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from gudhi.wasserstein import wasserstein_distance
import numpy as np
""" 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): Theo Lacombe
Copyright (C) 2019 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
__author__ = "Theo Lacombe"
__copyright__ = "Copyright (C) 2019 Inria"
__license__ = "MIT"
def test_basic_wasserstein():
diag1 = np.array([[2.7, 3.7], [9.6, 14.0], [34.2, 34.974]])
diag2 = np.array([[2.8, 4.45], [9.5, 14.1]])
diag3 = np.array([[0, 2], [4, 6]])
diag4 = np.array([[0, 3], [4, 8]])
emptydiag = np.array([[]])
assert wasserstein_distance(emptydiag, emptydiag, internal_p=2., q=1.) == 0.
assert wasserstein_distance(emptydiag, emptydiag, internal_p=np.inf, q=1.) == 0.
assert wasserstein_distance(emptydiag, emptydiag, internal_p=np.inf, q=2.) == 0.
assert wasserstein_distance(emptydiag, emptydiag, internal_p=2., q=2.) == 0.
assert wasserstein_distance(diag3, emptydiag, internal_p=np.inf, q=1.) == 2.
assert wasserstein_distance(diag3, emptydiag, internal_p=1., q=1.) == 4.
assert wasserstein_distance(diag4, emptydiag, internal_p=1., q=2.) == 5. # thank you Pythagorician triplets
assert wasserstein_distance(diag4, emptydiag, internal_p=np.inf, q=2.) == 2.5
assert wasserstein_distance(diag4, emptydiag, internal_p=2., q=2.) == 3.5355339059327378
assert wasserstein_distance(diag1, diag2, internal_p=2., q=1.) == 1.4453593023967701
assert wasserstein_distance(diag1, diag2, internal_p=2.35, q=1.74) == 0.9772734057168739
assert wasserstein_distance(diag1, emptydiag, internal_p=2.35, q=1.7863) == 3.141592214572228
assert wasserstein_distance(diag3, diag4, internal_p=1., q=1.) == 3.
assert wasserstein_distance(diag3, diag4, internal_p=np.inf, q=1.) == 3. # no diag matching here
assert wasserstein_distance(diag3, diag4, internal_p=np.inf, q=2.) == np.sqrt(5)
assert wasserstein_distance(diag3, diag4, internal_p=1., q=2.) == np.sqrt(5)
assert wasserstein_distance(diag3, diag4, internal_p=4.5, q=2.) == np.sqrt(5)
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