diff --git a/extreme_data/meteo_france_data/scm_models_data/utils_function.py b/extreme_data/meteo_france_data/scm_models_data/utils_function.py
index 55440cde70d77ff77ca30c79005a939a1e39b8c2..707188f3ec3f873beaabf526e297d7026b86e11b 100644
--- a/extreme_data/meteo_france_data/scm_models_data/utils_function.py
+++ b/extreme_data/meteo_france_data/scm_models_data/utils_function.py
@@ -67,7 +67,6 @@ class ReturnLevelBootstrap(object):
idxs = list(range(self.nb_bootstrap))
if multiprocess is None:
- print('multiprocessing batch')
with Pool(NB_CORES) as p:
batchsize = math.ceil(AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP / NB_CORES)
diff --git a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
index 168d7a10e4fc0f2ca728cd7618e7ee4a5d626044..335aeb358e7a8b398a1e09853f6d720b924f772b 100644
--- a/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
+++ b/extreme_fit/estimator/margin_estimator/abstract_margin_estimator.py
@@ -66,8 +66,8 @@ class LinearMarginEstimator(AbstractMarginEstimator):
maxima_values = self.dataset.maxima_gev(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'
+ assert len(maximum) == 1, \
+ 'So far, only one observation for each coordinate, but code would be easy to change'
maximum = maximum[0]
gev_params = self.function_from_fit.get_params(coordinate, is_transformed=True)
p = gev_params.density(maximum)
diff --git a/extreme_fit/estimator/margin_estimator/utils.py b/extreme_fit/estimator/margin_estimator/utils.py
index 4742aa0cd9c471d26c60f8f0f3fd33024c9fa2ed..5a516f5f901f447931b12d950a344f4192d6673b 100644
--- a/extreme_fit/estimator/margin_estimator/utils.py
+++ b/extreme_fit/estimator/margin_estimator/utils.py
@@ -53,5 +53,6 @@ def _fitted_stationary_gev(fit_method, model_class, starting_year, x_gev):
gev_param.param_name_to_confidence_interval = param_name_to_confidence_interval
# Warning
if not -0.5 < gev_param.shape < 0.5:
- warnings.warn('fitted shape parameter is outside physical bounds {}'.format(gev_param.shape))
+ pass
+ # warnings.warn('fitted shape parameter is outside physical bounds {}'.format(gev_param.shape))
return estimator, gev_param
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 cf17d088a852798791d07780702a0b0a50ff7658..e938e38649a685d5d6ed8607c520e160bd055707 100644
--- a/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
+++ b/projects/altitude_spatial_model/altitudes_fit/main_altitudes_studies.py
@@ -52,7 +52,7 @@ def main():
elif fast:
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
massif_names = ['Vanoise', 'Haute-Maurienne', 'Vercors'][:1]
- altitudes_list = altitudes_for_groups[1:2]
+ altitudes_list = altitudes_for_groups[2:3]
else:
massif_names = None
altitudes_list = altitudes_for_groups[:]
@@ -81,13 +81,13 @@ def main_loop(altitudes_list, massif_names, seasons, study_classes, model_must_p
def plot_visualizers(massif_names, visualizer_list):
- # plot_histogram_all_models_against_altitudes(massif_names, visualizer_list)
- plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list)
+ plot_histogram_all_models_against_altitudes(massif_names, visualizer_list)
+ plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list, with_significance=True)
# plot_shoe_plot_ratio_interval_size_against_altitude(massif_names, visualizer_list)
for relative in [True, False]:
plot_shoe_plot_changes_against_altitude(massif_names, visualizer_list, relative=relative)
- plot_coherence_curves(massif_names, visualizer_list)
- # plot_coherence_curves(['Vanoise'], visualizer_list)
+ # plot_coherence_curves(massif_names, visualizer_list)
+ plot_coherence_curves(['Vanoise'], visualizer_list)
pass
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 e3a4c4f2cb3a5e01e7e9618a2fcd8416337d01bb..f49d5ac33fa2a850d77aa0cde220ffd4abd3b101 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
@@ -220,8 +220,8 @@ class AltitudesStudiesVisualizerForNonStationaryModels(StudyVisualizer):
@property
def add_colorbar(self):
- return True
- # return isinstance(self.altitude_group, (VeyHighAltitudeGroup, MidAltitudeGroup))
+ # return True
+ return isinstance(self.altitude_group, (VeyHighAltitudeGroup, MidAltitudeGroup))
def plot_against_years(self, method_name, order):
ax = plt.gca()
diff --git a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/one_fold_fit.py b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/one_fold_fit.py
index 45c6572204982486f94a8d37dfa07171e4b44659..93ce1c0b6ae2f3c554d4b7427d563444de2c8708 100644
--- a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/one_fold_fit.py
+++ b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/one_fold_fit.py
@@ -142,6 +142,11 @@ class OneFoldFit(object):
@cached_property
def sorted_estimators(self):
estimators = list(self.model_class_to_estimator.values())
+ # print(self.massif_name)
+ # print(self.altitude_group)
+ # for estimator in estimators:
+ # print(estimator.margin_model)
+ # print(estimator.aic())
sorted_estimators = sorted([estimator for estimator in estimators], key=lambda e: e.aic())
return sorted_estimators
@@ -154,27 +159,13 @@ class OneFoldFit(object):
# and self.sensitivity_of_fit_test_last_years(e)
]
else:
- return self._sorted_estimators_without_stationary
+ assert len(self.sorted_estimators) == len(self.models_classes)
+ return self.sorted_estimators
@property
def has_at_least_one_valid_model(self):
return len(self.sorted_estimators_with_stationary) > 0
- @cached_property
- def _sorted_estimators_without_stationary(self):
- return [e for e in self.sorted_estimators if not isinstance(e.margin_model, StationaryAltitudinal)]
-
- @cached_property
- def sorted_estimators_without_stationary(self):
- if self.only_models_that_pass_goodness_of_fit_test:
- return [e for e in self._sorted_estimators_without_stationary if self.goodness_of_fit_test(e)]
- else:
- return self._sorted_estimators_without_stationary
-
- @property
- def has_at_least_one_valid_non_stationary_model(self):
- return len(self.sorted_estimators_without_stationary) > 0
-
@property
def model_class_to_estimator_with_finite_aic(self):
return {type(estimator.margin_model): estimator for estimator in self.sorted_estimators}
@@ -184,10 +175,6 @@ class OneFoldFit(object):
if self.best_estimator_minimizes_total_aic and self.best_estimator_class_for_total_aic is not None:
return self.model_class_to_estimator[self.best_estimator_class_for_total_aic]
else:
- # Without stationary
- # if self.has_at_least_one_valid_non_stationary_model:
- # best_estimator = self.sorted_estimators_without_stationary[0]
- # return best_estimator
# With stationary
if self.has_at_least_one_valid_model:
best_estimator = self.sorted_estimators_with_stationary[0]
@@ -428,7 +415,6 @@ class OneFoldFit(object):
idxs = list(range(AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP))
if multiprocess is None:
- print('multiprocessing batch')
start = time.time()
with Pool(NB_CORES) as p:
batchsize = math.ceil(AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP / NB_CORES)
diff --git a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py
index 6ebcbd94da8c0a415c5261e94278a751abba583d..2a50df32b9783491ae211e96f6930dfd589f572f 100644
--- a/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py
+++ b/projects/altitude_spatial_model/altitudes_fit/one_fold_analysis/plot_total_aic.py
@@ -14,9 +14,9 @@ from projects.exceeding_snow_loads.utils import dpi_paper1_figure
def plots(visualizer: AltitudesStudiesVisualizerForNonStationaryModels):
- # visualizer.plot_shape_map()
+ visualizer.plot_shape_map()
visualizer.plot_moments()
- # visualizer.plot_qqplots()
+ visualizer.plot_qqplots()
# for std in [True, False]:
# visualizer.studies.plot_mean_maxima_against_altitude(std=std)
diff --git a/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py b/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py
index ca2a3b01d69cf886a1335867a167b3205fd3ac20..0bc0683c249e60f9c2994b8e9d0a1405fab91d1e 100644
--- a/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py
+++ b/projects/altitude_spatial_model/altitudes_fit/plots/plot_histogram_altitude_studies.py
@@ -115,7 +115,7 @@ def plot_histogram_all_trends_against_altitudes(massif_names, visualizer_list: L
ax.tick_params(axis='both', which='major', labelsize=labelsize)
ax.set_xticks(x)
ax.yaxis.grid()
- ax.set_ylim([0, 89])
+ ax.set_ylim([0, 79])
ax.set_ylim(bottom=0)
ax.set_xticklabels([v.altitude_group.formula_upper for v in visualizer_list])