diff --git a/experiment/meteo_france_SCM_study/main_visualize.py b/experiment/meteo_france_SCM_study/main_visualize.py
index f644c311bd647981eee918b9b9289adf13d15239..84bde0b84c5eade2a87db7825623703804ba8646 100644
--- a/experiment/meteo_france_SCM_study/main_visualize.py
+++ b/experiment/meteo_france_SCM_study/main_visualize.py
@@ -33,10 +33,9 @@ def study_iterator(study_class, only_first_one=False, both_altitude=False, verbo
def extended_visualization():
- for study_class in SCM_EXTENDED_STUDIES[:1]:
- for study in study_iterator(study_class, only_first_one=True):
- study_visualizer = StudyVisualizer(study, save_to_file=False, only_one_graph=True, vertical_kde_plot=True,
- year_for_kde_plot=1958)
+ for study_class in SCM_EXTENDED_STUDIES[:]:
+ for study in study_iterator(study_class, only_first_one=False):
+ study_visualizer = StudyVisualizer(study, save_to_file=True, only_one_graph=True, plot_bm_quantiles=True)
# study_visualizer.visualize_all_mean_and_max_graphs()
study_visualizer.visualize_all_experimental_law()
# for study_class in SCM_EXTENDED_STUDIES[:]:
@@ -47,10 +46,11 @@ def extended_visualization():
def normal_visualization():
- only_first_one = True
- for study_class in SCM_STUDIES[1:2]:
+ save_to_file = True
+ only_first_one = False
+ for study_class in SCM_STUDIES[:]:
for study in study_iterator(study_class, only_first_one=only_first_one):
- study_visualizer = StudyVisualizer(study)
+ study_visualizer = StudyVisualizer(study, save_to_file=save_to_file)
# study_visualizer.visualize_independent_margin_fits(threshold=[None, 20, 40, 60][0])
study_visualizer.visualize_linear_margin_fit(only_first_max_stable=only_first_one)
@@ -71,6 +71,6 @@ def complete_analysis(only_first_one=False):
if __name__ == '__main__':
- # normal_visualization()
- extended_visualization()
+ normal_visualization()
+ # extended_visualization()
# complete_analysis()
diff --git a/experiment/meteo_france_SCM_study/safran/safran_visualizer.py b/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
index 9600169a1128a71773ded5fe0dd064fd0eff6929..d72300d4a47d82945b7cc8641259802898785443 100644
--- a/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
@@ -25,19 +25,23 @@ from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
from test.test_utils import load_test_max_stable_models
from utils import get_display_name_from_object_type, VERSION_TIME, float_to_str_with_only_some_significant_digits
+BLOCK_MAXIMA_DISPLAY_NAME = 'block maxima '
+
class StudyVisualizer(object):
def __init__(self, study: AbstractStudy, show=True, save_to_file=False, only_one_graph=False, only_first_row=False,
- vertical_kde_plot=False, year_for_kde_plot=None):
+ vertical_kde_plot=False, year_for_kde_plot=None, plot_bm_quantiles=False):
self.only_first_row = only_first_row
self.only_one_graph = only_one_graph
self.save_to_file = save_to_file
self.study = study
self.plot_name = None
# KDE PLOT ARGUMENTS
- self.vertical_kde_plot=vertical_kde_plot
+ self.vertical_kde_plot = vertical_kde_plot
self.year_for_kde_plot = year_for_kde_plot
+ self.plot_bm_quantiles = plot_bm_quantiles
+
self.show = False if self.save_to_file else show
self.window_size_for_smoothing = 21
if self.only_one_graph:
@@ -92,7 +96,8 @@ class StudyVisualizer(object):
if self.year_for_kde_plot is not None:
all_massif_data = self.study.year_to_daily_time_serie[self.year_for_kde_plot][:, massif_id]
else:
- all_massif_data = np.concatenate([data[:, massif_id] for data in self.study.year_to_daily_time_serie.values()])
+ all_massif_data = np.concatenate(
+ [data[:, massif_id] for data in self.study.year_to_daily_time_serie.values()])
all_massif_data = np.sort(all_massif_data)
# Kde plot, and retrieve the data forming the line
@@ -105,9 +110,15 @@ class StudyVisualizer(object):
np.mean(all_massif_data): ('g', 'mean'),
}
# Plot some specific quantiles in their color
- for p, color, name in zip(AbstractParams.QUANTILE_P_VALUES, AbstractParams.QUANTILE_COLORS, AbstractParams.QUANTILE_NAMES):
+ for p, color, name in zip(AbstractParams.QUANTILE_P_VALUES, AbstractParams.QUANTILE_COLORS,
+ AbstractParams.QUANTILE_NAMES):
x_level = all_massif_data[int(p * len(all_massif_data))]
x_level_to_color[x_level] = (color, name)
+ # Plot some additional quantiles from the correspond Annual Maxima law
+ if self.plot_bm_quantiles:
+ p = p ** (1 / 365)
+ x_level = all_massif_data[int(p * len(all_massif_data))]
+ x_level_to_color[x_level] = (color, BLOCK_MAXIMA_DISPLAY_NAME + name)
for xi, (color, name) in x_level_to_color.items():
if self.vertical_kde_plot:
@@ -115,7 +126,8 @@ class StudyVisualizer(object):
xi = np.interp(yi, data_y, data_x)
else:
yi = np.interp(xi, data_x, data_y)
- ax.scatter([xi], [yi], color=color, marker="o", label=name)
+ marker = "x" if BLOCK_MAXIMA_DISPLAY_NAME in name else "o"
+ ax.scatter([xi], [yi], color=color, marker=marker, label=name)
label_function = ax.set_xlabel if self.vertical_kde_plot else ax.set_ylabel
label_function('Probability Density function f(x)', color=color_kde)
@@ -236,7 +248,7 @@ class StudyVisualizer(object):
plt.show()
def visualize_cmap(self, massif_name_to_value):
- orig_cmap = plt.cm. coolwarm
+ orig_cmap = plt.cm.coolwarm
# shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.75, name='shifted')
massif_name_to_fill_kwargs = {massif_name: {'color': orig_cmap(value)} for massif_name, value in