diff --git a/extreme_estimator/estimator/abstract_estimator.py b/extreme_estimator/estimator/abstract_estimator.py
index 32027aaca4ad4590af6b700cdd19f263b7f89f4a..72e7670f2feb119fb7e78a33de421fa1181faec4 100644
--- a/extreme_estimator/estimator/abstract_estimator.py
+++ b/extreme_estimator/estimator/abstract_estimator.py
@@ -4,7 +4,7 @@ from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
class AbstractEstimator(object):
- DURATION = 'Duration'
+ DURATION = 'Average duration'
MAE_ERROR = 'Mean Average Error'
def __init__(self, dataset: AbstractDataset):
diff --git a/extreme_estimator/robustness_plot/msp_robustness.py b/extreme_estimator/robustness_plot/msp_robustness.py
index 10c892063311975548a3c0aecfce3e9e42c84e66..b73fb0f43ee8a5c378166ed33002835e3ed5f98f 100644
--- a/extreme_estimator/robustness_plot/msp_robustness.py
+++ b/extreme_estimator/robustness_plot/msp_robustness.py
@@ -1,12 +1,15 @@
-from extreme_estimator.R_fit.max_stable_fit.abstract_max_stable_model import AbstractMaxStableModel
-from extreme_estimator.R_fit.max_stable_fit.max_stable_models import Smith, BrownResnick
+from extreme_estimator.R_fit.max_stable_fit.abstract_max_stable_model import AbstractMaxStableModel, CovarianceFunction
+from extreme_estimator.R_fit.max_stable_fit.max_stable_models import Smith, BrownResnick, Schlather, ExtremalT
from extreme_estimator.estimator.abstract_estimator import AbstractEstimator
from extreme_estimator.estimator.unitary_msp_estimator import MaxStableEstimator
from extreme_estimator.robustness_plot.multiple_plot import MultiplePlot
from extreme_estimator.robustness_plot.single_plot import SinglePlot
from spatio_temporal_dataset.dataset.simulation_dataset import SimulatedDataset
-from spatio_temporal_dataset.spatial_coordinates.alps_station_coordinates import AlpsStationCoordinatesBetweenZeroAndOne
-from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinates
+from spatio_temporal_dataset.spatial_coordinates.abstract_coordinates import AbstractSpatialCoordinates
+from spatio_temporal_dataset.spatial_coordinates.alps_station_coordinates import \
+ AlpsStationCoordinatesBetweenZeroAndOne, AlpsStationCoordinatesBetweenZeroAndTwo
+from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1, \
+ CircleCoordinatesRadius2
from extreme_estimator.robustness_plot.display_item import DisplayItem
@@ -16,10 +19,15 @@ class MaxStableDisplayItem(DisplayItem):
return value.cov_mod
+class SpatialCoordinateDisplayItem(DisplayItem):
+
+ def display_name_from_value(self, value: AbstractSpatialCoordinates):
+ return str(value).split('.')[-1].split("'")[0]
+
+
class MspSpatial(object):
MaxStableModelItem = MaxStableDisplayItem('max_stable_model', Smith)
- SpatialCoordinateClassItem = DisplayItem('spatial_coordinate_class', CircleCoordinates)
- SpatialParamsItem = DisplayItem('spatial_params', {"r": 1})
+ SpatialCoordinateClassItem = SpatialCoordinateDisplayItem('spatial_coordinate_class', CircleCoordinatesRadius1)
NbStationItem = DisplayItem('Number of stations', 50)
NbObservationItem = DisplayItem('nb_obs', 60)
@@ -29,10 +37,9 @@ class MspSpatial(object):
**kwargs_single_point) # type: AbstractMaxStableModel
spatial_coordinate_class = self.SpatialCoordinateClassItem.value_from_kwargs(**kwargs_single_point)
nb_station = self.NbStationItem.value_from_kwargs(**kwargs_single_point)
- spatial_params = self.SpatialParamsItem.value_from_kwargs(**kwargs_single_point)
nb_obs = self.NbObservationItem.value_from_kwargs(**kwargs_single_point)
# Run the estimation
- spatial_coordinate = spatial_coordinate_class.from_nb_points(nb_points=nb_station, **spatial_params)
+ spatial_coordinate = spatial_coordinate_class.from_nb_points(nb_points=nb_station)
dataset = SimulatedDataset.from_max_stable_sampling(nb_obs=nb_obs, max_stable_model=max_stable_model,
spatial_coordinates=spatial_coordinate)
estimator = MaxStableEstimator(dataset, max_stable_model)
@@ -49,39 +56,54 @@ class SingleMspSpatial(SinglePlot, MspSpatial):
class MultipleMspSpatial(MultiplePlot, MspSpatial):
def compute_value_from_kwargs_single_point(self, **kwargs_single_point):
- print('here')
return self.msp_spatial_ordinates(**kwargs_single_point)
-def single_spatial_robustness_alps():
- spatial_robustness = SingleMspSpatial(grid_row_item=SingleMspSpatial.NbObservationItem,
- grid_column_item=SingleMspSpatial.SpatialCoordinateClassItem,
- plot_row_item=SingleMspSpatial.NbStationItem,
- plot_label_item=SingleMspSpatial.MaxStableModelItem)
- # Put only the parameter that will vary
- spatial_robustness.robustness_grid_plot(**{
- SingleMspSpatial.NbStationItem.name: [10, 30, 50, 70, 86][:],
- SingleMspSpatial.NbObservationItem.name: [10],
- SingleMspSpatial.MaxStableModelItem.name: [Smith(), BrownResnick()][:],
- SingleMspSpatial.SpatialCoordinateClassItem.name: [CircleCoordinates,
- AlpsStationCoordinatesBetweenZeroAndOne][:],
- })
+# def single_spatial_robustness_alps():
+# spatial_robustness = SingleMspSpatial(grid_row_item=SingleMspSpatial.NbObservationItem,
+# grid_column_item=SingleMspSpatial.SpatialCoordinateClassItem,
+# plot_row_item=SingleMspSpatial.NbStationItem,
+# plot_label_item=SingleMspSpatial.MaxStableModelItem)
+# # Put only the parameter that will vary
+# spatial_robustness.robustness_grid_plot(**{
+# SingleMspSpatial.NbStationItem.name: list(range(43, 87, 15)),
+# SingleMspSpatial.NbObservationItem.name: [10],
+# SingleMspSpatial.MaxStableModelItem.name: [Smith(), BrownResnick()][:],
+# SingleMspSpatial.SpatialCoordinateClassItem.name: [CircleCoordinatesRadius1,
+# AlpsStationCoordinatesBetweenZeroAndOne][:],
+# })
def multiple_spatial_robustness_alps():
+ nb_observation = 60
+ nb_sample = 10
+ plot_name = 'fast_result'
+ nb_stations = list(range(43, 87, 15))
+ # nb_stations = [10, 20, 30]
+
spatial_robustness = MultipleMspSpatial(
- grid_column_item=MspSpatial.MaxStableModelItem,
+ grid_column_item=MspSpatial.SpatialCoordinateClassItem,
plot_row_item=MspSpatial.NbStationItem,
- plot_label_item=MspSpatial.SpatialCoordinateClassItem,
- nb_samples=10)
+ plot_label_item=MspSpatial.MaxStableModelItem,
+ nb_samples=nb_sample,
+ main_title="Max stable analysis with {} years of observations".format(nb_observation),
+ plot_png_filename=plot_name
+ )
+ # Load all the models
+ msp_models = [Smith(), BrownResnick()]
+ # for covariance_function in CovarianceFunction:
+ # msp_models.extend([ExtremalT(covariance_function=covariance_function)])
+
# Put only the parameter that will vary
spatial_robustness.robustness_grid_plot(**{
SinglePlot.OrdinateItem.name: [AbstractEstimator.MAE_ERROR, AbstractEstimator.DURATION],
- MspSpatial.NbStationItem.name: [10, 20, 30, 50, 70, 86][:3],
- MspSpatial.NbObservationItem.name: 10,
- MspSpatial.MaxStableModelItem.name: [Smith(), BrownResnick()][:],
- MspSpatial.SpatialCoordinateClassItem.name: [CircleCoordinates,
- AlpsStationCoordinatesBetweenZeroAndOne][:],
+ MspSpatial.NbStationItem.name: nb_stations,
+ MspSpatial.NbObservationItem.name: nb_observation,
+ MspSpatial.MaxStableModelItem.name: msp_models,
+ MspSpatial.SpatialCoordinateClassItem.name: [CircleCoordinatesRadius1,
+ CircleCoordinatesRadius2,
+ AlpsStationCoordinatesBetweenZeroAndOne,
+ AlpsStationCoordinatesBetweenZeroAndTwo][:],
})
diff --git a/extreme_estimator/robustness_plot/multiple_plot.py b/extreme_estimator/robustness_plot/multiple_plot.py
index facb521ab5d4524c6d711ba2017a050f022eeaf1..ae98c0c09875d7808c63124dcdefcabc24b2d53a 100644
--- a/extreme_estimator/robustness_plot/multiple_plot.py
+++ b/extreme_estimator/robustness_plot/multiple_plot.py
@@ -8,19 +8,18 @@ class MultiplePlot(SinglePlot):
Each scalar, will be display on a grid row (to ease visual comparison)
"""
- def __init__(self, grid_column_item, plot_row_item, plot_label_item, nb_samples=1):
+ def __init__(self, grid_column_item, plot_row_item, plot_label_item, nb_samples=1, main_title='',
+ plot_png_filename=None):
super().__init__(grid_row_item=self.OrdinateItem, grid_column_item=grid_column_item,
plot_row_item=plot_row_item, plot_label_item=plot_label_item,
- nb_samples=nb_samples)
+ nb_samples=nb_samples, main_title=main_title, plot_png_filename=plot_png_filename)
self.kwargs_single_point_to_errors = {}
def cached_compute_value_from_kwargs_single_point(self, **kwargs_single_point):
- print('here1')
# Compute hash
hash_from_kwargs_single_point = self.hash_from_kwargs_single_point(kwargs_single_point)
# Either compute the errors or Reload them from cached results
if hash_from_kwargs_single_point in self.kwargs_single_point_to_errors:
- print('Load')
errors = self.kwargs_single_point_to_errors[hash_from_kwargs_single_point]
else:
errors = self.compute_value_from_kwargs_single_point(**kwargs_single_point)
@@ -30,6 +29,5 @@ class MultiplePlot(SinglePlot):
def hash_from_kwargs_single_point(self, kwargs_single_point):
items_except_error = [(k, v) for k, v in kwargs_single_point.items() if k != self.OrdinateItem.name]
ordered_dict_items_str = str(sorted(items_except_error, key=lambda x: x[0]))
- print(ordered_dict_items_str)
hash_from_kwargs_single_point = hash(ordered_dict_items_str)
return hash_from_kwargs_single_point
diff --git a/extreme_estimator/robustness_plot/single_plot.py b/extreme_estimator/robustness_plot/single_plot.py
index 4daf7de4aed2d8c142e852486d09115aed4c7dc0..06e6f2e25597128a90fef861ef3ecf37b8e4e253 100644
--- a/extreme_estimator/robustness_plot/single_plot.py
+++ b/extreme_estimator/robustness_plot/single_plot.py
@@ -1,9 +1,14 @@
+import os
+import os.path as op
+import random
+
import matplotlib.pyplot as plt
import numpy as np
from itertools import product
from extreme_estimator.estimator.abstract_estimator import AbstractEstimator
from extreme_estimator.robustness_plot.display_item import DisplayItem
+from utils import get_full_path
plt.style.use('seaborn-white')
@@ -12,12 +17,15 @@ class SinglePlot(object):
COLORS = ['blue', 'red', 'green', 'black', 'magenta', 'cyan']
OrdinateItem = DisplayItem('ordinate', AbstractEstimator.MAE_ERROR)
- def __init__(self, grid_row_item, grid_column_item, plot_row_item, plot_label_item, nb_samples=1):
+ def __init__(self, grid_row_item, grid_column_item, plot_row_item, plot_label_item, nb_samples=1, main_title='',
+ plot_png_filename=None):
self.grid_row_item = grid_row_item # type: DisplayItem
self.grid_column_item = grid_column_item # type: DisplayItem
self.plot_row_item = plot_row_item # type: DisplayItem
self.plot_label_item = plot_label_item # type: DisplayItem
self.nb_samples = nb_samples
+ self.main_title = main_title
+ self.plot_png_filename = plot_png_filename
def robustness_grid_plot(self, **kwargs):
# Extract Grid row and columns values
@@ -25,20 +33,41 @@ class SinglePlot(object):
grid_column_values = self.grid_column_item.values_from_kwargs(**kwargs)
nb_grid_rows, nb_grid_columns = len(grid_row_values), len(grid_column_values)
# Start the overall plot
- fig = plt.figure()
- fig.subplots_adjust(hspace=0.4, wspace=0.4)
- for i, (grid_row_value, grid_column_value) in enumerate(product(grid_row_values, grid_column_values), 1):
+ # fig = plt.figure()
+ fig, axes = plt.subplots(nb_grid_rows, nb_grid_columns, sharex='col', sharey='row')
+ fig.subplots_adjust(hspace=0.4, wspace=0.4, )
+ for (i, grid_row_value), (j, grid_column_value) in product(enumerate(grid_row_values),
+ enumerate(grid_column_values)):
print('Grid plot: {}={} {}={}'.format(self.grid_row_item.name, grid_row_value,
self.grid_column_item.name, grid_column_value))
- ax = fig.add_subplot(nb_grid_rows, nb_grid_columns, i)
+ ax = axes[i, j]
+ # ax = fig.add_subplot(nb_grid_rows, nb_grid_columns, i)
# Adapt the kwargs for the single plot
kwargs_single_plot = kwargs.copy()
kwargs_single_plot[self.grid_row_item.name] = grid_row_value
kwargs_single_plot[self.grid_column_item.name] = grid_column_value
self.robustness_single_plot(ax, **kwargs_single_plot)
- self.add_title(ax, grid_column_value, grid_row_value)
+ self.add_sub_title(ax, grid_column_value, grid_row_value)
+ fig.suptitle(self.main_title)
+ self.save_plot()
plt.show()
+ def save_plot(self):
+ if self.plot_png_filename is None:
+ return
+ assert isinstance(self.plot_png_filename, str)
+ relative_path = op.join('local', 'plot')
+ plot_pn_dirpath = get_full_path(relative_path=relative_path)
+ if not op.exists(plot_pn_dirpath):
+ os.makedirs(plot_pn_dirpath)
+ plot_pn_filepath = op.join(plot_pn_dirpath, self.plot_png_filename + '.png')
+ i = 2
+ while op.exists(plot_pn_filepath):
+ plot_pn_filepath = op.join(plot_pn_dirpath, self.plot_png_filename + str(i) + '.png')
+ i += 1
+ # plt.savefig(plot_pn_filepath, bbox_inches='tight')
+ plt.savefig(plot_pn_filepath)
+
def robustness_single_plot(self, ax, **kwargs_single_plot):
plot_row_values = self.plot_row_item.values_from_kwargs(**kwargs_single_plot)
plot_label_values = self.plot_label_item.values_from_kwargs(**kwargs_single_plot)
@@ -47,20 +76,28 @@ class SinglePlot(object):
mean_values, std_values = self.compute_mean_and_std_ordinate_values(kwargs_single_plot, ordinate_name,
plot_label_value, plot_row_values)
ax.errorbar(plot_row_values, mean_values, std_values,
- # linestyle='None', marker='^',
- linewidth = 0.5,
- color=self.COLORS[j % len(self.COLORS)],
- label=self.plot_label_item.display_name_from_value(plot_label_value))
+ # linestyle='None', marker='^',
+ linewidth=0.5,
+ color=self.COLORS[j % len(self.COLORS)],
+ label=self.plot_label_item.display_name_from_value(plot_label_value))
ax.legend()
+ # X axis
ax.set_xlabel(self.plot_row_item.name)
- ax.set_ylabel(ordinate_name)
+ plt.setp(ax.get_xticklabels(), visible=True)
+ ax.xaxis.set_tick_params(labelbottom=True)
+ # Y axis
+ ax.set_ylabel(ordinate_name + ' ({} samples)'.format(self.nb_samples))
+ plt.setp(ax.get_yticklabels(), visible=True)
+ ax.yaxis.set_tick_params(labelbottom=True)
- def compute_mean_and_std_ordinate_values(self, kwargs_single_plot, ordinate_name, plot_label_value, plot_row_values):
+ def compute_mean_and_std_ordinate_values(self, kwargs_single_plot, ordinate_name, plot_label_value,
+ plot_row_values):
all_ordinate_values = []
for nb_sample in range(self.nb_samples):
# Important to add the nb_sample argument, to differentiate the different experiments
kwargs_single_plot['nb_sample'] = nb_sample
- ordinate_values = self.compute_ordinate_values(kwargs_single_plot, ordinate_name, plot_label_value, plot_row_values)
+ ordinate_values = self.compute_ordinate_values(kwargs_single_plot, ordinate_name, plot_label_value,
+ plot_row_values)
all_ordinate_values.append(ordinate_values)
all_ordinate_values = np.array(all_ordinate_values)
return np.mean(all_ordinate_values, axis=0), np.std(all_ordinate_values, axis=0)
@@ -79,7 +116,6 @@ class SinglePlot(object):
assert not isinstance(v, list), '"{}" argument is a list'.format(k)
# Compute ordinate values
ordinate_name_to_ordinate_value = self.cached_compute_value_from_kwargs_single_point(**kwargs_single_point)
- print(ordinate_name, plot_row_value)
plot_row_value_to_ordinate_value[plot_row_value] = ordinate_name_to_ordinate_value[ordinate_name]
# Plot the figure
plot_ordinate_values = [plot_row_value_to_ordinate_value[plot_row_value] for plot_row_value in
@@ -92,7 +128,7 @@ class SinglePlot(object):
def cached_compute_value_from_kwargs_single_point(self, **kwargs_single_point) -> dict:
return self.compute_value_from_kwargs_single_point(**kwargs_single_point)
- def add_title(self, ax, grid_column_value, grid_row_value):
+ def add_sub_title(self, ax, grid_column_value, grid_row_value):
title_str = self.grid_row_item.display_name_from_value(grid_row_value)
title_str += ' ' if len(title_str) > 0 else ''
title_str += self.grid_column_item.display_name_from_value(grid_column_value)
diff --git a/spatio_temporal_dataset/dataset/simulation_dataset.py b/spatio_temporal_dataset/dataset/simulation_dataset.py
index 7312acc945598a29658bef1d76b0fb421b5cd608..6f8a1a6f5a0b8fda64103a7466fff1ce65a01032 100644
--- a/spatio_temporal_dataset/dataset/simulation_dataset.py
+++ b/spatio_temporal_dataset/dataset/simulation_dataset.py
@@ -3,7 +3,7 @@ import pandas as pd
from spatio_temporal_dataset.dataset.abstract_dataset import AbstractDataset
from spatio_temporal_dataset.temporal_maxima.temporal_maxima import TemporalMaxima
from spatio_temporal_dataset.spatial_coordinates.abstract_coordinates import AbstractSpatialCoordinates
-from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinates
+from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1
class SimulatedDataset(AbstractDataset):
diff --git a/spatio_temporal_dataset/spatial_coordinates/abstract_coordinates.py b/spatio_temporal_dataset/spatial_coordinates/abstract_coordinates.py
index e6cfba0b9eaa8bb3cf61c6cb804f9054f72bf3f0..3591e97ee7de973437d01627b9420e4f1e718877 100644
--- a/spatio_temporal_dataset/spatial_coordinates/abstract_coordinates.py
+++ b/spatio_temporal_dataset/spatial_coordinates/abstract_coordinates.py
@@ -73,10 +73,19 @@ class AbstractSpatialCoordinates(object):
def index(self):
return self.df_coord.index
- def __len__(self):
- return len(self.df_coord)
-
def visualization(self):
x, y = self.coord[:, 0], self.coord[:, 1]
plt.scatter(x, y)
plt.show()
+
+ # Magic Methods
+
+ def __len__(self):
+ return len(self.df_coord)
+
+ def __mul__(self, other: float):
+ self.df_coord *= other
+ return self
+
+ def __rmul__(self, other):
+ return self * other
\ No newline at end of file
diff --git a/spatio_temporal_dataset/spatial_coordinates/alps_station_coordinates.py b/spatio_temporal_dataset/spatial_coordinates/alps_station_coordinates.py
index fb1335eac9e6ff336d6037607bc532e6d1359631..fb07791f158717295955b9e04a97d49598a7ef0f 100644
--- a/spatio_temporal_dataset/spatial_coordinates/alps_station_coordinates.py
+++ b/spatio_temporal_dataset/spatial_coordinates/alps_station_coordinates.py
@@ -42,10 +42,18 @@ class AlpsStationCoordinatesBetweenZeroAndOne(AlpsStationCoordinates):
normalizing_function=BetweenZeroAndOneNormalization())
+class AlpsStationCoordinatesBetweenZeroAndTwo(AlpsStationCoordinatesBetweenZeroAndOne):
+
+ @classmethod
+ def from_csv(cls, csv_file='coord-lambert2'):
+ return 2 * super().from_csv(csv_file)
+
+
if __name__ == '__main__':
# AlpsStationCoordinate.transform_txt_into_csv()
# coord = AlpsStationCoordinates.from_csv()
# coord = AlpsStationCoordinates.from_nb_points(nb_points=60)
# coord = AlpsStationCoordinatesBetweenZeroAndOne.from_csv()
- coord = AlpsStationCoordinatesBetweenZeroAndOne.from_nb_points(nb_points=60)
+ coord = AlpsStationCoordinatesBetweenZeroAndTwo.from_nb_points(nb_points=60)
+ # coord = coord * 2
coord.visualization()
diff --git a/spatio_temporal_dataset/spatial_coordinates/generated_coordinates.py b/spatio_temporal_dataset/spatial_coordinates/generated_coordinates.py
index e49a6add9d5efdf1279ae440858c5caffd7deead..7acc626d9635a04c053ece73516d1756903f0663 100644
--- a/spatio_temporal_dataset/spatial_coordinates/generated_coordinates.py
+++ b/spatio_temporal_dataset/spatial_coordinates/generated_coordinates.py
@@ -7,11 +7,10 @@ from spatio_temporal_dataset.spatial_coordinates.abstract_coordinates import Abs
import matplotlib.pyplot as plt
-class CircleCoordinates(AbstractSpatialCoordinates):
+class CircleCoordinatesRadius1(AbstractSpatialCoordinates):
@classmethod
- def from_nb_points(cls, nb_points, **kwargs):
- max_radius = kwargs.get('max_radius', 1.0)
+ def from_nb_points(cls, nb_points, max_radius=1.0):
# Sample uniformly inside the circle
r = get_loaded_r()
angles = np.array(r.runif(nb_points, max=2 * math.pi))
@@ -28,6 +27,13 @@ class CircleCoordinates(AbstractSpatialCoordinates):
super().visualization()
+class CircleCoordinatesRadius2(CircleCoordinatesRadius1):
+
+ @classmethod
+ def from_nb_points(cls, nb_points, max_radius=1.0):
+ return 2 * super().from_nb_points(nb_points, max_radius)
+
+
if __name__ == '__main__':
- coord = CircleCoordinates.from_nb_points(nb_points=500, max_radius=1)
+ coord = CircleCoordinatesRadius1.from_nb_points(nb_points=500, max_radius=1)
coord.visualization()
diff --git a/test/extreme_estimator/test_max_stable_fit.py b/test/extreme_estimator/test_max_stable_fit.py
index 662c39ddee633451a698bd3931440ab6fb9169bb..9ea78042661010db918ccaec004a51e6840732eb 100644
--- a/test/extreme_estimator/test_max_stable_fit.py
+++ b/test/extreme_estimator/test_max_stable_fit.py
@@ -5,7 +5,7 @@ from extreme_estimator.R_fit.max_stable_fit.abstract_max_stable_model import \
from extreme_estimator.R_fit.max_stable_fit.max_stable_models import Smith, BrownResnick, Schlather, \
Geometric, ExtremalT, ISchlather
from spatio_temporal_dataset.dataset.simulation_dataset import SimulatedDataset
-from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinates
+from spatio_temporal_dataset.spatial_coordinates.generated_coordinates import CircleCoordinatesRadius1
class TestMaxStableFit(unittest.TestCase):
@@ -13,7 +13,7 @@ class TestMaxStableFit(unittest.TestCase):
def setUp(self):
super().setUp()
- self.spatial_coord = CircleCoordinates.from_nb_points(nb_points=5, max_radius=1)
+ self.spatial_coord = CircleCoordinatesRadius1.from_nb_points(nb_points=5, max_radius=1)
self.max_stable_models = []
for max_stable_class in self.MAX_STABLE_CLASSES:
if issubclass(max_stable_class, AbstractMaxStableModelWithCovarianceFunction):