diff --git a/experiment/meteo_france_SCM_study/abstract_study.py b/experiment/meteo_france_SCM_study/abstract_study.py
index 9620e50ed365aabef007a614637827d9fc2bcf32..42973271055ddb57cef77cc631318be7b60b4bd2 100644
--- a/experiment/meteo_france_SCM_study/abstract_study.py
+++ b/experiment/meteo_france_SCM_study/abstract_study.py
@@ -37,7 +37,7 @@ class AbstractStudy(object):
REANALYSIS_FOLDER = 'alp_flat/reanalysis'
def __init__(self, variable_class: type, altitude: int = 1800, year_min=1000, year_max=3000,
- multiprocessing=False):
+ multiprocessing=True):
assert altitude in ALTITUDES, altitude
self.altitude = altitude
self.model_name = None
@@ -148,7 +148,7 @@ class AbstractStudy(object):
@property
def _year_to_daily_time_serie_array(self) -> OrderedDict:
# Map each year to a matrix of size 365-nb_days_consecutive+1 x nb_massifs
- variables = [self.instantiate_variable_object(dataset) for dataset in
+ variables = [self.instantiate_variable_object(variable_array) for variable_array in
self.year_to_variable_array.values()]
year_to_variable = dict(zip(self.ordered_years, variables))
year_to_daily_time_serie_array = OrderedDict()
diff --git a/experiment/meteo_france_SCM_study/safran/safran.py b/experiment/meteo_france_SCM_study/safran/safran.py
index 7e4d928270f049da9c8290bf4c72bcb550aaa5ad..0258c0ff95c8704a32ae95e63f99043d9927f0fa 100644
--- a/experiment/meteo_france_SCM_study/safran/safran.py
+++ b/experiment/meteo_france_SCM_study/safran/safran.py
@@ -23,8 +23,8 @@ class SafranFrequency(Safran):
super().__init__(variable_class, *args, **kwargs)
self.nb_consecutive_days = nb_consecutive_days
- def instantiate_variable_object(self, dataset) -> AbstractVariable:
- return self.variable_class(dataset, self.nb_consecutive_days)
+ def instantiate_variable_object(self, variable_array) -> AbstractVariable:
+ return self.variable_class(variable_array, self.nb_consecutive_days)
@property
def variable_name(self):
@@ -55,6 +55,10 @@ class SafranTotalPrecip(SafranFrequency):
def __init__(self, *args, **kwargs):
super().__init__(SafranTotalPrecipVariable, *args, **kwargs)
+ def instantiate_variable_object(self, variable_array) -> AbstractVariable:
+ variable_array_snowfall, variable_array_rainfall = variable_array
+ return self.variable_class(variable_array_snowfall, variable_array_rainfall, self.nb_consecutive_days)
+
class ExtendedSafranTotalPrecip(AbstractExtendedStudy, SafranTotalPrecip):
pass
diff --git a/experiment/meteo_france_SCM_study/safran/safran_variable.py b/experiment/meteo_france_SCM_study/safran/safran_variable.py
index 1903abcd231e9e37ee410f19730d70b5ef6c2809..6ed6bd83487a4773fb23a9db027dc7d134c08a8e 100644
--- a/experiment/meteo_france_SCM_study/safran/safran_variable.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_variable.py
@@ -71,11 +71,10 @@ class SafranRainfallVariable(SafranSnowfallVariable):
class SafranTotalPrecipVariable(AbstractVariable):
- def __init__(self, variable_array):
- super().__init__(variable_array)
- snow_variable_array, rain_variable_array = self.variable_array
- self.snow_precipitation = SafranSnowfallVariable(snow_variable_array)
- self.rain_precipitation = SafranRainfallVariable(rain_variable_array)
+ def __init__(self, snow_variable_array, rain_variable_array, nb_consecutive_days_of_snowfall=1):
+ super().__init__(None)
+ self.snow_precipitation = SafranSnowfallVariable(snow_variable_array, nb_consecutive_days_of_snowfall)
+ self.rain_precipitation = SafranRainfallVariable(rain_variable_array, nb_consecutive_days_of_snowfall)
@classmethod
def keyword(cls):
diff --git a/experiment/meteo_france_SCM_study/visualization/studies_visualization/hypercube_visualizer.py b/experiment/meteo_france_SCM_study/visualization/studies_visualization/hypercube_visualizer.py
index 971bf62f511a6bbe62522d7555b91b80ebbe7e8f..99d5c5189ac9dd4b469cd32d5b9b450e76f61bc6 100644
--- a/experiment/meteo_france_SCM_study/visualization/studies_visualization/hypercube_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/studies_visualization/hypercube_visualizer.py
@@ -39,13 +39,14 @@ class HypercubeVisualizer(object):
@cached_property
def tuple_to_df_trend_type(self):
- df_spatio_temporal_trend_types = [study_visualizer.df_trend_spatio_temporal(self.trend_class, self.starting_years,
- self.nb_data_for_fast_mode)
- for study_visualizer in self.tuple_to_study_visualizer.values()]
+ df_spatio_temporal_trend_types = [
+ study_visualizer.df_trend_spatio_temporal(self.trend_class, self.starting_years,
+ self.nb_data_for_fast_mode)
+ for study_visualizer in self.tuple_to_study_visualizer.values()]
return dict(zip(self.tuple_to_study_visualizer.keys(), df_spatio_temporal_trend_types))
@cached_property
- def hypercube(self):
+ def df_hypercube(self):
keys = list(self.tuple_to_df_trend_type.keys())
values = list(self.tuple_to_df_trend_type.values())
df = pd.concat(values, keys=keys, axis=0)
@@ -82,7 +83,42 @@ class HypercubeVisualizer(object):
class AltitudeHypercubeVisualizer(HypercubeVisualizer):
- pass
+
+ @property
+ def altitudes(self):
+ return list(self.tuple_to_study_visualizer.keys())
+
+ def visualize_trend_test(self, ax=None, marker='o'):
+ if ax is None:
+ fig, ax = plt.subplots(1, 1, figsize=self.study_visualizer.figsize)
+
+ # Plot weighted percentages over the years
+ for trend_type, style in self.trend_class.trend_type_to_style().items():
+ altitude_percentages = (self.df_hypercube == trend_type)
+ # Take the mean with respect to the years
+ altitude_percentages = altitude_percentages.mean(axis=1)
+ # Take the mean with respect the massifs
+ altitude_percentages = altitude_percentages.mean(axis=0, level=0)
+ # Take the numpy array
+ altitude_percentages = altitude_percentages.values * 100
+ # Plot
+ ax.plot(self.altitudes, altitude_percentages, style + marker, label=trend_type)
+
+ # Global information
+ added_str = 'weighted '
+ ylabel = '% averaged on massifs & {}averaged on starting years'.format(added_str)
+ ylabel += ' (with uniform weights)'
+ ax.set_ylabel(ylabel)
+ ax.set_xlabel('altitude')
+ ax.set_xticks(self.altitudes)
+ ax.set_yticks(list(range(0, 101, 10)))
+ ax.grid()
+ ax.legend()
+
+ variable_name = self.study.variable_class.NAME
+ title = 'Evolution of {} trends (significative or not) wrt to the altitude'.format(variable_name)
+ ax.set_title(title)
+ self.show_or_save_to_file(specific_title=title)
class QuantitityAltitudeHypercubeVisualizer(HypercubeVisualizer):
diff --git a/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py b/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py
index 337449f621069410d4b45dc575eb24320244eee1..ad30484bdb1151090ac405346e3358253a3b5301 100644
--- a/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py
+++ b/experiment/meteo_france_SCM_study/visualization/studies_visualization/main_studies_visualizer.py
@@ -1,7 +1,7 @@
import time
from experiment.meteo_france_SCM_study.visualization.studies_visualization.hypercube_visualizer import \
- HypercubeVisualizer
+ HypercubeVisualizer, AltitudeHypercubeVisualizer
from experiment.trend_analysis.abstract_score import MannKendall, WeigthedScore, MeanScore, MedianScore
from experiment.trend_analysis.univariate_trend_test.abstract_gev_trend_test import GevLocationTrendTest, \
GevScaleTrendTest, GevShapeTrendTest
@@ -59,26 +59,28 @@ def altitude_trends_significant():
visualizer.trend_tests_percentage_evolution_with_altitude(trend_test_classes, starting_year_to_weights=None)
-def hypercube_test():
+def altitude_hypercube_test():
save_to_file = False
only_first_one = False
+ fast = False
altitudes = ALL_ALTITUDES[3:-6]
altitudes = ALL_ALTITUDES[2:4]
for study_class in SCM_STUDIES[:1]:
trend_test_class = [MannKendallTrendTest, GevLocationTrendTest, GevScaleTrendTest, GevShapeTrendTest][0]
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,
- altitudes=altitudes, multiprocessing=True)]
+ altitudes=altitudes)]
altitude_to_visualizer = OrderedDict(zip(altitudes, visualizers))
- visualizer = HypercubeVisualizer(altitude_to_visualizer, save_to_file=save_to_file,
- trend_class=trend_test_class, fast=True)
- print(visualizer.hypercube)
+ visualizer = AltitudeHypercubeVisualizer(altitude_to_visualizer, save_to_file=save_to_file,
+ trend_class=trend_test_class, fast=fast)
+ visualizer.visualize_trend_test()
+ # print(visualizer.df_hypercube)
def main_run():
# altitude_trends()
# altitude_trends_significant()
- hypercube_test()
+ altitude_hypercube_test()
if __name__ == '__main__':
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 ded791ecbb663514de9749be3779716efeca127f..645955e4657eede24fe0b877f4d099b6a70a153f 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
@@ -35,8 +35,7 @@ List[AbstractStudy]:
break
-def study_iterator(study_class, only_first_one=False, both_altitude=False, verbose=True, altitudes=None,
- multiprocessing=True) -> List[
+def study_iterator(study_class, only_first_one=False, both_altitude=False, verbose=True, altitudes=None) -> List[
AbstractStudy]:
all_studies = []
is_safran_study = study_class in [SafranSnowfall, ExtendedSafranSnowfall]
@@ -50,7 +49,7 @@ def study_iterator(study_class, only_first_one=False, both_altitude=False, verbo
if verbose:
print('alti: {}, nb_day: {} '.format(alti, nb_day), end='')
- study = study_class(altitude=alti, multiprocessing=multiprocessing)
+ study = study_class(altitude=alti)
massifs = study.altitude_to_massif_names[alti]
if verbose:
print('{} massifs: {} \n'.format(len(massifs), massifs))
diff --git a/test/test_experiment/test_SCM_study.py b/test/test_experiment/test_SCM_study.py
index 6b22c30965a3274220763d3f389394963866b81f..e8070c84f14c6f36af0efb63415b6d8ce18c255a 100644
--- a/test/test_experiment/test_SCM_study.py
+++ b/test/test_experiment/test_SCM_study.py
@@ -10,89 +10,83 @@ from experiment.meteo_france_SCM_study.safran.safran import SafranSnowfall, Exte
from experiment.meteo_france_SCM_study.visualization.study_visualization.study_visualizer import StudyVisualizer
from test.test_utils import load_scm_studies
+
# TESTS TO REACTIVATE SOMETIMES
-#
-# class TestSCMAllStudy(unittest.TestCase):
-#
-# def test_extended_run(self):
-# for study_class in [ExtendedSafranSnowfall]:
-# for study in study_iterator(study_class, only_first_one=True, both_altitude=False, verbose=False):
-# study_visualizer = StudyVisualizer(study, show=False, save_to_file=False)
-# study_visualizer.visualize_all_mean_and_max_graphs()
-# self.assertTrue(True)
-#
-# def test_scm_daily_data(self):
-# for study in load_scm_studies():
-# time_serie = study.year_to_daily_time_serie_array[1958]
-# self.assertTrue(time_serie.ndim == 2, msg='for {} ndim={}'.format(study.__repr__(), time_serie.ndim))
-# self.assertTrue(len(time_serie) in [365, 366],
-# msg="current time serie length for {} is {}".format(study.__repr__(), len(time_serie)))
-#
-#
-# class TestSCMStudy(unittest.TestCase):
-#
-# def setUp(self) -> None:
-# super().setUp()
-# self.study = None
-#
-# def check(self, massif_name_to_value_to_check):
-# df_annual_total = self.study.df_annual_total
-# for massif_name, value in massif_name_to_value_to_check.items():
-# found_value = df_annual_total.loc[:, massif_name].mean()
-# self.assertEqual(value, self.round(found_value))
-#
-# def round(self, f):
-# raise NotImplementedError
-#
-#
-# class TestSCMSafranSnowfall(TestSCMStudy):
-#
-# def setUp(self) -> None:
-# super().setUp()
-# self.study = SafranSnowfall()
-#
-# def test_massif_safran(self):
-# df_centroid = pd.read_csv(op.join(self.study.map_full_path, 'coordonnees_massifs_alpes.csv'))
-# # Assert that the massif names are the same between SAFRAN and the coordinate file
-# assert not set(self.study.study_massif_names).symmetric_difference(set(df_centroid['NOM']))
-#
-#
-# class TestSCMPrecipitation(TestSCMStudy):
-#
-# def setUp(self) -> None:
-# super().setUp()
-# self.study = SafranTotalPrecip(altitude=1800, year_min=1958, year_max=2002)
-#
-# def test_durand(self):
-# # Test based on Durand paper
-# # (some small differences probably due to the fact that SAFRAN model has evolved since then)
-# # Test for the mean total precipitation (rainfall + snowfall) between 1958 and 2002
-# self.check({
-# "Mercantour": 1281,
-# 'Chablais': 1922,
-# })
-#
-# def round(self, f):
-# return int(f)
-#
-#
-# class TestSafranTemperature(TestSCMStudy):
-#
-# def setUp(self):
-# super().setUp()
-# self.study = SafranTemperature(altitude=1800, year_min=1958, year_max=2002)
-#
-# def test_durand(self):
-# # Test based on Durand paper
-# # Test for the mean temperature between 1958 and 2002
-# self.check({
-# "Mercantour": 5.3,
-# 'Chablais': 3.5,
-# })
-#
-# def round(self, f):
-# return round(float(f), 1)
-#
-#
-# if __name__ == '__main__':
-# unittest.main()
+
+class TestSCMAllStudy(unittest.TestCase):
+
+ def test_extended_run(self):
+ for study_class in [ExtendedSafranSnowfall]:
+ for study in study_iterator(study_class, only_first_one=True, both_altitude=False, verbose=False):
+ study_visualizer = StudyVisualizer(study, show=False, save_to_file=False)
+ study_visualizer.visualize_all_mean_and_max_graphs()
+ self.assertTrue(True)
+
+
+class TestSCMStudy(unittest.TestCase):
+
+ def setUp(self) -> None:
+ super().setUp()
+ self.study = None
+
+ def check(self, massif_name_to_value_to_check):
+ df_annual_total = self.study.df_annual_total
+ for massif_name, value in massif_name_to_value_to_check.items():
+ found_value = df_annual_total.loc[:, massif_name].mean()
+ self.assertEqual(value, self.round(found_value))
+
+ def round(self, f):
+ raise NotImplementedError
+
+
+class TestSCMSafranSnowfall(TestSCMStudy):
+
+ def setUp(self) -> None:
+ super().setUp()
+ self.study = SafranSnowfall()
+
+ def test_massif_safran(self):
+ df_centroid = pd.read_csv(op.join(self.study.map_full_path, 'coordonnees_massifs_alpes.csv'))
+ # Assert that the massif names are the same between SAFRAN and the coordinate file
+ assert not set(self.study.study_massif_names).symmetric_difference(set(df_centroid['NOM']))
+
+
+class TestSCMPrecipitation(TestSCMStudy):
+
+ def setUp(self) -> None:
+ super().setUp()
+ self.study = SafranTotalPrecip(altitude=1800, year_min=1958, year_max=2002)
+
+ def test_durand(self):
+ # Test based on Durand paper
+ # (some small differences probably due to the fact that SAFRAN model has evolved since then)
+ # Test for the mean total precipitation (rainfall + snowfall) between 1958 and 2002
+ self.check({
+ "Mercantour": 1281,
+ 'Chablais': 1922,
+ })
+
+ def round(self, f):
+ return int(f)
+
+
+class TestSafranTemperature(TestSCMStudy):
+
+ def setUp(self):
+ super().setUp()
+ self.study = SafranTemperature(altitude=1800, year_min=1958, year_max=2002)
+
+ def test_durand(self):
+ # Test based on Durand paper
+ # Test for the mean temperature between 1958 and 2002
+ self.check({
+ "Mercantour": 5.3,
+ 'Chablais': 3.5,
+ })
+
+ def round(self, f):
+ return round(float(f), 1)
+
+
+if __name__ == '__main__':
+ unittest.main()