From aa4e276ed083036f2aec5c899932c53a67434a92 Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Wed, 17 Jun 2020 14:07:40 +0200
Subject: [PATCH] [contrasting]fix limit for some assertion equal. add r2 value
written on the plot
---
extreme_trend/abstract_gev_trend_test.py | 4 +-
.../snowfall_plot.py | 62 +++++++++++++------
.../study_visualizer_for_mean_values.py | 8 ++-
projects/exceeding_snow_loads/utils.py | 2 +-
4 files changed, 53 insertions(+), 23 deletions(-)
diff --git a/extreme_trend/abstract_gev_trend_test.py b/extreme_trend/abstract_gev_trend_test.py
index 13121a30..c8a72be9 100644
--- a/extreme_trend/abstract_gev_trend_test.py
+++ b/extreme_trend/abstract_gev_trend_test.py
@@ -108,8 +108,8 @@ class AbstractGevTrendTest(object):
def aic(self):
aic = 2 * self.total_number_of_parameters_for_unconstrained_model + self.unconstrained_model_deviance
assert np.equal(self.total_number_of_parameters_for_unconstrained_model, self.unconstrained_estimator.margin_model.nb_params)
- npt.assert_almost_equal(self.unconstrained_estimator.result_from_model_fit.aic, aic, decimal=12)
- npt.assert_almost_equal(self.unconstrained_estimator.aic(), aic, decimal=12)
+ npt.assert_almost_equal(self.unconstrained_estimator.result_from_model_fit.aic, aic, decimal=5)
+ npt.assert_almost_equal(self.unconstrained_estimator.aic(), aic, decimal=5)
return aic
@property
diff --git a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/snowfall_plot.py b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/snowfall_plot.py
index 38299ac8..e34f8755 100644
--- a/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/snowfall_plot.py
+++ b/projects/contrasting_trends_in_snow_loads/article2_snowfall_versus_time_and_altitude/snowfall_plot.py
@@ -36,7 +36,8 @@ def plot_snowfall_change_mean(altitude_to_visualizer: Dict[int, StudyVisualizerF
visualizer.plot_abstract_fast(massif_name_to_mean_at_2000,
label='Time derivative of mean annual maxima \nof {} at 2000 m ({})'.format(
SCM_STUDY_CLASS_TO_ABBREVIATION[type(study)], study.variable_unit),
- add_x_label=False)
+ add_x_label=False,
+ add_text=True, massif_name_to_text={k: str(v) for k,v in massif_name_to_r2_score.items()})
# Altitude for the change of dynamic
massif_name_to_altitude_change_dynamic = {m: - massif_name_to_b[m] / a for m, a in massif_name_to_a.items()}
# Keep only those that are in a reasonable range
@@ -44,11 +45,13 @@ def plot_snowfall_change_mean(altitude_to_visualizer: Dict[int, StudyVisualizerF
if 0 < d < 3000}
visualizer.plot_abstract_fast(massif_name_to_altitude_change_dynamic,
label='Altitude for the change of dynamic (m)',
- add_x_label=False, graduation=500)
+ add_x_label=False, graduation=500,
+ add_text=True, massif_name_to_text={k: str(v) for k,v in massif_name_to_r2_score.items()})
# R2 score
- visualizer.plot_abstract_fast(massif_name_to_r2_score, label='r2 time derivative of the mean', graduation=0.1,
- add_x_label=False,
- negative_and_positive_values=False)
+ # visualizer.plot_abstract_fast(massif_name_to_r2_score, label='r2 time derivative of the mean', graduation=0.1,
+ # add_x_label=False,
+ # negative_and_positive_values=False,
+ # )
def plot_snowfall_mean(altitude_to_visualizer: Dict[int, StudyVisualizerForMeanValues]):
@@ -56,20 +59,35 @@ def plot_snowfall_mean(altitude_to_visualizer: Dict[int, StudyVisualizerForMeanV
study = visualizer.study
# Plot the curve for the evolution of the mean
massif_name_to_a, massif_name_to_b, massif_name_to_r2_score = plot_mean(altitude_to_visualizer, derivative=False)
- # Augmentation every km
+ # Compute values of interest
+ massif_name_to_mean_at_2000 = {m: a * 2000 + massif_name_to_b[m] for m, a in massif_name_to_a.items()}
+ massif_name_to_mean_at_1000 = {m: a * 1000 + massif_name_to_b[m] for m, a in massif_name_to_a.items()}
massif_name_to_augmentation_every_km = {m: a * 1000 for m, a in massif_name_to_a.items()}
- visualizer.plot_abstract_fast(massif_name_to_augmentation_every_km,
- label='Augmentation of mean annual maxima of {} \nfor every km of elevation ({})'.format(
- SCM_STUDY_CLASS_TO_ABBREVIATION[type(study)], study.variable_unit),
- add_x_label=False, negative_and_positive_values=False)
+ massif_name_to_relative_augmentation_between_2000_and_3000_every_km = {m: 100 * (a * 1000) / (a * 2000 + massif_name_to_b[m]) for m, a in massif_name_to_a.items()}
+ massif_name_to_relative_augmentation_between_1000_and_2000_every_km = {m: 100 * (a * 1000) / (a * 1000 + massif_name_to_b[m]) for m, a in massif_name_to_a.items()}
+
+ # Augmentation every km
+ ds = [massif_name_to_augmentation_every_km, massif_name_to_relative_augmentation_between_1000_and_2000_every_km,
+ massif_name_to_relative_augmentation_between_2000_and_3000_every_km]
+ prefixs = ['Augmentation', 'Relative augmentation between 1000m and 2000m', 'Relative augmentation between 2000m and 3000m']
+ graduations = [1.0, 10.0, 10.0]
+ for d, prefix in zip(ds, prefixs):
+ visualizer.plot_abstract_fast(d,
+ graduation=1.0,
+ label=prefix + ' of mean annual maxima of {} \nfor every km of elevation ({})'.format(
+ SCM_STUDY_CLASS_TO_ABBREVIATION[type(study)], study.variable_unit),
+ add_x_label=False, negative_and_positive_values=False,
+ add_text=True,
+ massif_name_to_text={k: str(v) for k, v in massif_name_to_r2_score.items()}
+ )
# Value at 2000 m
- massif_name_to_mean_at_2000 = {m: a * 2000 + massif_name_to_b[m] for m, a in massif_name_to_a.items()}
visualizer.plot_abstract_fast(massif_name_to_mean_at_2000, label='Mean annual maxima of {} at 2000 m ()'.format(
SCM_STUDY_CLASS_TO_ABBREVIATION[type(study)], study.variable_unit),
- add_x_label=False, negative_and_positive_values=False)
- # R2 score
- visualizer.plot_abstract_fast(massif_name_to_r2_score, label='r2 mean', graduation=0.1,
- add_x_label=False, negative_and_positive_values=False)
+ add_x_label=False, negative_and_positive_values=False,
+ add_text=True, massif_name_to_text={k: str(v) for k,v in massif_name_to_r2_score.items()})
+ # # R2 score
+ # visualizer.plot_abstract_fast(massif_name_to_r2_score, label='r2 mean', graduation=0.1,
+ # add_x_label=False, negative_and_positive_values=False)
def plot_mean(altitude_to_visualizer: Dict[int, StudyVisualizerForMeanValues], derivative=False):
@@ -90,9 +108,17 @@ def plot_mean(altitude_to_visualizer: Dict[int, StudyVisualizerForMeanValues], d
nb_years = 10
res = [(a, t.change_in_mean_for_the_last_x_years(nb_years=nb_years))
for i, (a, t) in enumerate(zip(altitudes_massif, trend_tests))
- if not t.unconstrained_model_is_stationary]
- altitudes_values, values = zip(*res)
- moment = 'Change in the last {} years \nfor non-stationary models'.format(nb_years)
+ if t.is_significant]
+ if len(res) > 0:
+ altitudes_values, values = zip(*res)
+ else:
+ altitudes_values, values = [], []
+ moment = 'Change in the last {} years \nfor significative models'.format(nb_years)
+ # res = [(a, t.change_in_mean_for_the_last_x_years(nb_years=nb_years))
+ # for i, (a, t) in enumerate(zip(altitudes_massif, trend_tests))
+ # if not t.unconstrained_model_is_stationary]
+ # altitudes_values, values = zip(*res)
+ # moment = 'Change in the last {} years \nfor non-stationary models'.format(nb_years)
else:
moment = 'mean'
values = [t.unconstrained_estimator_gev_params_last_year.mean for t in trend_tests]
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 c480742b..2c33eb43 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
@@ -38,8 +38,12 @@ class StudyVisualizerForMeanValues(StudyVisualizerForNonStationaryTrends):
assert len(self.non_stationary_trend_test) == len(NON_STATIONARY_TREND_TEST_PAPER_2)
def plot_abstract_fast(self, massif_name_to_value, label, graduation=10.0, cmap=plt.cm.coolwarm, add_x_label=True,
- negative_and_positive_values=True, add_text=False):
- massif_name_to_text = self.massif_name_to_text if add_text else None
+ negative_and_positive_values=True, add_text=False, massif_name_to_text=None):
+ if add_text:
+ if massif_name_to_text is None:
+ massif_name_to_text = self.massif_name_to_text
+ else:
+ massif_name_to_text = None
super().plot_abstract(massif_name_to_value, label, label, self.fit_method, graduation, cmap, add_x_label,
negative_and_positive_values, massif_name_to_text)
diff --git a/projects/exceeding_snow_loads/utils.py b/projects/exceeding_snow_loads/utils.py
index 477660cd..496884fb 100644
--- a/projects/exceeding_snow_loads/utils.py
+++ b/projects/exceeding_snow_loads/utils.py
@@ -33,7 +33,7 @@ NON_STATIONARY_TREND_TEST_PAPER_2 = [
# Gumbel models
GumbelVersusGumbel, GumbelLocationTrendTest, GumbelScaleTrendTest, GumbelLocationAndScaleTrendTest,
# GEV models with constant shape
- GevVersusGev, GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest,
+ GevVersusGev, GevLocationTrendTest, GevScaleTrendTest, GevLocationAndScaleTrendTest,
# GEV models with linear shape
GevShapeTrendTest, GevLocationAndShapeTrendTest, GevScaleAndShapeTrendTest, GevLocationAndScaleAndShapeTrendTest,
# Quadratic model for the Gev/Gumbel and for the location/scale
--
GitLab