From 5d94491c88abf0281684e19edd46f9b3f3c8b38f Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Mon, 9 Sep 2019 18:57:25 +0200
Subject: [PATCH] [POSTER EVAN] add maxima visualization for the EAN
---
.../main_study_visualizer.py | 26 ++++++++++++++-----
.../study_visualization/study_visualizer.py | 8 +++---
2 files changed, 23 insertions(+), 11 deletions(-)
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 144b992a..092e620a 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
@@ -34,13 +34,20 @@ altitude_massif_name_and_study_class_for_poster = [
(2700, 'Parpaillon', SafranSnowfall),
]
+altitude_massif_name_and_study_class_for_poster_evan = [
+ (900, 'Chartreuse', CrocusSwe3Days),
+ (1800, 'Vanoise', CrocusSwe3Days),
+ (2700, 'Parpaillon', CrocusSwe3Days),
+]
+
+
SCM_STUDY_NAME_TO_ABBREVIATION = {get_display_name_from_object_type(k): v for k, v in
SCM_STUDY_CLASS_TO_ABBREVIATION.items()}
SCM_COLORS = ['tab:orange', 'y', 'tab:purple', 'lightseagreen']
SCM_STUDY_CLASS_TO_COLOR = dict(zip(SCM_STUDIES, SCM_COLORS))
SCM_STUDY_NAME_TO_COLOR = {get_display_name_from_object_type(s): color
for s, color in zip(SCM_STUDIES, SCM_COLORS)}
-
+poster_altitude_to_color = dict(zip([900, 1800, 2700], ['y', 'tab:purple', 'tab:orange']))
SCM_EXTENDED_STUDIES = [ExtendedSafranSnowfall, ExtendedCrocusSweTotal, ExtendedCrocusDepth]
SCM_STUDY_TO_EXTENDED_STUDY = OrderedDict(zip(SCM_STUDIES, SCM_EXTENDED_STUDIES))
@@ -237,15 +244,20 @@ def maxima_analysis():
def max_graph_annual_maxima_poster():
save_to_file = True
- for altitude, massif_name, study_class in altitude_massif_name_and_study_class_for_poster:
+ choice_tuple = [
+ altitude_massif_name_and_study_class_for_poster,
+ altitude_massif_name_and_study_class_for_poster_evan,
+ ][1]
+ for altitude, massif_name, study_class in choice_tuple:
for study in study_iterator_global([study_class], altitudes=[altitude]):
study_visualizer = StudyVisualizer(study, save_to_file=save_to_file,
verbose=True,
multiprocessing=True)
snow_abbreviation = SCM_STUDY_CLASS_TO_ABBREVIATION[study_class]
- color = SCM_STUDY_CLASS_TO_COLOR[study_class]
- # study_visualizer.visualize_max_graphs_poster(massif_name, altitude, snow_abbreviation, color)
- study_visualizer.visualize_gev_graphs_poster(massif_name, altitude, snow_abbreviation, color)
+ # color = SCM_STUDY_CLASS_TO_COLOR[study_class]
+ color = poster_altitude_to_color[altitude]
+ study_visualizer.visualize_max_graphs_poster(massif_name, altitude, snow_abbreviation, color)
+ # study_visualizer.visualize_gev_graphs_poster(massif_name, altitude, snow_abbreviation, color)
def altitude_analysis():
@@ -260,8 +272,8 @@ def main_run():
# trend_analysis()
# altitude_analysis()
- # max_graph_annual_maxima_poster()
- maxima_analysis()
+ max_graph_annual_maxima_poster()
+ # maxima_analysis()
# case_study()
# all_scores_vizu()
# maxima_analysis()
diff --git a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
index 45a7526e..faa2ef59 100644
--- a/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
+++ b/experiment/meteo_france_data/scm_models_data/visualization/study_visualization/study_visualizer.py
@@ -618,12 +618,12 @@ class StudyVisualizer(VisualizationParameters):
# Display the graph of the max on top
ax = plt.gca()
_, y = self.smooth_maxima_x_y(massif_names.index(massif_name))
- d = IsmevGevFit(x_gev=y).gev_params
+ gev_param = IsmevGevFit(x_gev=y).gev_params
# Round up
- d = {k: self.round_sig(v, 2) for k, v in d.items()}
- print(d)
- gev_param = GevParams.from_dict(d)
+ # d = {k: self.round_sig(v, 2) for k, v in d.items()}
+ # print(d)
+ # gev_param = GevParams.from_dict(d)
x_gev = np.linspace(0.0, 1.5 * max(y), num=1000)
y_gev = [gev_param.density(x) for x in x_gev]
ax.plot(x_gev, y_gev, color=color, linewidth=5)
--
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