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author | RĂ©mi Flamary <remi.flamary@gmail.com> | 2018-05-29 16:16:41 +0200 |
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committer | GitHub <noreply@github.com> | 2018-05-29 16:16:41 +0200 |
commit | 90efa5a8b189214d1aeb81920b2bb04ce0c261ca (patch) | |
tree | 62e2f1a3cca2f4885e8c0e2a0b135a5f574d6a8c /test | |
parent | ec79b791f4f4a62f7c04b7bbf14fe2f5dcbb4c75 (diff) | |
parent | 54f0b47e55c966d5492e4ce19ec4e704ef3278d6 (diff) |
Merge pull request #47 from rflamary/bary
LP Wasserstein barycenter with scipy linear solver and/or cvxopt
Diffstat (limited to 'test')
-rw-r--r-- | test/test_gpu.py | 2 | ||||
-rw-r--r-- | test/test_ot.py | 36 |
2 files changed, 37 insertions, 1 deletions
diff --git a/test/test_gpu.py b/test/test_gpu.py index 615c2a7..1e97c45 100644 --- a/test/test_gpu.py +++ b/test/test_gpu.py @@ -76,4 +76,4 @@ def test_gpu_sinkhorn_lpl1(): time3 - time2)) describe_res(G2) - np.testing.assert_allclose(G1, G2, rtol=1e-5, atol=1e-5) + np.testing.assert_allclose(G1, G2, rtol=1e-3, atol=1e-3) diff --git a/test/test_ot.py b/test/test_ot.py index ea6d9dc..cc25bf4 100644 --- a/test/test_ot.py +++ b/test/test_ot.py @@ -10,6 +10,7 @@ import numpy as np import ot from ot.datasets import get_1D_gauss as gauss +import pytest def test_doctest(): @@ -117,6 +118,41 @@ def test_emd2_multi(): np.testing.assert_allclose(emd1, emdn) +def test_lp_barycenter(): + + a1 = np.array([1.0, 0, 0])[:, None] + a2 = np.array([0, 0, 1.0])[:, None] + + A = np.hstack((a1, a2)) + M = np.array([[0, 1.0, 4.0], [1.0, 0, 1.0], [4.0, 1.0, 0]]) + + # obvious barycenter between two diracs + bary0 = np.array([0, 1.0, 0]) + + bary = ot.lp.barycenter(A, M, [.5, .5]) + + np.testing.assert_allclose(bary, bary0, rtol=1e-5, atol=1e-7) + np.testing.assert_allclose(bary.sum(), 1) + + +@pytest.mark.skipif(not ot.lp.cvx.cvxopt, reason="No cvxopt available") +def test_lp_barycenter_cvxopt(): + + a1 = np.array([1.0, 0, 0])[:, None] + a2 = np.array([0, 0, 1.0])[:, None] + + A = np.hstack((a1, a2)) + M = np.array([[0, 1.0, 4.0], [1.0, 0, 1.0], [4.0, 1.0, 0]]) + + # obvious barycenter between two diracs + bary0 = np.array([0, 1.0, 0]) + + bary = ot.lp.barycenter(A, M, [.5, .5], solver=None) + + np.testing.assert_allclose(bary, bary0, rtol=1e-5, atol=1e-7) + np.testing.assert_allclose(bary.sum(), 1) + + def test_warnings(): n = 100 # nb bins m = 100 # nb bins |