diff --git a/experiment/safran_study/__init__.py b/experiment/meteo_france_SCM_study/__init__.py
similarity index 100%
rename from experiment/safran_study/__init__.py
rename to experiment/meteo_france_SCM_study/__init__.py
diff --git a/experiment/safran_study/safran.py b/experiment/meteo_france_SCM_study/abstract_study.py
similarity index 79%
rename from experiment/safran_study/safran.py
rename to experiment/meteo_france_SCM_study/abstract_study.py
index 374ebb460281eee0e9c87193a3487bef05ca0d59..60b885496682eda338f7f74e633332da58260d19 100644
--- a/experiment/safran_study/safran.py
+++ b/experiment/meteo_france_SCM_study/abstract_study.py
@@ -1,15 +1,14 @@
import os
-from typing import List
-
import os.path as op
from collections import OrderedDict
+from typing import List
import matplotlib.pyplot as plt
import pandas as pd
from netCDF4 import Dataset
-from experiment.safran_study.massif import safran_massif_names_from_datasets
-from experiment.safran_study.snowfall_annual_maxima import SafranSnowfall
+from experiment.meteo_france_SCM_study.abstract_variable import AbstractVariable
+from experiment.meteo_france_SCM_study.massif import safran_massif_names_from_datasets
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
AbstractSpatialCoordinates
@@ -17,12 +16,13 @@ from spatio_temporal_dataset.spatio_temporal_observations.annual_maxima_observat
from utils import get_full_path, cached_property
-class Safran(object):
+class AbstractStudy(object):
- def __init__(self, safran_altitude=1800, nb_days_of_snowfall=1):
+ def __init__(self, safran_altitude=1800):
assert safran_altitude in [1800, 2400]
self.safran_altitude = safran_altitude
- self.nb_days_of_snowfall = nb_days_of_snowfall
+ self.model_name = None
+ self.variable_class = None
def write_to_file(self, df):
if not op.exists(self.result_full_path):
@@ -33,17 +33,14 @@ class Safran(object):
@property
def df_all_snowfall_concatenated(self):
- df_list = [pd.DataFrame(snowfall, columns=self.safran_massif_names) for snowfall in self.year_to_snowfall.values()]
+ df_list = [pd.DataFrame(snowfall, columns=self.safran_massif_names) for snowfall in
+ self.year_to_daily_time_serie.values()]
df_concatenated = pd.concat(df_list)
return df_concatenated
- @property
- def df_annual_maxima(self):
- return pd.DataFrame(self.year_to_annual_maxima, index=self.safran_massif_names).T
-
@property
def observations_annual_maxima(self):
- return AnnualMaxima(df_maxima_gev=self.df_annual_maxima.T)
+ return AnnualMaxima(df_maxima_gev=pd.DataFrame(self.year_to_annual_maxima, index=self.safran_massif_names))
""" Load some attributes only once """
@@ -51,19 +48,33 @@ class Safran(object):
def year_to_annual_maxima(self) -> OrderedDict:
# Map each year to an array of size nb_massif
year_to_annual_maxima = OrderedDict()
- for year, snowfall in self.year_to_snowfall.items():
- year_to_annual_maxima[year] = snowfall.max(axis=0)
+ for year, time_serie in self.year_to_daily_time_serie.items():
+ year_to_annual_maxima[year] = time_serie.max(axis=0)
return year_to_annual_maxima
@cached_property
- def year_to_snowfall(self) -> OrderedDict:
+ def year_to_dataset_ordered_dict(self) -> OrderedDict:
+ # Map each year to the correspond netCDF4 Dataset
+ year_to_dataset = OrderedDict()
+ nc_files = [(int(f.split('_')[1][:4]), f) for f in os.listdir(self.safran_full_path) if f.endswith('.nc')]
+ for year, nc_file in sorted(nc_files, key=lambda t: t[0]):
+ year_to_dataset[year] = Dataset(op.join(self.safran_full_path, nc_file))
+ return year_to_dataset
+
+ @cached_property
+ def year_to_daily_time_serie(self) -> OrderedDict:
# Map each year to a matrix of size 365-nb_days_consecutive+1 x nb_massifs
- year_to_safran_snowfall = {year: SafranSnowfall(dataset) for year, dataset in
- self.year_to_dataset_ordered_dict.items()}
- year_to_snowfall = OrderedDict()
+ year_to_variable = {year: self.instantiate_variable_object(dataset) for year, dataset in
+ self.year_to_dataset_ordered_dict.items()}
+ year_to_daily_time_serie = OrderedDict()
for year in self.year_to_dataset_ordered_dict.keys():
- year_to_snowfall[year] = year_to_safran_snowfall[year].annual_snowfall(self.nb_days_of_snowfall)
- return year_to_snowfall
+ year_to_daily_time_serie[year] = year_to_variable[year].daily_time_serie
+ return year_to_daily_time_serie
+
+ def instantiate_variable_object(self, dataset) -> AbstractVariable:
+ return self.variable_class(dataset)
+
+ ##########
@property
def safran_massif_names(self) -> List[str]:
@@ -74,15 +85,6 @@ class Safran(object):
def safran_massif_id_to_massif_name(self):
return dict(enumerate(self.safran_massif_names))
- @cached_property
- def year_to_dataset_ordered_dict(self) -> OrderedDict:
- # Map each year to the correspond netCDF4 Dataset
- year_to_dataset = OrderedDict()
- nc_files = [(int(f.split('_')[1][:4]), f) for f in os.listdir(self.safran_full_path) if f.endswith('.nc')]
- for year, nc_file in sorted(nc_files, key=lambda t: t[0]):
- year_to_dataset[year] = Dataset(op.join(self.safran_full_path, nc_file))
- return year_to_dataset
-
@cached_property
def massifs_coordinates(self) -> AbstractSpatialCoordinates:
# Coordinate object that represents the massif coordinates in Lambert extended
@@ -105,7 +107,6 @@ class Safran(object):
df_centroid = self.load_df_centroid()
return dict(zip(df_centroid['id'], df_centroid.index))
-
""" Visualization methods """
def visualize(self, ax=None, massif_name_to_fill_kwargs=None, show=True, fill=True):
@@ -142,7 +143,8 @@ class Safran(object):
@property
def safran_full_path(self) -> str:
- return op.join(self.full_path, 'safran-crocus_{}'.format(self.safran_altitude), 'Safran')
+ assert self.model_name in ['Safran', 'Crocus']
+ return op.join(self.full_path, 'safran-crocus_{}'.format(self.safran_altitude), self.model_name)
@property
def map_full_path(self) -> str:
@@ -150,4 +152,4 @@ class Safran(object):
@property
def result_full_path(self) -> str:
- return op.join(self.full_path, 'results')
\ No newline at end of file
+ return op.join(self.full_path, 'results')
diff --git a/experiment/meteo_france_SCM_study/abstract_variable.py b/experiment/meteo_france_SCM_study/abstract_variable.py
new file mode 100644
index 0000000000000000000000000000000000000000..acc653c78c5916291296296cd6af89d0018c03a7
--- /dev/null
+++ b/experiment/meteo_france_SCM_study/abstract_variable.py
@@ -0,0 +1,11 @@
+
+
+class AbstractVariable(object):
+
+ def __init__(self, dataset):
+ self.dataset = dataset
+
+ @property
+ def daily_time_serie(self):
+ # Return an array of size length of time series x nb_massif
+ raise NotImplementedError
\ No newline at end of file
diff --git a/experiment/meteo_france_SCM_study/crocus/__init__.py b/experiment/meteo_france_SCM_study/crocus/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/experiment/meteo_france_SCM_study/crocus/crocus.py b/experiment/meteo_france_SCM_study/crocus/crocus.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a9c21775dddb87481ecdcc2d7352619d57d38ad
--- /dev/null
+++ b/experiment/meteo_france_SCM_study/crocus/crocus.py
@@ -0,0 +1,19 @@
+from experiment.meteo_france_SCM_study.abstract_study import AbstractStudy
+from experiment.meteo_france_SCM_study.crocus.crocus_variables import CrocusSweVariable, CrocusDepthVariable
+
+
+class Crocus(AbstractStudy):
+
+ def __init__(self, safran_altitude=1800, crocus_variable_class=CrocusSweVariable):
+ super().__init__(safran_altitude)
+ self.model_name = 'Crocus'
+ assert crocus_variable_class in [CrocusSweVariable, CrocusDepthVariable]
+ self.variable_class = crocus_variable_class
+
+if __name__ == '__main__':
+ for variable_class in [CrocusSweVariable, CrocusDepthVariable]:
+ study = Crocus(crocus_variable_class=variable_class)
+ # d = study.year_to_dataset_ordered_dict[1960]
+ # print(d)
+ a = study.year_to_daily_time_serie[1960]
+ print(a.shape)
\ No newline at end of file
diff --git a/experiment/meteo_france_SCM_study/crocus/crocus_variables.py b/experiment/meteo_france_SCM_study/crocus/crocus_variables.py
new file mode 100644
index 0000000000000000000000000000000000000000..1825a43791648c6049cd6e711d0901b238dd4a11
--- /dev/null
+++ b/experiment/meteo_france_SCM_study/crocus/crocus_variables.py
@@ -0,0 +1,27 @@
+import numpy as np
+
+from experiment.meteo_france_SCM_study.abstract_variable import AbstractVariable
+
+
+class CrocusVariable(AbstractVariable):
+
+ def __init__(self, dataset, variable_name):
+ super().__init__(dataset)
+ self.variable_name = variable_name
+
+ @property
+ def daily_time_serie(self):
+ # So far the dimension of the time serie is 1460 x 23
+ return np.array(self.dataset.variables[self.variable_name])[:, 0, :]
+
+
+class CrocusSweVariable(CrocusVariable):
+
+ def __init__(self, dataset):
+ super().__init__(dataset, 'SNOWSWE')
+
+
+class CrocusDepthVariable(CrocusVariable):
+
+ def __init__(self, dataset):
+ super().__init__(dataset, "SNOWDEPTH")
diff --git a/experiment/safran_study/main_visualize_safran.py b/experiment/meteo_france_SCM_study/main_visualize.py
similarity index 81%
rename from experiment/safran_study/main_visualize_safran.py
rename to experiment/meteo_france_SCM_study/main_visualize.py
index 2f5bc83b52b50eb267947fb27cef0751639e6edd..f20d24f0e7d4ff4ae1e438176527b527f472efe4 100644
--- a/experiment/safran_study/main_visualize_safran.py
+++ b/experiment/meteo_france_SCM_study/main_visualize.py
@@ -1,7 +1,7 @@
-from experiment.safran_study.safran import Safran
+from experiment.meteo_france_SCM_study.safran.safran import Safran
from itertools import product
-from experiment.safran_study.safran_visualizer import SafranVisualizer
+from experiment.meteo_france_SCM_study.safran.safran_visualizer import SafranVisualizer
def load_all_safran(only_first_one=False):
diff --git a/experiment/safran_study/massif.py b/experiment/meteo_france_SCM_study/massif.py
similarity index 100%
rename from experiment/safran_study/massif.py
rename to experiment/meteo_france_SCM_study/massif.py
diff --git a/experiment/meteo_france_SCM_study/safran/__init__.py b/experiment/meteo_france_SCM_study/safran/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/experiment/safran_study/fit_safran.py b/experiment/meteo_france_SCM_study/safran/fit_safran.py
similarity index 91%
rename from experiment/safran_study/fit_safran.py
rename to experiment/meteo_france_SCM_study/safran/fit_safran.py
index 843150240e3c069adaa62c86100a5933be9724ac..0e93a16446b3f0fb73e47ac26e7bd2901c686f12 100644
--- a/experiment/safran_study/fit_safran.py
+++ b/experiment/meteo_france_SCM_study/safran/fit_safran.py
@@ -1,6 +1,6 @@
import pandas as pd
-from experiment.safran_study.safran_extended import ExtendedSafran
+from experiment.meteo_france_SCM_study.safran.safran_extended import ExtendedSafran
from utils import VERSION
diff --git a/experiment/meteo_france_SCM_study/safran/safran.py b/experiment/meteo_france_SCM_study/safran/safran.py
new file mode 100644
index 0000000000000000000000000000000000000000..a647d239c950af780ba5b5314059e2995592f3da
--- /dev/null
+++ b/experiment/meteo_france_SCM_study/safran/safran.py
@@ -0,0 +1,32 @@
+from typing import List
+
+import os.path as op
+from collections import OrderedDict
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+from experiment.meteo_france_SCM_study.abstract_study import AbstractStudy
+from experiment.meteo_france_SCM_study.abstract_variable import AbstractVariable
+from experiment.meteo_france_SCM_study.massif import safran_massif_names_from_datasets
+from experiment.meteo_france_SCM_study.safran.safran_snowfall_variable import SafranSnowfallVariable
+from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
+from spatio_temporal_dataset.coordinates.spatial_coordinates.abstract_spatial_coordinates import \
+ AbstractSpatialCoordinates
+from spatio_temporal_dataset.spatio_temporal_observations.annual_maxima_observations import AnnualMaxima
+from utils import cached_property
+
+
+class Safran(AbstractStudy):
+
+ def __init__(self, safran_altitude=1800, nb_days_of_snowfall=1):
+ super().__init__(safran_altitude)
+ self.nb_days_of_snowfall = nb_days_of_snowfall
+ self.model_name = 'Safran'
+ self.variable_class = SafranSnowfallVariable
+
+
+ def instantiate_variable_object(self, dataset) -> AbstractVariable:
+ return self.variable_class(dataset, self.nb_days_of_snowfall)
+
+
diff --git a/experiment/safran_study/safran_extended.py b/experiment/meteo_france_SCM_study/safran/safran_extended.py
similarity index 95%
rename from experiment/safran_study/safran_extended.py
rename to experiment/meteo_france_SCM_study/safran/safran_extended.py
index 775a47d9d909a5c12f20f2fc8f01886e4f5ef505..691d719265136e6f91210869c43e88ea78e521ed 100644
--- a/experiment/safran_study/safran_extended.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_extended.py
@@ -2,7 +2,7 @@ from collections import OrderedDict
import pandas as pd
-from experiment.safran_study.safran import Safran
+from experiment.meteo_france_SCM_study.safran.safran import Safran
from utils import cached_property
diff --git a/experiment/safran_study/snowfall_annual_maxima.py b/experiment/meteo_france_SCM_study/safran/safran_snowfall_variable.py
similarity index 77%
rename from experiment/safran_study/snowfall_annual_maxima.py
rename to experiment/meteo_france_SCM_study/safran/safran_snowfall_variable.py
index f2bce13bc83a236b831bd873222a1025e4475675..04b25737727e049d82fd0900b056260af4a2f47f 100644
--- a/experiment/safran_study/snowfall_annual_maxima.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_snowfall_variable.py
@@ -1,7 +1,9 @@
import numpy as np
+from experiment.meteo_france_SCM_study.abstract_variable import AbstractVariable
-class SafranSnowfall(object):
+
+class SafranSnowfallVariable(AbstractVariable):
""""
Hypothesis:
@@ -17,12 +19,9 @@ class SafranSnowfall(object):
(but here the problem might be that the x_i are not idnependent, they are highly dependent one from another)
"""
- def __init__(self, dataset):
- self.dataset = dataset
- # Corresponding starting times
- # start_datetime = datetime(year=year, month=8, day=1, hour=6)
- # start_times = np.array(dataset.variables['time'])[:-1]
-
+ def __init__(self, dataset, nb_consecutive_days_of_snowfall=1):
+ super().__init__(dataset)
+ self.nb_consecutive_days_of_snowfall = nb_consecutive_days_of_snowfall
# Compute the daily snowfall in kg/m2
snowfall_rates = np.array(dataset.variables['Snowf'])
mean_snowfall_rates = 0.5 * (snowfall_rates[:-1] + snowfall_rates[1:])
@@ -31,13 +30,13 @@ class SafranSnowfall(object):
nb_days = len(hourly_snowfall) // 24
self.daily_snowfall = [sum(hourly_snowfall[24 * i:24 * (i+1)]) for i in range(nb_days)]
- def annual_snowfall(self, nb_days_of_snowfall=1):
+ @property
+ def daily_time_serie(self):
# Aggregate the daily snowfall by the number of consecutive days
- shifted_list = [self.daily_snowfall[i:] for i in range(nb_days_of_snowfall)]
+ shifted_list = [self.daily_snowfall[i:] for i in range(self.nb_consecutive_days_of_snowfall)]
# First element of shifted_list is of length n, Second element of length n-1, Third element n-2....
# The zip is done with respect to the shortest list
snowfall_in_consecutive_days = [sum(e) for e in zip(*shifted_list)]
- # Return the maximum of the aggregated list
# The returned array is of size n-nb_days+1 x nb_massif
return np.array(snowfall_in_consecutive_days)
diff --git a/experiment/safran_study/safran_visualizer.py b/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
similarity index 91%
rename from experiment/safran_study/safran_visualizer.py
rename to experiment/meteo_france_SCM_study/safran/safran_visualizer.py
index 567e14a10563948df6961aa4a1658574e235c432..8a8c79db81c39be6270ca9cfcfd8abccb6498239 100644
--- a/experiment/safran_study/safran_visualizer.py
+++ b/experiment/meteo_france_SCM_study/safran/safran_visualizer.py
@@ -1,22 +1,17 @@
-import matplotlib as mpl
-import matplotlib.colorbar as cbar
import matplotlib.pyplot as plt
import pandas as pd
-from matplotlib import cm
-from mpl_toolkits.axes_grid1 import make_axes_locatable
from extreme_estimator.estimator.full_estimator.abstract_full_estimator import \
FullEstimatorInASingleStepWithSmoothMargin
from extreme_estimator.estimator.margin_estimator.abstract_margin_estimator import SmoothMarginEstimator
from extreme_estimator.extreme_models.margin_model.smooth_margin_model import LinearAllParametersAllDimsMarginModel
from extreme_estimator.extreme_models.max_stable_model.max_stable_models import Smith
-from extreme_estimator.margin_fits.extreme_params import ExtremeParams
from extreme_estimator.margin_fits.gev.gev_params import GevParams
from extreme_estimator.margin_fits.gev.gevmle_fit import GevMleFit
from extreme_estimator.margin_fits.gpd.gpd_params import GpdParams
from extreme_estimator.margin_fits.gpd.gpdmle_fit import GpdMleFit
-from experiment.safran_study.safran import Safran
-from extreme_estimator.margin_fits.plot.create_shifted_cmap import plot_extreme_param, get_color_rbga
+from experiment.meteo_france_SCM_study.safran.safran import Safran
+from extreme_estimator.margin_fits.plot.create_shifted_cmap import get_color_rbga_shifted
from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
@@ -76,7 +71,7 @@ class SafranVisualizer(object):
massif_name_to_value = df.loc[gev_param_name, :].to_dict()
# Compute the middle point of the values for the color map
values = list(massif_name_to_value.values())
- colors = get_color_rbga(ax, gev_param_name, values)
+ colors = get_color_rbga_shifted(ax, gev_param_name, values)
massif_name_to_fill_kwargs = {massif_name: {'color': color} for massif_name, color in
zip(self.safran.safran_massif_names, colors)}
self.safran.visualize(ax=ax, massif_name_to_fill_kwargs=massif_name_to_fill_kwargs, show=False)
@@ -98,7 +93,7 @@ class SafranVisualizer(object):
@property
def df_gev_mle_each_massif(self):
# Fit a margin_fits on each massif
- massif_to_gev_mle = {massif_name: GevMleFit(self.safran.df_annual_maxima[massif_name]).gev_params.summary_serie
+ massif_to_gev_mle = {massif_name: GevMleFit(self.safran.observations_annual_maxima.loc[massif_name]).gev_params.summary_serie
for massif_name in self.safran.safran_massif_names}
return pd.DataFrame(massif_to_gev_mle, columns=self.safran.safran_massif_names)
diff --git a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
index 14e0ca22037eae84145d42e02d8c93cbbc245029..9fec7d591fb2548c320a9e588d49c9aeae2180a1 100644
--- a/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
+++ b/extreme_estimator/extreme_models/margin_model/margin_function/abstract_margin_function.py
@@ -6,7 +6,7 @@ import numpy as np
import pandas as pd
from extreme_estimator.margin_fits.gev.gev_params import GevParams
-from extreme_estimator.margin_fits.plot.create_shifted_cmap import plot_extreme_param
+from extreme_estimator.margin_fits.plot.create_shifted_cmap import plot_extreme_param, imshow_shifted
from spatio_temporal_dataset.coordinates.abstract_coordinates import AbstractCoordinates
from spatio_temporal_dataset.slicer.split import Split
@@ -47,7 +47,8 @@ class AbstractMarginFunction(object):
# Visualization function
- def set_datapoint_display_parameters(self, spatio_temporal_split=Split.all, datapoint_marker=None, filter=None, color=None,
+ def set_datapoint_display_parameters(self, spatio_temporal_split=Split.all, datapoint_marker=None, filter=None,
+ color=None,
linewidth=1, datapoint_display=False):
self.datapoint_display = datapoint_display
self.spatio_temporal_split = spatio_temporal_split
@@ -132,13 +133,10 @@ class AbstractMarginFunction(object):
grid = self.grid_2D(x, y)
if ax is None:
ax = plt.gca()
- imshow_method = ax.imshow
- values = grid[gev_param_name]
- norm, shifted_cmap = plot_extreme_param(ax, gev_param_name, values)
+ # Special display
+ imshow_shifted(ax, gev_param_name, grid[gev_param_name], x, y)
- imshow_method(values, extent=(x.min(), x.max(), y.min(), y.max()),
- interpolation='nearest', cmap=shifted_cmap)
# X axis
ax.set_xlabel('coordinate X')
plt.setp(ax.get_xticklabels(), visible=True)
@@ -151,7 +149,6 @@ class AbstractMarginFunction(object):
if show:
plt.show()
-
def grid_2D(self, x, y):
resolution = 100
grid = []
diff --git a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
index dc72f36e4c2300a9d3272503e8179139f4e5e53e..9e83b2789679c18307a3e923cd4d2ae281eb9222 100644
--- a/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
+++ b/extreme_estimator/margin_fits/plot/create_shifted_cmap.py
@@ -32,7 +32,7 @@ def plot_extreme_param(ax, gev_param_name, values):
return norm, shifted_cmap
-def get_color_rbga(ax, gev_param_name, values):
+def get_color_rbga_shifted(ax, gev_param_name, values):
"""
For some display it was necessary to transform dark blue values into white values
"""
@@ -40,5 +40,20 @@ def get_color_rbga(ax, gev_param_name, values):
m = cm.ScalarMappable(norm=norm, cmap=shifted_cmap)
colors = [m.to_rgba(value) for value in values]
if gev_param_name != ExtremeParams.SHAPE:
- colors = [color if color != (0, 0, 1, 1) else (1, 1, 1, 1) for color in colors]
+ colors = [color if color[2] == 1 else (1, 1, 1, 1) for color in colors]
return colors
+
+
+def imshow_shifted(ax, gev_param_name, values, x, y):
+ norm, shifted_cmap = plot_extreme_param(ax, gev_param_name, values)
+ shifted_cmap.set_bad(color='white')
+
+ masked_array = values
+ if gev_param_name != ExtremeParams.SHAPE:
+ epsilon = 1.0
+ value = np.min(values)
+ # The right blue corner will be blue (but most of the time, another display will be on top)
+ masked_array[-1, -1] = value - epsilon
+
+ ax.imshow(masked_array, extent=(x.min(), x.max(), y.min(), y.max()), cmap=shifted_cmap)
+
diff --git a/test/test_experiment/test_safran/test_safran_visualizer.py b/test/test_experiment/test_safran/test_safran_visualizer.py
index d63d2e97b6164a67b86ebaec193d0f9b01470e49..6f94d5c4b4b365993a3a577f55121f7fb6568bb8 100644
--- a/test/test_experiment/test_safran/test_safran_visualizer.py
+++ b/test/test_experiment/test_safran/test_safran_visualizer.py
@@ -1,7 +1,7 @@
# import unittest
#
-# from experiment.safran_study.safran import Safran
-# from experiment.safran_study.safran_visualizer import SafranVisualizer
+# from experiment.meteo_france_SCM_study.safran import Safran
+# from experiment.meteo_france_SCM_study.safran_visualizer import SafranVisualizer
#
#
# class TestSafranVisualizer(unittest.TestCase):
diff --git a/test/test_utils.py b/test/test_utils.py
index 3f2c854e0038123855c00a02b2ac3d2251a63d59..2bb92efefa07f84a633241d0ac9c4624381170d4 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -7,7 +7,7 @@ from extreme_estimator.extreme_models.max_stable_model.abstract_max_stable_model
AbstractMaxStableModelWithCovarianceFunction, CovarianceFunction
from extreme_estimator.extreme_models.max_stable_model.max_stable_models import Smith, BrownResnick, Schlather, \
Geometric, ExtremalT, ISchlather
-from experiment.safran_study.safran import Safran
+from experiment.meteo_france_SCM_study.safran.safran import Safran
from spatio_temporal_dataset.coordinates.spatial_coordinates.alps_station_3D_coordinates import \
AlpsStation3DCoordinatesWithAnisotropy
from spatio_temporal_dataset.coordinates.spatial_coordinates.generated_spatial_coordinates import \