diff --git a/experiment/meteo_france_SCM_study/abstract_study.py b/experiment/meteo_france_SCM_study/abstract_study.py
index 901970a80606e1b4cea7651d70ccb002c72835e8..9a5bd415d7690670639459066e3f11800eb1fe3d 100644
--- a/experiment/meteo_france_SCM_study/abstract_study.py
+++ b/experiment/meteo_france_SCM_study/abstract_study.py
@@ -82,9 +82,12 @@ class AbstractStudy(object):
# Map each year to an array of size nb_massif
year_to_annual_mean = OrderedDict()
for year, time_serie in self._year_to_daily_time_serie_array.items():
- year_to_annual_mean[year] = self.annual_aggregation_function(time_serie, axis=0)
+ year_to_annual_mean[year] = self.apply_annual_aggregation(time_serie)
return year_to_annual_mean
+ def apply_annual_aggregation(self, time_serie):
+ return self.annual_aggregation_function(time_serie, axis=0)
+
def instantiate_variable_object(self, dataset) -> AbstractVariable:
return self.variable_class(dataset, self.altitude)
@@ -142,11 +145,14 @@ class AbstractStudy(object):
""" Visualization methods """
def visualize_study(self, ax=None, massif_name_to_value=None, show=True, fill=True, replace_blue_by_white=True,
- label=None):
- massif_names, values = list(zip(*massif_name_to_value.items()))
- colors = get_color_rbga_shifted(ax, replace_blue_by_white, values, label=label)
- massif_name_to_fill_kwargs = {massif_name: {'color': color} for massif_name, color in
- zip(massif_names, colors)}
+ label=None, add_text=False):
+ if massif_name_to_value is None:
+ massif_name_to_fill_kwargs = None
+ else:
+ massif_names, values = list(zip(*massif_name_to_value.items()))
+ colors = get_color_rbga_shifted(ax, replace_blue_by_white, values, label=label)
+ massif_name_to_fill_kwargs = {massif_name: {'color': color} for massif_name, color in
+ zip(massif_names, colors)}
if ax is None:
ax = plt.gca()
@@ -176,12 +182,13 @@ class AbstractStudy(object):
# ax.text(x, y, massif_name)
# Display the center of the massif
ax.scatter(self.massifs_coordinates.x_coordinates, self.massifs_coordinates.y_coordinates, s=1)
- # Display the name of the massif
- for _, row in self.massifs_coordinates.df_all_coordinates.iterrows():
- x, y = list(row)
- massif_name = row.name
- value = massif_name_to_value[massif_name]
- ax.text(x, y, str(round(value, 1)))
+ # Display the name or value of the massif
+ if add_text:
+ for _, row in self.massifs_coordinates.df_all_coordinates.iterrows():
+ x, y = list(row)
+ massif_name = row.name
+ value = massif_name_to_value[massif_name]
+ ax.text(x, y, str(round(value, 1)))
if show:
plt.show()
diff --git a/experiment/meteo_france_SCM_study/abstract_variable.py b/experiment/meteo_france_SCM_study/abstract_variable.py
index 7a59e49decd85e2fa9d92da8b273054f4e40a8d0..31b50bfc3b928736101492fd91f9d3007421c85b 100644
--- a/experiment/meteo_france_SCM_study/abstract_variable.py
+++ b/experiment/meteo_france_SCM_study/abstract_variable.py
@@ -2,6 +2,9 @@ import numpy as np
class AbstractVariable(object):
+ """
+ All Variable (CROCUS & SAFRAN) are available since 1958-08-01 06:00:00
+ """
NAME = ''
diff --git a/experiment/meteo_france_SCM_study/crocus/crocus.py b/experiment/meteo_france_SCM_study/crocus/crocus.py
index 0390e08d951fa2814f95973fa702c43d7f73e38e..853985203f2c3e51da820cb78b500c337574af67 100644
--- a/experiment/meteo_france_SCM_study/crocus/crocus.py
+++ b/experiment/meteo_france_SCM_study/crocus/crocus.py
@@ -17,12 +17,18 @@ class Crocus(AbstractStudy):
@property
def variable_name(self):
- suffix = '' if self.altitude == 2400 else ' average of data observed every 6 hours'
+ suffix = '' if self.altitude == 2400 else ' instantaneous data observed sampled every 24 hours'
return super().variable_name + suffix
def annual_aggregation_function(self, *args, **kwargs):
return np.mean(*args, **kwargs)
+ def apply_annual_aggregation(self, time_serie):
+ # In the Durand paper, we only want the data from November to April
+ # 91 = 30 + 31 + 30 first days of the time serie correspond to the month of August + September + October
+ # 92 = 31 + 30 + 31 last days correspond to the month of May + June + JUly
+ return super().apply_annual_aggregation(time_serie[91:-92, ...])
+
class CrocusSwe(Crocus):
@@ -45,8 +51,8 @@ class ExtendedCrocusDepth(AbstractExtendedStudy, CrocusDepth):
if __name__ == '__main__':
- for variable_class in [CrocusSweVariable, CrocusDepthVariable]:
- study = Crocus(variable_class=variable_class, altitude=2400)
+ for variable_clas in [CrocusSweVariable, CrocusDepthVariable]:
+ study = Crocus(variable_class=variable_clas, altitude=2400)
d = study.year_to_dataset_ordered_dict[1960]
time_arr = np.array(d.variables['time'])
print(time_arr)
diff --git a/experiment/meteo_france_SCM_study/crocus/crocus_variables.py b/experiment/meteo_france_SCM_study/crocus/crocus_variables.py
index 1018669998df569899de81e072f3f46be9ecdbbf..8591bcce4f266dbf7181e192a1706c7c9f46fba3 100644
--- a/experiment/meteo_france_SCM_study/crocus/crocus_variables.py
+++ b/experiment/meteo_france_SCM_study/crocus/crocus_variables.py
@@ -4,6 +4,8 @@ from experiment.meteo_france_SCM_study.abstract_variable import AbstractVariable
class CrocusVariable(AbstractVariable):
+ """Crocus data is every 6 hours. To obtain daily data, we select one data out of 4
+ (in order to have data that will still be comparable to an instantaneous variable"""
def __init__(self, dataset, altitude, variable_name):
super().__init__(dataset, altitude)
@@ -34,8 +36,6 @@ class CrocusSweVariable(CrocusVariable):
class CrocusDepthVariable(CrocusVariable):
- """Crocus Depth data is every 6 hours
- To obtain daily data, we take the average over the 4 slots of 6 hours that compose a full day """
NAME = 'Snow Depth'
def __init__(self, dataset, altitude):
diff --git a/experiment/meteo_france_SCM_study/safran/safran.py b/experiment/meteo_france_SCM_study/safran/safran.py
index a5c1b30d77fb3aa10e8b2e359f69380e3702f7f8..4388b94a4f9f151e0ae297b71a60ce9057feb963 100644
--- a/experiment/meteo_france_SCM_study/safran/safran.py
+++ b/experiment/meteo_france_SCM_study/safran/safran.py
@@ -73,8 +73,8 @@ if __name__ == '__main__':
for year, dataset in study.year_to_dataset_ordered_dict.items():
print('{}: {}'.format(year, dataset.massifsList))
d = study.year_to_dataset_ordered_dict[1958]
- # print(d.variables['time'])
+ print(d.variables['time'])
# print(study.year_to_daily_time_serie[1958].shape)
# print(len(d.variables['time']))
# print(study.year_to_annual_total)
- print(study.df_annual_total.columns)
+ # print(study.df_annual_total.columns)
diff --git a/experiment/meteo_france_SCM_study/safran/safran_variable.py b/experiment/meteo_france_SCM_study/safran/safran_variable.py
index 7f419c7f5df9513fff75fdfa0088532bc4246605..4e3e2e270aec438e72d73ed0ab17778fb56bcdd4 100644
--- a/experiment/meteo_france_SCM_study/safran/safran_variable.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_variable.py
@@ -72,7 +72,6 @@ class SafranTotalPrecipVariable(AbstractVariable):
return self.snow_precipitation.daily_time_serie_array + self.rain_precipitation.daily_time_serie_array
-
class SafranTemperatureVariable(AbstractVariable):
def __init__(self, dataset, altitude, keyword='Tair'):
@@ -82,8 +81,6 @@ class SafranTemperatureVariable(AbstractVariable):
nb_days = len(self.hourly_temperature) // 24
self.daily_temperature = [np.mean(self.hourly_temperature[24 * i:24 * (i + 1)], axis=0) for i in range(nb_days)]
-
@property
def daily_time_serie_array(self):
return np.array(self.daily_temperature)
-
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 a7bf917ae71fb95fcae40219075be34e1f214682..d20f41ad29ba79ffa2802803acee3ff0d4f69733 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
@@ -48,23 +48,29 @@ def extended_visualization():
# study_visualizer.visualize_all_experimental_law()
-def annual_mean_vizu_compare_durand_study():
- for study_class in [SafranTotalPrecip, SafranRainfall, SafranSnowfall, SafranTemperature][:1]:
- study = study_class(altitude=1800, year_min=1958, year_max=2002)
- study_visualizer = StudyVisualizer(study)
- study_visualizer.visualize_annual_mean_values()
+def annual_mean_vizu_compare_durand_study(safran=True, take_mean_value=True):
+ if safran:
+ for study_class in [SafranTotalPrecip, SafranRainfall, SafranSnowfall, SafranTemperature][:1]:
+ study = study_class(altitude=1800, year_min=1958, year_max=2002)
+ study_visualizer = StudyVisualizer(study)
+ study_visualizer.visualize_annual_mean_values(take_mean_value=True)
+ else:
+ for study_class in [CrocusSwe, CrocusDepth][1:]:
+ study = study_class(altitude=1800, year_min=1958, year_max=2005)
+ study_visualizer = StudyVisualizer(study)
+ study_visualizer.visualize_annual_mean_values(take_mean_value=take_mean_value)
def normal_visualization():
save_to_file = False
only_first_one = True
# for study_class in SCM_STUDIES[:1]:
- for study_class in [SafranRainfall, SafranSnowfall, SafranTemperature][1:]:
+ for study_class in [SafranRainfall, SafranSnowfall, SafranTemperature][:1]:
for study in study_iterator(study_class, only_first_one=only_first_one):
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_annual_mean_values()
- # study_visualizer.visualize_linear_margin_fit(only_first_max_stable=True)
+ # study_visualizer.visualize_annual_mean_values()
+ study_visualizer.visualize_linear_margin_fit(only_first_max_stable=only_first_one)
def complete_analysis(only_first_one=False):
@@ -83,7 +89,7 @@ def complete_analysis(only_first_one=False):
if __name__ == '__main__':
- annual_mean_vizu_compare_durand_study()
+ annual_mean_vizu_compare_durand_study(safran=False, take_mean_value=True)
# normal_visualization()
# extended_visualization()
# complete_analysis()
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 a20a8ca621cd04609cb4633a174c1989a8f0fc52..56870301acbd7dd2f15d282836e5e816c37050aa 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
@@ -308,16 +308,19 @@ class StudyVisualizer(object):
# plot_name = 'Full Likelihood with Linear marginals and max stable dependency structure'
plt.show()
- def visualize_annual_mean_values(self, ax=None):
+ def visualize_annual_mean_values(self, ax=None, take_mean_value=True):
if ax is None:
_, ax = plt.subplots(1, 1, figsize=self.figsize)
massif_name_to_value = OrderedDict()
df_annual_total = self.study.df_annual_total
for massif_id, massif_name in enumerate(self.study.safran_massif_names):
- # We take the mean over all the annual values
- massif_name_to_value[massif_name] = df_annual_total.loc[:, massif_name].mean()
- self.study.visualize_study(ax=ax, massif_name_to_value=massif_name_to_value, show=self.show)
+ # We take the mean over all the annual values, otherwise we take the max
+ value = df_annual_total.loc[:, massif_name]
+ value = value.mean() if take_mean_value else value.max()
+ massif_name_to_value[massif_name] = value
+ self.study.visualize_study(ax=ax, massif_name_to_value=massif_name_to_value, show=self.show, add_text=True,
+ label=self.study.variable_name)
""" Statistics methods """