diff --git a/experiment/eurocode_data/departementalpesfrancaises.py b/experiment/eurocode_data/departementalpesfrancaises.py
index d36d9f41eb9dfc7c229ee3bc9a80fb9005bd9967..4b30db0599a1e7e8d7560ea46b6b5a63c4b9023e 100644
--- a/experiment/eurocode_data/departementalpesfrancaises.py
+++ b/experiment/eurocode_data/departementalpesfrancaises.py
@@ -51,11 +51,6 @@ class Drome(AbstractDepartementAlpesFrancaises):
super().__init__(C2)
-"""
-Quand c'est à cheval, je mets les deux massifs
-Quand juste un bout du massif est dans un autre departement
-(Chartreuse, Belledonne sont un peu en Savoie
-"""
massif_name_to_departements = {
'Chablais': [HauteSavoie],
'Aravis': [HauteSavoie, Savoie],
@@ -63,8 +58,8 @@ massif_name_to_departements = {
'Bauges': [HauteSavoie, Savoie],
'Beaufortain': [HauteSavoie, Savoie],
'Haute-Tarentaise': [Savoie],
- 'Chartreuse': [Isere],
- 'Belledonne': [Isere],
+ 'Chartreuse': [Isere, Savoie],
+ 'Belledonne': [Isere, Savoie],
'Maurienne': [Savoie],
'Vanoise': [Savoie],
'Haute-Maurienne': [Savoie],
diff --git a/experiment/meteo_france_data/scm_models_data/abstract_study.py b/experiment/meteo_france_data/scm_models_data/abstract_study.py
index 121eec14347aaffade3929a54215abfccca1ea06..424398e0fc25bf37f87854d6d096fa1b9d401c68 100644
--- a/experiment/meteo_france_data/scm_models_data/abstract_study.py
+++ b/experiment/meteo_france_data/scm_models_data/abstract_study.py
@@ -229,7 +229,7 @@ class AbstractStudy(object):
def visualize_study(cls, ax=None, massif_name_to_value: Union[None, Dict[str, float]] = None, show=True, fill=True,
replace_blue_by_white=True,
label=None, add_text=False, cmap=None, vmax=100, vmin=0,
- default_color_for_missing_massif='grey',
+ default_color_for_missing_massif='gainsboro',
default_color_for_nan_values='w',
massif_name_to_color=None,
show_label=True,
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py
index 4bc1d621192865c7e484e12392130092a1c87a2b..11fb476c616337024b59fcd022bf0693293c7b5c 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/main_study_visualizer.py
@@ -24,7 +24,7 @@ SCM_STUDY_NAME_TO_SCM_STUDY = dict(zip(SCM_STUDIES_NAMES, SCM_STUDIES))
SCM_STUDY_CLASS_TO_ABBREVIATION = {
SafranSnowfall: 'SF3',
CrocusTotalSwe: 'TSWE',
- CrocusRecentSwe: 'RSWE',
+ CrocusRecentSwe: 'SWE3',
CrocusDepth: 'SD',
}
diff --git a/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py b/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py
index 4e1b2427d660924c5e51acb65736c86c06b4fe22..5ee81c4f3b970006e3b8a686dd380e3e4659775e 100644
--- a/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py
+++ b/experiment/meteo_france_data/stations_data/visualization/comparisons_visualization/comparisons_visualization.py
@@ -14,7 +14,6 @@ from experiment.meteo_france_data.scm_models_data.visualization.study_visualizat
VisualizationParameters
from experiment.meteo_france_data.stations_data.comparison_analysis import ComparisonAnalysis, MASSIF_COLUMN_NAME, \
REANALYSE_STR, ALTITUDE_COLUMN_NAME, STATION_COLUMN_NAME
-from experiment.trend_analysis.univariate_test.abstract_gev_trend_test import GevLocationChangePointTest
from experiment.trend_analysis.univariate_test.abstract_univariate_test import AbstractUnivariateTest
from experiment.trend_analysis.univariate_test.utils import compute_gev_change_point_test_results
from extreme_estimator.extreme_models.result_from_fit import ResultFromIsmev
@@ -259,21 +258,3 @@ class ComparisonsVisualization(VisualizationParameters):
ax.grid()
ax.plot(years, maxima, label=label, color=plot_color)
return ordered_dict
-
- def visualize_gev(self):
- return self._visualize_main(self.plot_gev)
-
- def plot_gev(self, ax, ax2, years, maxima, label, plot_color):
- # todo should I normalize here ?
- # fit gev
- data = maxima
- res = safe_run_r_estimator(function=r('gev.fit'), xdat=ro.FloatVector(data),
- use_start=True)
- res = ResultFromIsmev(res, {})
- gev_params = res.constant_gev_params
-
- lim = 1.5 * max(data)
- x = np.linspace(0, lim, 1000)
- y = gev_params.density(x)
- # display the gev distribution that was obtained
- ax.plot(x, y, label=label, color=plot_color)
diff --git a/experiment/paper1_steps/hard extreme evolution - annual maxima/main1_good_stationary_gev_fit.py b/experiment/paper1_steps/hard extreme evolution - annual maxima/main1_good_stationary_gev_fit.py
index 0cfb9bcb7e9af08f6615c7de2f6a75093beaaef0..935d017c241bc17f1c98add8b6280387e9f21203 100644
--- a/experiment/paper1_steps/hard extreme evolution - annual maxima/main1_good_stationary_gev_fit.py
+++ b/experiment/paper1_steps/hard extreme evolution - annual maxima/main1_good_stationary_gev_fit.py
@@ -8,14 +8,15 @@ from experiment.meteo_france_data.scm_models_data.visualization.study_visualizat
def maxima_analysis():
save_to_file = False
only_first_one = False
- durand_altitude = [900, 1500, 2100, 2700]
+ durand_altitude = [900, 1500, 1800, 2100, 2700][2:-2]
altitudes = durand_altitude
study_classes = [CrocusRecentSwe][:]
for study in study_iterator_global(study_classes, only_first_one=only_first_one, altitudes=altitudes):
study_visualizer = StudyVisualizer(study, save_to_file=save_to_file,
verbose=True,
multiprocessing=True)
- study_visualizer.visualize_summary_of_annual_values_and_stationary_gev_fit()
+ # study_visualizer.visualize_summary_of_annual_values_and_stationary_gev_fit()
+ study_visualizer.visualize_all_mean_and_max_graphs()
if __name__ == '__main__':
diff --git a/experiment/paper1_steps/hard extreme evolution - annual maxima/main3_non_stationary_strength_evolution.py b/experiment/paper1_steps/hard extreme evolution - annual maxima/main3_non_stationary_strength_evolution.py
index 5ec783b15fa436167a242d2c644f6bb435c347c1..29713ba1b35b6ada4e64ae01fb2e2f864a3e3ff5 100644
--- a/experiment/paper1_steps/hard extreme evolution - annual maxima/main3_non_stationary_strength_evolution.py
+++ b/experiment/paper1_steps/hard extreme evolution - annual maxima/main3_non_stationary_strength_evolution.py
@@ -13,7 +13,7 @@ from experiment.paper1_steps.utils import get_full_altitude_visualizer, FULL_ALT
def main_fast_spatial_risk_evolution():
- for altitude in FULL_ALTITUDES[-1:]:
+ for altitude in [1800]:
vizualiser = get_full_altitude_visualizer(Altitude_Hypercube_Year_Visualizer, altitude=altitude,
exact_starting_year=1958, reduce_strength_array=True,
trend_test_class=GevLocationAndScaleTrendTest)
@@ -31,8 +31,8 @@ def main_full_spatial_risk_evolution():
def main_run():
- main_full_spatial_risk_evolution()
- # main_fast_spatial_risk_evolution()
+ # main_full_spatial_risk_evolution()
+ main_fast_spatial_risk_evolution()
if __name__ == '__main__':
diff --git a/experiment/trend_analysis/univariate_test/abstract_gev_trend_test.py b/experiment/trend_analysis/univariate_test/abstract_gev_trend_test.py
index e3584e95a4ee2b92cf8db477b3fccd6bab8038e4..456390e33ffeee82c0db89d5f40fbeafcd9127da 100644
--- a/experiment/trend_analysis/univariate_test/abstract_gev_trend_test.py
+++ b/experiment/trend_analysis/univariate_test/abstract_gev_trend_test.py
@@ -113,14 +113,18 @@ class AbstractGevTrendTest(AbstractUnivariateTest):
@property
def non_stationary_constant_gev_params(self) -> GevParams:
- return self.non_stationary_estimator.result_from_fit.constant_gev_params
+ # Constant parameters correspond to the gev params in 1958
+ return self.non_stationary_estimator.margin_function_fitted.get_gev_params(coordinate=np.array([1958]),
+ is_transformed=False)
@property
def test_trend_slope_strength(self):
if self.crashed:
return 0.0
else:
+ # Compute the slope strength
slope = self._slope_strength()
+ # Delta T must in the same unit as were the parameter of slope mu1 and sigma1
slope *= self.nb_years_for_quantile_evolution * self.coordinates.transformed_distance_between_two_successive_years[0]
return slope
diff --git a/experiment/trend_analysis/univariate_test/abstract_univariate_test.py b/experiment/trend_analysis/univariate_test/abstract_univariate_test.py
index 7381e71ca383ac6645ccd34a18ecbd3d11ff9338..7cbbf78e57b2deba5571785eb8db6f2829625dbc 100644
--- a/experiment/trend_analysis/univariate_test/abstract_univariate_test.py
+++ b/experiment/trend_analysis/univariate_test/abstract_univariate_test.py
@@ -61,8 +61,8 @@ class AbstractUnivariateTest(object):
d[cls.ALL_TREND] = 'k-'
d[cls.NON_SIGNIFICATIVE_TREND] = 'b-'
# d[cls.SIGNIFICATIVE_ALL_TREND] = 'k-'
- d[cls.SIGNIFICATIVE_POSITIVE_TREND] = 'g-'
- d[cls.SIGNIFICATIVE_NEGATIVE_TREND] = 'r-'
+ d[cls.SIGNIFICATIVE_POSITIVE_TREND] = 'darkgreen-'
+ d[cls.SIGNIFICATIVE_NEGATIVE_TREND] = 'darkred-'
# d[cls.NO_TREND] = 'k--'
return d
diff --git a/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py b/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py
index 90d95ba18320051cd352888a2c79aa9d4316add9..156558e1396ff8a3319100403e9f70067c5bd3b1 100644
--- a/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py
+++ b/extreme_estimator/extreme_models/margin_model/temporal_linear_margin_model.py
@@ -37,6 +37,10 @@ class TemporalLinearMarginModel(LinearMarginModel):
def shl(self):
return get_null()
+ @property
+ def siglink(self):
+ return r('identity')
+
class StationaryStationModel(TemporalLinearMarginModel):
@@ -64,6 +68,16 @@ class NonStationaryScaleStationModel(TemporalLinearMarginModel):
return 1
+class NonStationaryLogScaleStationModel(NonStationaryScaleStationModel):
+
+ def load_margin_functions(self, gev_param_name_to_dims=None):
+ super().load_margin_functions({GevParams.SCALE: [self.coordinates.idx_temporal_coordinates]})
+
+ @property
+ def siglink(self):
+ return r('exp')
+
+
class NonStationaryShapeStationModel(TemporalLinearMarginModel):
def load_margin_functions(self, gev_param_name_to_dims=None):
diff --git a/extreme_estimator/extreme_models/result_from_fit.py b/extreme_estimator/extreme_models/result_from_fit.py
index 78d9d83a18c050836090e3dbae55fb615df40147..c3170e183d625dd17605b9c0fd9882d8996d553a 100644
--- a/extreme_estimator/extreme_models/result_from_fit.py
+++ b/extreme_estimator/extreme_models/result_from_fit.py
@@ -48,10 +48,6 @@ class ResultFromFit(object):
def convergence(self) -> str:
raise NotImplementedError
- @property
- def constant_gev_params(self) -> GevParams:
- raise NotImplementedError
-
class ResultFromIsmev(ResultFromFit):
@@ -79,12 +75,6 @@ class ResultFromIsmev(ResultFromFit):
i += 1
return coef_dict
- @property
- def constant_gev_params(self) -> GevParams:
- params = {k.split('Coeff1')[0]: v for k, v in self.margin_coef_dict.items()
- if 'Coeff1' in k and 'temp' not in k}
- return GevParams.from_dict(params)
-
@property
def all_parameters(self):
return self.margin_coef_dict
diff --git a/test/test_extreme_estimator/test_margin_fits/test_gev/test_gev_temporal.py b/test/test_extreme_estimator/test_margin_fits/test_gev/test_gev_temporal.py
index 8ffe351324c74f4df0d402ca2260899fb77a1da6..f0a17fb376c709cb3f4e402a18050ed6e3de6f4d 100644
--- a/test/test_extreme_estimator/test_margin_fits/test_gev/test_gev_temporal.py
+++ b/test/test_extreme_estimator/test_margin_fits/test_gev/test_gev_temporal.py
@@ -33,8 +33,6 @@ class TestGevTemporal(unittest.TestCase):
df2 = pd.DataFrame(data=np.array(r['x_gev']), index=df.index)
observations = AbstractSpatioTemporalObservations(df_maxima_gev=df2)
self.dataset = AbstractDataset(observations=observations, coordinates=self.coordinates)
- #
- self.margin_models = load_non_stationary_temporal_margin_models(self.coordinates)
def test_gev_temporal_margin_fit_stationary(self):
# Create estimator
@@ -49,7 +47,8 @@ class TestGevTemporal(unittest.TestCase):
def test_gev_temporal_margin_fit_nonstationary(self):
# Create estimator
- for margin_model in self.margin_models:
+ margin_models = load_non_stationary_temporal_margin_models(self.coordinates)
+ for margin_model in margin_models:
# margin_model = NonStationaryLocationStationModel(self.coordinates)
estimator = LinearMarginEstimator(self.dataset, margin_model)
estimator.fit()