diff --git a/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py b/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py
index 7432c1d15c1d30c1be9500d2188cd826359a8254..a54c835822ad60a815b405845f5d9771b26f3a42 100644
--- a/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/study_visualization/main_study_visualizer.py
@@ -97,8 +97,10 @@ def normal_visualization(temporal_non_stationarity=False):
study_visualizer = StudyVisualizer(study, save_to_file=save_to_file,
temporal_non_stationarity=temporal_non_stationarity)
# study_visualizer.visualize_independent_margin_fits(threshold=[None, 20, 40, 60][0])
- study_visualizer.visualize_annual_mean_values()
- study_visualizer.visualize_linear_margin_fit(only_first_max_stable=None)
+ # study_visualizer.visualize_annual_mean_values()
+ study_visualizer.visualize_all_mean_and_max_graphs()
+
+ # study_visualizer.visualize_linear_margin_fit(only_first_max_stable=None)
def complete_analysis(only_first_one=False):
@@ -133,8 +135,8 @@ def trend_analysis():
def main_run():
# annual_mean_vizu_compare_durand_study(safran=True, take_mean_value=True, altitude=2100)
- # normal_visualization(temporal_non_stationarity=True)
- trend_analysis()
+ normal_visualization(temporal_non_stationarity=True)
+ # trend_analysis()
# max_stable_process_vizu_compare_gaume_study(altitude=1800, nb_days=1)
diff --git a/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py b/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py
index 7c4bce2429a486c1ae08400624fd913097dacf2f..af522ee361b462d6aee3dd56e92f60816618985b 100644
--- a/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/study_visualization/study_visualizer.py
@@ -49,6 +49,7 @@ class StudyVisualizer(object):
temporal_non_stationarity=False,
transformation_class=None,
normalization_under_one_observations=True):
+ self.massif_id_to_smooth_maxima = {}
self.temporal_non_stationarity = temporal_non_stationarity
self.only_first_row = only_first_row
self.only_one_graph = only_one_graph
@@ -139,7 +140,7 @@ class StudyVisualizer(object):
# Graph for each massif / or groups of massifs
- def visualize_massif_graphs(self, visualize_function):
+ def visualize_massif_graphs(self, visualize_function, specified_massif_names=None):
if self.only_one_graph:
fig, ax = plt.subplots(1, 1, figsize=self.figsize)
visualize_function(ax, 0)
@@ -153,12 +154,16 @@ class StudyVisualizer(object):
ax = axes[massif_id]
visualize_function(ax, massif_id)
else:
- for massif_id, massif_name in enumerate(self.study.study_massif_names):
- row_id, column_id = massif_id // nb_columns, massif_id % nb_columns
+ if specified_massif_names is None:
+ massif_ids = list(range(len(self.study.study_massif_names)))
+ else:
+ massif_ids = [self.study.study_massif_names.index(massif_name) for massif_name in specified_massif_names]
+ for j, massif_id in enumerate(massif_ids):
+ row_id, column_id = j // nb_columns, j % nb_columns
ax = axes[row_id, column_id]
visualize_function(ax, massif_id)
- def visualize_all_experimental_law(self):
+ def visualize_all_experimental_law( self):
self.visualize_massif_graphs(self.visualize_experimental_law)
self.plot_name = ' Empirical distribution \n'
self.plot_name += 'with data from the 23 mountain chains of the French Alps ' if self.year_for_kde_plot is None else \
@@ -277,16 +282,20 @@ class StudyVisualizer(object):
return all_massif_data
def visualize_all_mean_and_max_graphs(self):
- self.visualize_massif_graphs(self.visualize_mean_and_max_graph)
- self.plot_name = ' mean with sliding window of size {}'.format(self.window_size_for_smoothing)
+ # Compute the order of massif names
+ massif_name_to_score = {}
+ for massif_id, massif_name in enumerate(self.study.study_massif_names):
+ score = self.smooth_maxima_x_y(massif_id)[1].argmax()
+ massif_name_to_score[massif_name] = score
+ ordered_massif_names = sorted(self.study.study_massif_names[:], key=lambda s: massif_name_to_score[s])
+ self.visualize_massif_graphs(self.visualize_mean_and_max_graph, specified_massif_names=ordered_massif_names)
+ self.plot_name = ' smoothing values temporally with sliding window of size {}'.format(self.window_size_for_smoothing)
self.show_or_save_to_file()
def visualize_mean_and_max_graph(self, ax, massif_id):
# Display the graph of the max on top
color_maxima = 'r'
- tuples_x_y = [(year, annual_maxima[massif_id]) for year, annual_maxima in
- self.study.year_to_annual_maxima.items()]
- x, y = list(zip(*tuples_x_y))
+ x, y = self.smooth_maxima_x_y(massif_id)
ax2 = ax.twinx()
ax2.plot(x, y, color=color_maxima)
ax2.set_ylabel('maxima', color=color_maxima)
@@ -299,9 +308,20 @@ class StudyVisualizer(object):
x, y = list(zip(*tuples_x_y))
x, y = average_smoothing_with_sliding_window(x, y, window_size_for_smoothing=self.window_size_for_smoothing)
ax.plot(x, y, color=color_mean)
- ax.set_ylabel('mean with sliding window of size {}'.format(self.window_size_for_smoothing), color=color_mean)
+ ax.set_ylabel('mean'.format(self.window_size_for_smoothing), color=color_mean)
ax.set_xlabel('year')
ax.set_title(self.study.study_massif_names[massif_id])
+ ax.xaxis.set_ticks(x[2::10])
+
+
+ def smooth_maxima_x_y(self, massif_id):
+ if massif_id not in self.massif_id_to_smooth_maxima:
+ tuples_x_y = [(year, annual_maxima[massif_id]) for year, annual_maxima in
+ self.study.year_to_annual_maxima.items()]
+ x, y = list(zip(*tuples_x_y))
+ x, y = average_smoothing_with_sliding_window(x, y, window_size_for_smoothing=self.window_size_for_smoothing)
+ self.massif_id_to_smooth_maxima[massif_id] = (x, y)
+ return self.massif_id_to_smooth_maxima[massif_id]
def visualize_brown_resnick_fit(self):
pass