diff --git a/extreme_data/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py b/extreme_data/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py
index 662212c08cc1a0cf52a8506ebeefb02d05c274fd..2c4068f30cf5ecebe31974e40243c7f456951edd 100644
--- a/extreme_data/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py
+++ b/extreme_data/meteo_france_data/scm_models_data/visualization/create_shifted_cmap.py
@@ -77,6 +77,7 @@ def imshow_shifted(ax, param_name, values, visualization_extend, mask_2D=None):
def ticks_values_and_labels_for_percentages(graduation, max_abs_change):
+ assert max_abs_change != np.inf
positive_ticks = []
tick = graduation
while tick < max_abs_change:
@@ -86,7 +87,9 @@ def ticks_values_and_labels_for_percentages(graduation, max_abs_change):
ticks_values = [((t / max_abs_change) + 1) / 2 for t in all_ticks_labels]
return ticks_values, all_ticks_labels
+
def ticks_values_and_labels_for_positive_value(graduation, max_abs_change):
+ assert max_abs_change != np.inf
positive_ticks = []
tick = 0
while tick < max_abs_change:
diff --git a/extreme_trend/abstract_gev_trend_test.py b/extreme_trend/abstract_gev_trend_test.py
index 46224e060436a944e7400c618d81a091972c886c..b7e5d16cce3dfd82fb0a8425fa2ebbfddc471087 100644
--- a/extreme_trend/abstract_gev_trend_test.py
+++ b/extreme_trend/abstract_gev_trend_test.py
@@ -139,10 +139,12 @@ class AbstractGevTrendTest(object):
AbstractCoordinates.COORDINATE_T)
@cached_property
- def unconstrained_estimator_gev_params(self) -> GevParams:
- # Constant parameters correspond to the gev params in 1958
- return self.unconstrained_estimator.function_from_fit.get_params(coordinate=np.array([1958]),
- is_transformed=False)
+ def unconstrained_estimator_gev_params_last_year(self) -> GevParams:
+ return self.get_unconstrained_gev_params(year=self.years[-1])
+
+ @cached_property
+ def unconstrained_estimator_gev_params_first_year(self) -> GevParams:
+ return self.get_unconstrained_gev_params(year=self.years[0])
def time_derivative_times_years(self, nb_years):
# Compute the slope strength
@@ -186,7 +188,7 @@ class AbstractGevTrendTest(object):
@property
def test_trend_constant_quantile(self):
- return self.unconstrained_estimator_gev_params.quantile(p=self.quantile_level)
+ return self.unconstrained_estimator_gev_params_last_year.quantile(p=self.quantile_level)
# Some class properties for display purpose
@@ -471,7 +473,8 @@ class AbstractGevTrendTest(object):
def unconstrained_average_mean_value(self, year_min, year_max) -> float:
mean_values = []
for year in range(year_min, year_max + 1):
- mean = self.get_unconstrained_gev_params(year).mean
+ gev_params = self.get_unconstrained_gev_params(year)
+ mean = gev_params.mean
mean_values.append(mean)
average_mean_value = np.mean(mean_values)
assert isinstance(average_mean_value, float)
diff --git a/extreme_trend/trend_test_one_parameter/gev_trend_test_one_parameter.py b/extreme_trend/trend_test_one_parameter/gev_trend_test_one_parameter.py
index e0f942a18800346c9b742e072bbc20c8ca04a16c..49474239ea96ba960edab4f8f05cef6285049517 100644
--- a/extreme_trend/trend_test_one_parameter/gev_trend_test_one_parameter.py
+++ b/extreme_trend/trend_test_one_parameter/gev_trend_test_one_parameter.py
@@ -73,12 +73,12 @@ class GevLocationTrendTest(GevTrendTestOneParameterAgainstStationary):
fit_method=fit_method)
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(p=self.quantile_level,
- mu1=self.non_stationary_linear_coef)
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(p=self.quantile_level,
+ mu1=self.non_stationary_linear_coef)
@property
def mean_difference_same_sign_as_slope_strenght(self) -> bool:
- zeta0 = self.unconstrained_estimator_gev_params.shape
+ zeta0 = self.unconstrained_estimator_gev_params_last_year.shape
mean_difference = self.mean_difference(zeta0=zeta0, mu1=self.non_stationary_linear_coef)
return self.same_sign(mean_difference, self._slope_strength())
@@ -100,13 +100,13 @@ class GevScaleTrendTest(GevTrendTestOneParameterAgainstStationary):
fit_method=fit_method)
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(
p=self.quantile_level,
sigma1=self.non_stationary_linear_coef)
@property
def mean_difference_same_sign_as_slope_strenght(self) -> bool:
- zeta0 = self.unconstrained_estimator_gev_params.shape
+ zeta0 = self.unconstrained_estimator_gev_params_last_year.shape
mean_difference = self.mean_difference(zeta0=zeta0, sigma1=self.non_stationary_linear_coef)
return self.same_sign(mean_difference, self._slope_strength())
diff --git a/extreme_trend/trend_test_one_parameter/gumbel_trend_test_one_parameter.py b/extreme_trend/trend_test_one_parameter/gumbel_trend_test_one_parameter.py
index 79e8f4947a70d570da7467152440dae5af586d14..b9a066062694f56c4813897137a07c6fa4ed1fc2 100644
--- a/extreme_trend/trend_test_one_parameter/gumbel_trend_test_one_parameter.py
+++ b/extreme_trend/trend_test_one_parameter/gumbel_trend_test_one_parameter.py
@@ -79,8 +79,8 @@ class GumbelLocationTrendTest(GevTrendTestOneParameterAgainstStationary):
return 3
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(p=self.quantile_level,
- mu1=self.non_stationary_linear_coef)
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(p=self.quantile_level,
+ mu1=self.non_stationary_linear_coef)
@classproperty
def label(self):
@@ -103,7 +103,7 @@ class GumbelScaleTrendTest(GevTrendTestOneParameterAgainstStationary):
fit_method=fit_method)
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(
p=self.quantile_level,
sigma1=self.non_stationary_linear_coef)
diff --git a/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py b/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py
index dc411f3a0e68dec565f13a5b7db8ff333916edc3..04d780b076163fb7bb2c246f5d99a2a87315a905 100644
--- a/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py
+++ b/extreme_trend/trend_test_three_parameters/gev_trend_test_three_parameters.py
@@ -50,9 +50,9 @@ class GevLocationAndScaleTrendTestAgainstGumbel(GevTrendTestThreeParameters):
return self.get_non_stationary_linear_coef(param_name=GevParams.SCALE)
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(p=self.quantile_level,
- mu1=self.mu1,
- sigma1=self.sigma1)
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(p=self.quantile_level,
+ mu1=self.mu1,
+ sigma1=self.sigma1)
@classproperty
def label(self):
diff --git a/extreme_trend/trend_test_two_parameters/gev_trend_test_two_parameters.py b/extreme_trend/trend_test_two_parameters/gev_trend_test_two_parameters.py
index 7830fb4cf19bf3a8e77881b86e25fae68edcf8fd..a7f49d72577afb1f441a542ce096f32ad9cc9cd5 100644
--- a/extreme_trend/trend_test_two_parameters/gev_trend_test_two_parameters.py
+++ b/extreme_trend/trend_test_two_parameters/gev_trend_test_two_parameters.py
@@ -66,13 +66,13 @@ class GevLocationAndScaleTrendTest(GevTrendTestTwoParametersAgainstGev):
return self.get_non_stationary_linear_coef(param_name=GevParams.SCALE)
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(p=self.quantile_level,
- mu1=self.mu1,
- sigma1=self.sigma1)
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(p=self.quantile_level,
+ mu1=self.mu1,
+ sigma1=self.sigma1)
@property
def mean_difference_same_sign_as_slope_strenght(self) -> bool:
- zeta0 = self.unconstrained_estimator_gev_params.shape
+ zeta0 = self.unconstrained_estimator_gev_params_last_year.shape
mean_difference = self.mean_difference(zeta0=zeta0, mu1=self.mu1, sigma1=self.sigma1)
return self.same_sign(mean_difference, self._slope_strength())
diff --git a/extreme_trend/trend_test_two_parameters/gumbel_test_two_parameters.py b/extreme_trend/trend_test_two_parameters/gumbel_test_two_parameters.py
index db57fb579102a4133d60d0e48b4128fa88ccba61..426e593d45edcb4ce16a47472a5cee6d7669841e 100644
--- a/extreme_trend/trend_test_two_parameters/gumbel_test_two_parameters.py
+++ b/extreme_trend/trend_test_two_parameters/gumbel_test_two_parameters.py
@@ -31,9 +31,9 @@ class GumbelLocationAndScaleTrendTest(GevTrendTestTwoParameters):
return self.get_non_stationary_linear_coef(param_name=GevParams.SCALE)
def _slope_strength(self):
- return self.unconstrained_estimator_gev_params.time_derivative_of_return_level(p=self.quantile_level,
- mu1=self.mu1,
- sigma1=self.sigma1)
+ return self.unconstrained_estimator_gev_params_last_year.time_derivative_of_return_level(p=self.quantile_level,
+ mu1=self.mu1,
+ sigma1=self.sigma1)
@classproperty
def label(self):
return super().label % '\\mu_1, \\sigma_1'
diff --git a/extreme_trend/visualizers/study_visualizer_for_non_stationary_trends.py b/extreme_trend/visualizers/study_visualizer_for_non_stationary_trends.py
index 1376bb39104e9c447a39b335eb503035f3e221b3..c426001f444d8e119517f96cc7e10a7e7e38a4f8 100644
--- a/extreme_trend/visualizers/study_visualizer_for_non_stationary_trends.py
+++ b/extreme_trend/visualizers/study_visualizer_for_non_stationary_trends.py
@@ -169,7 +169,8 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
if self.select_only_acceptable_shape_parameter:
acceptable_shape_parameter = lambda s: -0.5 <= s <= 0.5 # physically acceptable prior
all_trend_test = [t for t in all_trend_test
- if acceptable_shape_parameter(t.unconstrained_estimator_gev_params.shape)]
+ if (acceptable_shape_parameter(t.unconstrained_estimator_gev_params_last_year.shape)
+ and acceptable_shape_parameter(t.unconstrained_estimator_gev_params_first_year.shape))]
sorted_trend_test = sorted(all_trend_test, key=lambda t: t.aic)
# Extract the stationary or non-stationary model that minimized AIC
@@ -424,14 +425,14 @@ class StudyVisualizerForNonStationaryTrends(StudyVisualizer):
psnow = self.massif_name_to_psnow[massif_name]
trend_test = self.massif_name_to_trend_test_that_minimized_aic[massif_name]
trend_test.intensity_plot_wrt_standard_gumbel_simple(massif_name, self.altitude, color, psnow)
- self.plot_name = 'intensity_plot_{}_{}_{}_{}'.format(self.altitude, massif_name, psnow, trend_test.unconstrained_estimator_gev_params.shape)
+ self.plot_name = 'intensity_plot_{}_{}_{}_{}'.format(self.altitude, massif_name, psnow, trend_test.unconstrained_estimator_gev_params_last_year.shape)
self.show_or_save_to_file(add_classic_title=False, no_title=True)
plt.close()
def qqplot(self, massif_name, color=None):
trend_test = self.massif_name_to_trend_test_that_minimized_aic[massif_name]
trend_test.qqplot_wrt_standard_gumbel(massif_name, self.altitude)
- self.plot_name = 'qpplot_plot_{}_{}_{}'.format(self.altitude, massif_name, trend_test.unconstrained_estimator_gev_params.shape)
+ self.plot_name = 'qpplot_plot_{}_{}_{}'.format(self.altitude, massif_name, trend_test.unconstrained_estimator_gev_params_last_year.shape)
self.show_or_save_to_file(add_classic_title=False, no_title=True)
plt.close()
diff --git a/extreme_trend/visualizers/study_visualizer_for_shape_repartition.py b/extreme_trend/visualizers/study_visualizer_for_shape_repartition.py
index 392cedd2ca087d2ee56e7ac10cae441edf95bd09..901754e8e7ec919aec5fec866f9a180db286f832 100644
--- a/extreme_trend/visualizers/study_visualizer_for_shape_repartition.py
+++ b/extreme_trend/visualizers/study_visualizer_for_shape_repartition.py
@@ -14,7 +14,7 @@ class StudyVisualizerForShape(StudyVisualizerForNonStationaryTrends):
@cached_property
def massif_name_to_unconstrained_shape_parameter(self):
- return {m: t.unconstrained_estimator_gev_params.shape
+ return {m: t.unconstrained_estimator_gev_params_last_year.shape
for m, t in self.massif_name_to_trend_test_that_minimized_aic.items()}
@cached_property
diff --git a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py
index 4438841cb3519ad6b6ddddc045e4b2ed3b70ed3a..2fe80931b12ce361dd03caaa3d3d0b327bd63390 100644
--- a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py
+++ b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/main_snowfall_article.py
@@ -88,13 +88,14 @@ def major_result():
model_subsets_for_uncertainty = None
altitudes = paper_altitudes
# altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900]
- altitudes = [900, 1200, 1500, 1800]
- # draft_altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000]
+ # altitudes = [900, 1200, 1500, 1800][:2]
+ # altitudes = [2400, 2700][:2]
+ altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000]
# altitudes = draft_altitudes
for study_class in study_classes:
intermediate_result(altitudes, massif_names, model_subsets_for_uncertainty,
- uncertainty_methods, study_class)
+ uncertainty_methods, study_class, multiprocessing=True)
if __name__ == '__main__':
diff --git a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py
index 351a50c283ace71185fcc284ee1f7d00c26eb4a1..a074aad7b779344cddfb93492f5d0b9fc988a2f6 100644
--- a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py
+++ b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/study_visualizer_for_mean_values.py
@@ -77,19 +77,18 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
return massif_name_to_empirical_value
@cached_property
- def massif_name_to_model_mean(self):
- massif_name_to_model_value = {}
+ def massif_name_to_model_mean_last_year(self):
+ massif_name_to_model_value_last_year = {}
for massif_name, trend_test in self.massif_name_to_trend_test_that_minimized_aic.items():
- parameter_value = trend_test.unconstrained_average_mean_value(self.study.year_min, self.study.year_max)
- massif_name_to_model_value[massif_name] = parameter_value
- return massif_name_to_model_value
+ massif_name_to_model_value_last_year[massif_name] = trend_test.unconstrained_estimator_gev_params_last_year.mean
+ return massif_name_to_model_value_last_year
@cached_property
def massif_name_to_relative_difference_for_mean(self):
massif_name_to_relative_difference = {}
for massif_name in self.massif_name_to_trend_test_that_minimized_aic.keys():
e = self.massif_name_to_empirical_mean[massif_name]
- m = self.massif_name_to_model_mean[massif_name]
+ m = self.massif_name_to_model_mean_last_year[massif_name]
relative_diference = 100 * (m - e) / e
massif_name_to_relative_difference[massif_name] = relative_diference
return massif_name_to_relative_difference
diff --git a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/validation_plot.py b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/validation_plot.py
index 053570e21409e5b6393b11b4fb55a215ef38d9d4..354de6fe95cfe7ac799b3b18065aaa87a97d171f 100644
--- a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/validation_plot.py
+++ b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/validation_plot.py
@@ -1,3 +1,4 @@
+from multiprocessing import Pool
from typing import Dict
import matplotlib.pyplot as plt
@@ -8,25 +9,27 @@ from projects.contrasting_trends_in_snow_loads.article2_snowfall_versus_time_and
StudyVisualizerForMeanValues
from projects.ogorman.gorman_figures.figure1.study_visualizer_for_double_stationary_fit import \
StudyVisualizerForReturnLevelChange
+from root_utils import NB_CORES
def validation_plot(altitude_to_visualizer: Dict[int, StudyVisualizerForMeanValues], order_derivative=0):
# Plot the mean empirical, the mean parametric and the relative difference between the two
altitudes = list(altitude_to_visualizer.keys())
study_visualizer = list(altitude_to_visualizer.values())[0]
- altitude_to_relative_differences = {}
+ visualizers = list(altitude_to_visualizer.values())
if order_derivative == 0:
plot_function = plot_relative_difference_map_order_zero
else:
plot_function = plot_relative_difference_map_order_one
# Plot map for the repartition of the difference
+ altitude_to_relative_differences = {}
for altitude, visualizer in altitude_to_visualizer.items():
altitude_to_relative_differences[altitude] = plot_function(visualizer)
- study_visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
+ # study_visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
# # Shoe plot with respect to the altitude.
# plot_shoe_relative_differences_distribution(altitude_to_relative_differences, altitudes, study_visualizer,
# order_derivative)
- study_visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
+ # study_visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
plt.close()
@@ -53,11 +56,12 @@ def plot_relative_difference_map_order_zero(visualizer: StudyVisualizerForMeanVa
label = ' mean annual maxima of {} ({})'.format(SCM_STUDY_CLASS_TO_ABBREVIATION[type(study)], study.variable_unit)
# visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_empirical_mean,
# label='Empirical' + label, negative_and_positive_values=False)
- visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_model_mean,
+ visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_model_mean_last_year,
label='Model' + label, negative_and_positive_values=False, add_text=True)
# visualizer.plot_abstract_fast(massif_name_to_value=visualizer.massif_name_to_relative_difference_for_mean,
# label='Relative difference of the model mean w.r.t. the empirical mean \n'
# 'for the ' + label, graduation=1)
+ visualizer.show_or_save_to_file(add_classic_title=False, dpi=500)
return list(visualizer.massif_name_to_relative_difference_for_mean.values())
diff --git a/projects/exceeding_snow_loads/checks/qqplot/main_qqplot_for_big_shapes.py b/projects/exceeding_snow_loads/checks/qqplot/main_qqplot_for_big_shapes.py
index d39214fb460650861407913eb362e816717ecd13..459b93ebc1ed86bba8466188003de0435b694538 100644
--- a/projects/exceeding_snow_loads/checks/qqplot/main_qqplot_for_big_shapes.py
+++ b/projects/exceeding_snow_loads/checks/qqplot/main_qqplot_for_big_shapes.py
@@ -23,7 +23,7 @@ def get_tuple_ordered_by_shape(fast=False):
# Extract all the values
l = []
for a, v in altitude_to_visualizer.items():
- l.extend([(a, v, m, t.unconstrained_estimator_gev_params.shape) for m, t in
+ l.extend([(a, v, m, t.unconstrained_estimator_gev_params_last_year.shape) for m, t in
v.massif_name_to_trend_test_that_minimized_aic.items()])
# Sort them and keep the highest examples
l = sorted(l, key=lambda t: t[-1])
diff --git a/projects/exceeding_snow_loads/checks/without_maximum/study_visualizer_for_fit_witout_maximum.py b/projects/exceeding_snow_loads/checks/without_maximum/study_visualizer_for_fit_witout_maximum.py
index 31d9d5eba25126afa3cc0ac1829a0ab8cc7b763a..c33fb52e6f5d6f04b621acdb914ba6bdac353b60 100644
--- a/projects/exceeding_snow_loads/checks/without_maximum/study_visualizer_for_fit_witout_maximum.py
+++ b/projects/exceeding_snow_loads/checks/without_maximum/study_visualizer_for_fit_witout_maximum.py
@@ -40,7 +40,7 @@ class StudyVisualizerForFitWithoutMaximum(StudyVisualizerForNonStationaryTrends)
for massif_name, maximum in self.massif_name_to_maximum.items():
t = self.massif_name_to_trend_test_that_minimized_aic[massif_name]
msg = '{} {}m'.format(massif_name, self.study.altitude)
- upper_bound = t.unconstrained_estimator_gev_params.density_upper_bound
+ upper_bound = t.unconstrained_estimator_gev_params_last_year.density_upper_bound
if not np.isinf(upper_bound):
diff.append(upper_bound - maximum)
assert maximum <= upper_bound, msg
diff --git a/projects/exceeding_snow_loads/section_results/plot_selection_curves.py b/projects/exceeding_snow_loads/section_results/plot_selection_curves.py
index fde43a425ea11db9bead800bb4748ef87e0be13a..b31ed8952779ec957665b13f7c54b8fd1bbb13d4 100644
--- a/projects/exceeding_snow_loads/section_results/plot_selection_curves.py
+++ b/projects/exceeding_snow_loads/section_results/plot_selection_curves.py
@@ -2,7 +2,7 @@ from typing import Dict
import matplotlib.pyplot as plt
from extreme_data.meteo_france_data.scm_models_data.visualization.utils import create_adjusted_axes
-from projects.exceeding_snow_loads.utils import dpi_paper1_figure
+from projects.exceeding_snow_loads.utils import dpi_paper1_figure, get_trend_test_name
from extreme_trend.visualizers.study_visualizer_for_non_stationary_trends import StudyVisualizerForNonStationaryTrends
@@ -10,7 +10,8 @@ def permute(l, permutation):
# permutation = [i//2 if i % 2 == 0 else 4 + i //2 for i in range(8)]
return [l[i] for i in permutation]
-def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNonStationaryTrends]):
+def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNonStationaryTrends],
+ paper1=True):
"""
Plot a single trend curves
:return:
@@ -20,8 +21,7 @@ def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNo
ax = create_adjusted_axes(1, 1)
selected_counter = merge_counter([v.selected_trend_test_class_counter for v in altitude_to_visualizer.values()])
- # selected_and_significative_counter = merge_counter([v.selected_and_significative_trend_test_class_counter for v in altitude_to_visualizer.values()])
- selected_and_significative_counter = merge_counter([v.selected_and_anderson_goodness_of_fit_trend_test_class_counter for v in altitude_to_visualizer.values()])
+ selected_and_significative_counter = merge_counter([v.selected_and_significative_trend_test_class_counter for v in altitude_to_visualizer.values()])
# selected_and_significative_counter = merge_counter([v.selected_and_kstest_goodness_of_fit_trend_test_class_counter for v in altitude_to_visualizer.values()])
total_of_selected_models = sum(selected_counter.values())
l = sorted(enumerate(visualizer.non_stationary_trend_test), key=lambda e: selected_counter[e[1]])
@@ -29,7 +29,11 @@ def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNo
select_list = get_ordered_list_from_counter(selected_counter, total_of_selected_models, visualizer, permutation)
selected_and_signifcative_list = get_ordered_list_from_counter(selected_and_significative_counter, total_of_selected_models, visualizer, permutation)
- labels = permute(['${}$'.format(t.label) for t in visualizer.non_stationary_trend_test], permutation)
+ if paper1:
+ labels = ['${}$'.format(t.label) for t in visualizer.non_stationary_trend_test]
+ else:
+ labels = [get_trend_test_name(t) for t in visualizer.non_stationary_trend_test]
+ labels = permute(labels, permutation)
print(l)
print(sum(select_list), select_list)
@@ -42,7 +46,10 @@ def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNo
width = 5
size = 30
legend_fontsize = 30
- labelsize = 25
+ if paper1:
+ labelsize = 25
+ else:
+ labelsize = 15
linewidth = 3
x = [10 * (i+1) for i in range(len(select_list))]
ax.bar(x, select_list, width=width, color='grey', edgecolor='grey', label='Non significant model',
@@ -95,8 +102,18 @@ def plot_selection_curves(altitude_to_visualizer: Dict[int, StudyVisualizerForNo
# ax_twinx.plot(altitudes, mean_decrease, label=label, linewidth=linewidth, marker='o')
# ax_twinx.legend(loc='upper right', prop={'size': size})
+ # Compute the ratio of plots that pass the goodness of fit test
+ if paper1:
+ ratio = '100'
+ else:
+ nb_selected_total = 0
+ nb_selected_total_and_goodness_of_fit = 0
+ for v in altitude_to_visualizer.values():
+ nb_selected_total += len(v.super_massif_name_to_trend_test_that_minimized_aic)
+ nb_selected_total_and_goodness_of_fit += len(v.massif_name_to_trend_test_that_minimized_aic)
+ ratio = 100 * nb_selected_total_and_goodness_of_fit / nb_selected_total
# Save plot
- visualizer.plot_name = 'Selection curves'
+ visualizer.plot_name = 'Selection curves ({}% of selected models were kept)'.format(ratio)
visualizer.show_or_save_to_file(no_title=True, dpi=dpi_paper1_figure)
plt.close()