diff options
author | Marc Glisse <marc.glisse@inria.fr> | 2019-11-05 23:01:31 +0100 |
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committer | Marc Glisse <marc.glisse@inria.fr> | 2019-11-05 23:01:31 +0100 |
commit | 94391b1cc232c5f66ae3cdadf865554c57f1308a (patch) | |
tree | 05621622d3f41638ab062a6ec825d28308937eea /src/python/test/test_wasserstein_distance.py | |
parent | 6e5f3f2c5ed908774c9005fa3ba07694bb2c6b0c (diff) |
Create GUDHI_PYTHON_MODULES_EXTRA without auto-import
Put Wasserstein in it.
Diffstat (limited to 'src/python/test/test_wasserstein_distance.py')
-rwxr-xr-x | src/python/test/test_wasserstein_distance.py | 38 |
1 files changed, 18 insertions, 20 deletions
diff --git a/src/python/test/test_wasserstein_distance.py b/src/python/test/test_wasserstein_distance.py index c1b568e2..a6bf9901 100755 --- a/src/python/test/test_wasserstein_distance.py +++ b/src/python/test/test_wasserstein_distance.py @@ -1,4 +1,4 @@ -import gudhi +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. @@ -23,28 +23,26 @@ def test_basic_wasserstein(): diag4 = np.array([[0, 3], [4, 8]]) emptydiag = np.array([[]]) - assert gudhi.wasserstein_distance(emptydiag, emptydiag, q=2., p=1.) == 0. - assert gudhi.wasserstein_distance(emptydiag, emptydiag, q=np.inf, p=1.) == 0. - assert gudhi.wasserstein_distance(emptydiag, emptydiag, q=np.inf, p=2.) == 0. - assert gudhi.wasserstein_distance(emptydiag, emptydiag, q=2., p=2.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, q=2., p=1.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, q=np.inf, p=1.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, q=np.inf, p=2.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, q=2., p=2.) == 0. - assert gudhi.wasserstein_distance(diag3, emptydiag, q=np.inf, p=1.) == 2. - assert gudhi.wasserstein_distance(diag3, emptydiag, q=1., p=1.) == 4. + assert wasserstein_distance(diag3, emptydiag, q=np.inf, p=1.) == 2. + assert wasserstein_distance(diag3, emptydiag, q=1., p=1.) == 4. - assert gudhi.wasserstein_distance(diag4, emptydiag, q=1., p=2.) == 5. # thank you Pythagorician triplets - assert gudhi.wasserstein_distance(diag4, emptydiag, q=np.inf, p=2.) == 2.5 - assert gudhi.wasserstein_distance(diag4, emptydiag, q=2., p=2.) == 3.5355339059327378 + assert wasserstein_distance(diag4, emptydiag, q=1., p=2.) == 5. # thank you Pythagorician triplets + assert wasserstein_distance(diag4, emptydiag, q=np.inf, p=2.) == 2.5 + assert wasserstein_distance(diag4, emptydiag, q=2., p=2.) == 3.5355339059327378 - assert gudhi.wasserstein_distance(diag1, diag2, q=2., p=1.) == 1.4453593023967701 - assert gudhi.wasserstein_distance(diag1, diag2, q=2.35, p=1.74) == 0.9772734057168739 + assert wasserstein_distance(diag1, diag2, q=2., p=1.) == 1.4453593023967701 + assert wasserstein_distance(diag1, diag2, q=2.35, p=1.74) == 0.9772734057168739 - assert gudhi.wasserstein_distance(diag1, emptydiag, q=2.35, p=1.7863) == 3.141592214572228 + assert wasserstein_distance(diag1, emptydiag, q=2.35, p=1.7863) == 3.141592214572228 - assert gudhi.wasserstein_distance(diag3, diag4, q=1., p=1.) == 3. - assert gudhi.wasserstein_distance(diag3, diag4, q=np.inf, p=1.) == 3. # no diag matching here - assert gudhi.wasserstein_distance(diag3, diag4, q=np.inf, p=2.) == np.sqrt(5) - assert gudhi.wasserstein_distance(diag3, diag4, q=1., p=2.) == np.sqrt(5) - assert gudhi.wasserstein_distance(diag3, diag4, q=4.5, p=2.) == np.sqrt(5) - - + assert wasserstein_distance(diag3, diag4, q=1., p=1.) == 3. + assert wasserstein_distance(diag3, diag4, q=np.inf, p=1.) == 3. # no diag matching here + assert wasserstein_distance(diag3, diag4, q=np.inf, p=2.) == np.sqrt(5) + assert wasserstein_distance(diag3, diag4, q=1., p=2.) == np.sqrt(5) + assert wasserstein_distance(diag3, diag4, q=4.5, p=2.) == np.sqrt(5) |