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""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
Author(s): Vincent Rouvreau
Copyright (C) 2021 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
from gudhi.sklearn.cubical_persistence import CubicalPersistence
import numpy as np
from sklearn import datasets
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2021 Inria"
__license__ = "MIT"
CUBICAL_PERSISTENCE_H0_IMG0 = np.array([[0., 6.], [0., 8.], [ 0., np.inf]])
def test_simple_constructor_from_top_cells():
cells = datasets.load_digits().images[0]
cp = CubicalPersistence(only_this_dim = 0)
np.testing.assert_array_equal(cp._CubicalPersistence__transform(cells),
[CUBICAL_PERSISTENCE_H0_IMG0])
cp = CubicalPersistence(max_persistence_dimension = 2)
diags = cp._CubicalPersistence__transform(cells)
assert len(diags) == 3
np.testing.assert_array_equal(diags[0],
CUBICAL_PERSISTENCE_H0_IMG0)
def test_simple_constructor_from_top_cells_list():
digits = datasets.load_digits().images[:10]
cp = CubicalPersistence(only_this_dim = 0, n_jobs=-2)
diags = cp.fit_transform(digits)
assert len(diags) == 10
np.testing.assert_array_equal(diags[0],
CUBICAL_PERSISTENCE_H0_IMG0)
cp = CubicalPersistence(max_persistence_dimension = 1, n_jobs=-1)
diagsH0H1 = cp.fit_transform(digits)
assert len(diagsH0H1) == 10
for idx in range(10):
np.testing.assert_array_equal(diags[idx], diagsH0H1[idx][0])
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