_july.columns) == 7
df_temp_after_august = df.iloc[:-1, 7:]
assert len(df_temp_after_august.columns) == 5
- l = df_temp_until_july.sum(axis=1).values + df_temp_after_august.sum(axis=1).values
+ l = df_temp_until_july.sum_of_differences(axis=1).values + df_temp_after_august.sum_of_differences(axis=1).values
l /= 12
l = [np.nan] + list(l)
assert len(l) == len(df.index)
diff --git a/extreme_data/meteo_france_data/stations_data/comparison_analysis.py b/extreme_data/meteo_france_data/stations_data/comparison_analysis.py
index d4bd1bd125f7b7fad8db1ab7629049a35516ccc1..278991570f52c5059ee35973d351a081bf666e8f 100644
--- a/extreme_data/meteo_france_data/stations_data/comparison_analysis.py
+++ b/extreme_data/meteo_france_data/stations_data/comparison_analysis.py
@@ -213,7 +213,7 @@ class ComparisonAnalysis(object):
# Mean number of non-Nan values
d['% of Nan'] = df_values_from_1958.isna().mean().mean()
# Number of lines with only Nan
- d['Lines w Nan'] = df_values_from_1958.isna().all(axis=1).sum()
+ d['Lines w Nan'] = df_values_from_1958.isna().all(axis=1).sum_of_differences()
return pd.Series(d)
def altitude_short_analysis(self):
diff --git a/projects/archive/check_mcmc_convergence_for_return_levels/gelman_convergence_test.py b/projects/archive/check_mcmc_convergence_for_return_levels/gelman_convergence_test.py
index e5f6b7a5575abd544f01cb9cbf21d5693d261266..aed8b4dbfe3c71a5757f0cf7060c0264aa85de05 100644
--- a/projects/archive/check_mcmc_convergence_for_return_levels/gelman_convergence_test.py
+++ b/projects/archive/check_mcmc_convergence_for_return_levels/gelman_convergence_test.py
@@ -13,7 +13,7 @@ def compute_gelman_score(means, variances, N, M):
assert isinstance(means, pd.Series)
assert isinstance(variances, pd.Series)
mean = means.mean()
- B = N * (means - mean).pow(2).sum() / (M - 1)
+ B = N * (means - mean).pow(2).sum_of_differences() / (M - 1)
W = variances.mean()
V_hat = (N - 1) * W / N
V_hat += (M + 1) * B / (M * N)
diff --git a/projects/projected_swe/model_as_truth_visualizer/__init__.py b/projects/projected_swe/model_as_truth_visualizer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/projects/projected_swe/old_weight_computer/__init__.py b/projects/projected_swe/old_weight_computer/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/projects/projected_swe/abstract_weight_computer.py b/projects/projected_swe/old_weight_computer/abstract_weight_computer.py
similarity index 83%
rename from projects/projected_swe/abstract_weight_computer.py
rename to projects/projected_swe/old_weight_computer/abstract_weight_computer.py
index 669419f1f0b75141fd4ee9790fb3e70002e794b4..455d992e881ac2863c5d5d8eb8e0ba63cbdd2a1a 100644
--- a/projects/projected_swe/abstract_weight_computer.py
+++ b/projects/projected_swe/old_weight_computer/abstract_weight_computer.py
@@ -1,28 +1,14 @@
-from collections import OrderedDict
import pandas as pd
-import numpy as np
-from scipy.special import softmax
-
-from extreme_data.meteo_france_data.adamont_data.adamont_scenario import gcm_rcm_couple_to_str
-from extreme_data.meteo_france_data.scm_models_data.altitudes_studies import AltitudesStudies
-from extreme_fit.estimator.margin_estimator.abstract_margin_estimator import compute_nllh
-from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fit import IndependentEnsembleFit
-from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
-from projects.projected_swe.utils import WEIGHT_COLUMN_NAME, get_csv_filepath, save_to_filepath
-from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
- TimeTemporalCovariate
+from projects.projected_swe.weight_computer.utils import WEIGHT_COLUMN_NAME, save_to_filepath
from collections import OrderedDict
import numpy as np
from scipy.special import softmax
from extreme_data.meteo_france_data.scm_models_data.altitudes_studies import AltitudesStudies
-from extreme_fit.estimator.margin_estimator.abstract_margin_estimator import compute_nllh
from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fit import IndependentEnsembleFit
from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
-from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
- TimeTemporalCovariate
class AbstractWeightComputer(object):
diff --git a/projects/projected_swe/knutti_weight_computer.py b/projects/projected_swe/old_weight_computer/knutti_weight_computer.py
similarity index 80%
rename from projects/projected_swe/knutti_weight_computer.py
rename to projects/projected_swe/old_weight_computer/knutti_weight_computer.py
index 41b43b1331109aa963231273a9fef39ad18cf585..17284b7a95d14b608cae39fc22dbcc7f7e436332 100644
--- a/projects/projected_swe/knutti_weight_computer.py
+++ b/projects/projected_swe/old_weight_computer/knutti_weight_computer.py
@@ -1,7 +1,7 @@
import numpy as np
-from projects.projected_swe.abstract_weight_computer import AbstractWeightComputer
-from projects.projected_swe.non_stationary_weight_computer import NllhWeightComputer
+from projects.projected_swe.weight_computer.abstract_weight_computer import AbstractWeightComputer
+from projects.projected_swe.weight_computer.non_stationary_weight_computer import NllhWeightComputer
class KnuttiWeightComputer(AbstractWeightComputer):
diff --git a/projects/projected_swe/main_weight_computation.py b/projects/projected_swe/old_weight_computer/main_weight_computation.py
similarity index 75%
rename from projects/projected_swe/main_weight_computation.py
rename to projects/projected_swe/old_weight_computer/main_weight_computation.py
index 8a6b87513be25d40e0a87eeb6f56280c42c9ad08..bfd4a62bad883a91c1749a53bde130f403d154fd 100644
--- a/projects/projected_swe/main_weight_computation.py
+++ b/projects/projected_swe/old_weight_computer/main_weight_computation.py
@@ -1,38 +1,21 @@
-import os
-
-from collections import OrderedDict
-
-import pandas as pd
-import os.path as op
import datetime
import time
-import numpy as np
-from scipy.special import softmax
from extreme_data.meteo_france_data.adamont_data.adamont.adamont_safran import AdamontSnowfall
-from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario, get_gcm_rcm_couples, \
- gcm_rcm_couple_to_str, SEPARATOR_STR, scenario_to_str
-from extreme_data.meteo_france_data.scm_models_data.altitudes_studies import AltitudesStudies
+from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario, get_gcm_rcm_couples
from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day
from extreme_data.meteo_france_data.scm_models_data.utils import Season
-from extreme_data.utils import DATA_PATH
-from extreme_fit.estimator.margin_estimator.abstract_margin_estimator import compute_nllh
from extreme_fit.model.margin_model.polynomial_margin_model.gev_altitudinal_models import StationaryAltitudinal
from extreme_fit.model.margin_model.polynomial_margin_model.models_based_on_pariwise_analysis.gev_with_linear_shape_wrt_altitude import \
AltitudinalShapeLinearTimeStationary
-from extreme_fit.model.margin_model.polynomial_margin_model.utils import \
- ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fit import IndependentEnsembleFit
from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
from extreme_trend.one_fold_fit.altitude_group import altitudes_for_groups
-from projects.projected_swe.abstract_weight_computer import AbstractWeightComputer
-from projects.projected_swe.knutti_weight_computer import KnuttiWeightComputer
-from projects.projected_swe.non_stationary_weight_computer import NllhWeightComputer
-from projects.projected_swe.utils import load_gcm_rcm_couple_to_weight
+from projects.projected_swe.weight_computer.abstract_weight_computer import AbstractWeightComputer
+from projects.projected_swe.weight_computer.knutti_weight_computer import KnuttiWeightComputer
+from projects.projected_swe.weight_computer.non_stationary_weight_computer import NllhWeightComputer
from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
TimeTemporalCovariate
-from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
- AnomalyTemperatureWithSplineTemporalCovariate
def main_weight_computation():
diff --git a/projects/projected_swe/non_stationary_weight_computer.py b/projects/projected_swe/old_weight_computer/non_stationary_weight_computer.py
similarity index 89%
rename from projects/projected_swe/non_stationary_weight_computer.py
rename to projects/projected_swe/old_weight_computer/non_stationary_weight_computer.py
index dd305395470c24252ad5a85cc65d741e2d8643f0..75215187cebd37adac010174bd05886de1601b26 100644
--- a/projects/projected_swe/non_stationary_weight_computer.py
+++ b/projects/projected_swe/old_weight_computer/non_stationary_weight_computer.py
@@ -1,8 +1,7 @@
import numpy as np
from extreme_fit.estimator.margin_estimator.abstract_margin_estimator import compute_nllh
-from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
-from projects.projected_swe.abstract_weight_computer import AbstractWeightComputer
+from projects.projected_swe.weight_computer.abstract_weight_computer import AbstractWeightComputer
from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
TimeTemporalCovariate
diff --git a/projects/projected_swe/utils.py b/projects/projected_swe/old_weight_computer/utils.py
similarity index 100%
rename from projects/projected_swe/utils.py
rename to projects/projected_swe/old_weight_computer/utils.py
diff --git a/projects/projected_swe/weight_solver/__init__.py b/projects/projected_swe/weight_solver/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/projects/projected_swe/weight_solver/abtract_weight_solver.py b/projects/projected_swe/weight_solver/abtract_weight_solver.py
new file mode 100644
index 0000000000000000000000000000000000000000..70bc47e3edb1c3118aa0d997d0b53c8e331c0845
--- /dev/null
+++ b/projects/projected_swe/weight_solver/abtract_weight_solver.py
@@ -0,0 +1,51 @@
+from scipy.special import softmax
+import numpy as np
+
+from projects.projected_swe.weight_solver.indicator import AbstractIndicator
+
+
+class AbstractWeightSolver(object):
+
+ def __init__(self, observation_study, couple_to_study, indicator_class: type, add_interdependence_weight=False):
+ self.observation_study = observation_study
+ self.couple_to_study = couple_to_study
+ self.indicator_class = indicator_class
+ self.add_interdependence_weight = add_interdependence_weight
+
+ @property
+ def couple_to_weight(self):
+ nllh_list, couple_list = zip(*list(self.couple_to_nllh.items()))
+ weights = softmax(-np.array(nllh_list))
+ return dict(zip(couple_list, weights))
+
+ @property
+ def couple_to_nllh(self):
+ couple_to_nllh = self.couple_to_nllh_skill
+ if self.add_interdependence_weight:
+ for c, v in self.couple_to_nllh_interdependence.items():
+ couple_to_nllh[c] += v
+ return couple_to_nllh
+
+ @property
+ def couple_to_nllh_skill(self):
+ couple_to_nllh_skill = {}
+ for couple, couple_study in self.couple_to_study.items():
+ skill = self.compute_skill(couple_study=couple_study)
+ nllh_skill = -np.log(skill)
+ couple_to_nllh_skill[couple] = nllh_skill
+ return couple_to_nllh_skill
+
+ def compute_skill(self, couple_study):
+ raise NotImplementedError
+
+ @property
+ def couple_to_nllh_interdependence(self):
+ couple_to_nllh_interdependence = {}
+ for couple, couple_study in self.couple_to_study.items():
+ interdependence = self.compute_interdependence(couple_study=couple_study)
+ nllh_interdependence = -np.log(interdependence)
+ couple_to_nllh_interdependence[couple] = nllh_interdependence
+ return couple_to_nllh_interdependence
+
+ def compute_interdependence(self, couple_study):
+ raise NotImplementedError
diff --git a/projects/projected_swe/weight_solver/indicator.py b/projects/projected_swe/weight_solver/indicator.py
new file mode 100644
index 0000000000000000000000000000000000000000..1507f8a295e8aed4c79a8b0dde7906791d364dd0
--- /dev/null
+++ b/projects/projected_swe/weight_solver/indicator.py
@@ -0,0 +1,19 @@
+class AbstractIndicator(object):
+
+ @classmethod
+ def get_indicator(cls, study, bootstrap=False):
+ raise NotImplementedError
+
+
+class AnnualMaximaMeanIndicator(AbstractIndicator):
+
+ @classmethod
+ def get_indicator(cls, study, bootstrap=False):
+ pass
+
+
+class ReturnLevelIndicator(AbstractIndicator):
+
+ @classmethod
+ def get_indicator(cls, study, bootstrap=False):
+ pass
diff --git a/projects/projected_swe/weight_solver/knutti_weight_solver.py b/projects/projected_swe/weight_solver/knutti_weight_solver.py
new file mode 100644
index 0000000000000000000000000000000000000000..b1b2a651938dd13ef701a7786431f1e3080e1d4f
--- /dev/null
+++ b/projects/projected_swe/weight_solver/knutti_weight_solver.py
@@ -0,0 +1,49 @@
+import numpy as np
+from projects.projected_swe.weight_solver.abtract_weight_solver import AbstractWeightSolver
+from projects.projected_swe.weight_solver.indicator import AbstractIndicator
+
+
+class KnuttiWeightSolver(AbstractWeightSolver):
+
+ def __init__(self, sigma_skill, sigma_interdependence, *args, **kwargs):
+ super().__init__(*args, **kwargs)
+ self.sigma_skill = sigma_skill
+ self.sigma_interdependence = sigma_interdependence
+
+ def compute_skill(self, couple_study):
+ raise self.compute_distance_between_two_study(self.observation_study, self.couple_to_study, self.sigma_skill)
+
+ def compute_interdependence(self, couple_study):
+ sum = 0
+ for other_couple_study in self.couple_to_study.values():
+ if other_couple_study is not couple_study:
+ sum += self.compute_distance_between_two_study(couple_study, other_couple_study, self.sigma_interdependence)
+ return 1 / (1 + sum)
+
+ def compute_distance_between_two_study(self, study_1, study_2, sigma):
+ difference = self.sum_of_differences(study_1, study_2)
+ return np.exp(-np.power(difference, 2 * sigma))
+
+ def sum_of_differences(self, study_1, study_2):
+ assert issubclass(self.indicator_class, AbstractIndicator)
+ return self.indicator_class.get_indicator(study_1) - self.indicator_class.get_indicator(study_2)
+
+
+class KnuttiWeightSolverWithBootstrapVersion1(KnuttiWeightSolver):
+
+ def sum_of_differences(self, study_1, study_2):
+ assert issubclass(self.indicator_class, AbstractIndicator)
+ bootstrap_study_1 = self.indicator_class.get_indicator(study_1, bootstrap=True)
+ bootstrap_study_2 = self.indicator_class.get_indicator(study_2, bootstrap=True)
+ differences = bootstrap_study_1 - bootstrap_study_2
+ return differences.sum()
+
+
+class KnuttiWeightSolverWithBootstrapVersion2(KnuttiWeightSolver):
+
+ def sum_of_differences(self, study_1, study_2):
+ assert issubclass(self.indicator_class, AbstractIndicator)
+ bootstrap_study_1 = self.indicator_class.get_indicator(study_1, bootstrap=True)
+ bootstrap_study_2 = self.indicator_class.get_indicator(study_2, bootstrap=True)
+ differences = np.subtract.outer(bootstrap_study_1, bootstrap_study_2)
+ return differences.sum()
diff --git a/projects/projected_swe/weight_solver/zhu_weight_solver.py b/projects/projected_swe/weight_solver/zhu_weight_solver.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391