From cdc6dc8bb710bc4d0917d4e41948288fb91472bb Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Mon, 3 Jun 2019 16:43:31 +0200
Subject: [PATCH] [HYPERCUBE VISUALIZER] fix big issue with respect to the
"best year", take the year that minimizes the nllh
---
.../altitude_hypercube_visualizer.py | 5 +++--
.../hypercube_visualization/main_hypercube_visualization.py | 6 +++---
.../visualization/study_visualization/study_visualizer.py | 3 ++-
3 files changed, 8 insertions(+), 6 deletions(-)
diff --git a/experiment/meteo_france_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py b/experiment/meteo_france_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
index c546a14e..2e9beb56 100644
--- a/experiment/meteo_france_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
+++ b/experiment/meteo_france_data/visualization/hypercube_visualization/altitude_hypercube_visualizer.py
@@ -118,7 +118,8 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
# Figure title
specific_title += '\n'
- trend_types = [AbstractUnivariateTest.SIGNIFICATIVE_ALL_TREND,
+ trend_types = [AbstractUnivariateTest.ALL_TREND,
+ AbstractUnivariateTest.SIGNIFICATIVE_ALL_TREND,
AbstractUnivariateTest.SIGNIFICATIVE_POSITIVE_TREND,
AbstractUnivariateTest.SIGNIFICATIVE_NEGATIVE_TREND]
series = [trend_type_to_series[trend_type][0] for trend_type in trend_types]
@@ -126,7 +127,7 @@ class AltitudeHypercubeVisualizer(AbstractHypercubeVisualizer):
percents = [round(p) for p in percents]
specific_title += 'Total ' if xlabel == STARTING_YEARS_XLABEL else 'Mean '
- specific_title += 'of significative trends: {} (+:{} -{})'.format(*percents)
+ specific_title += 'all trend {}, all significative trends: {} (+:{} -{})'.format(*percents)
plt.suptitle(specific_title)
self.show_or_save_to_file(specific_title=specific_title)
diff --git a/experiment/meteo_france_data/visualization/hypercube_visualization/main_hypercube_visualization.py b/experiment/meteo_france_data/visualization/hypercube_visualization/main_hypercube_visualization.py
index 9f0c8daf..dd866ec9 100644
--- a/experiment/meteo_france_data/visualization/hypercube_visualization/main_hypercube_visualization.py
+++ b/experiment/meteo_france_data/visualization/hypercube_visualization/main_hypercube_visualization.py
@@ -74,12 +74,12 @@ def fast_altitude_hypercube():
def fast_altitude_year_hypercube():
- save_to_file = True
+ save_to_file = False
only_first_one = False
nb_data_reduced_for_speed = True
altitudes = [ALL_ALTITUDES[3], ALL_ALTITUDES[-7]]
for study_class in SCM_STUDIES[:1]:
- for last_starting_year in [1989, 1999]:
+ for last_starting_year in [None, 1989, 1999][:1]:
for trend_test_class in [GevLocationChangePointTest, GevScaleChangePointTest, GevShapeChangePointTest][:1]:
visualizers = [StudyVisualizer(study, temporal_non_stationarity=True, verbose=False, multiprocessing=True)
for study in study_iterator(study_class=study_class, only_first_one=only_first_one,
@@ -102,7 +102,7 @@ def full_altitude_year_hypercube():
for study_class in SCM_STUDIES[:1]:
for trend_test_class in [GevLocationChangePointTest, GevScaleChangePointTest,
GevShapeChangePointTest][:1]:
- for last_starting_year in [1967, 1977, 1987, 1997, 2007, None]:
+ for last_starting_year in [1967, 1977, 1987, 1997, 2007, None][-2::-1]:
visualizers = [
StudyVisualizer(study, temporal_non_stationarity=True, verbose=False, multiprocessing=True)
for study in study_iterator(study_class=study_class, only_first_one=only_first_one,
diff --git a/experiment/meteo_france_data/visualization/study_visualization/study_visualizer.py b/experiment/meteo_france_data/visualization/study_visualization/study_visualizer.py
index a50338a7..aa6d260a 100644
--- a/experiment/meteo_france_data/visualization/study_visualization/study_visualizer.py
+++ b/experiment/meteo_france_data/visualization/study_visualization/study_visualizer.py
@@ -411,8 +411,9 @@ class StudyVisualizer(object):
self.compute_gev_change_point_test_result(smooth_maxima, starting_year, trend_test_class, years)
for starting_year in starting_years]
# Keep only the most likely starting year
+ # (i.e. the starting year that minimizes its negative log likelihood)
# (set all the other data to np.nan so that they will not be taken into account in mean function)
- best_idx = list(np.argmax(trend_test_res, axis=0))[2]
+ best_idx = list(np.argmin(trend_test_res, axis=0))[2]
# print(best_idx, trend_test_res)
best_idxs = [best_idx]
# todo: by doing a sorting on the deviance, I could get the nb_top_likelihood_values values
--
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