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| author | tlacombe <lacombe1993@gmail.com> | 2020-03-10 15:45:45 +0100 |
|---|---|---|
| committer | tlacombe <lacombe1993@gmail.com> | 2020-03-10 15:45:45 +0100 |
| commit | 2eca5c75b1fbd7157e2656b875e730dc5f00f373 (patch) | |
| tree | e3c2a0053590c153ae6b04ba92f9bb8ef73310c8 /src | |
| parent | 570a9b83eb3f714bc52735dae289a5195874bf41 (diff) | |
removed P[P < 0.5] thresholding ; as it shouldn't happen anymore.
Diffstat (limited to 'src')
| -rw-r--r-- | src/python/gudhi/wasserstein.py | 1 |
1 files changed, 0 insertions, 1 deletions
diff --git a/src/python/gudhi/wasserstein.py b/src/python/gudhi/wasserstein.py index aab0cb3c..e28c63e6 100644 --- a/src/python/gudhi/wasserstein.py +++ b/src/python/gudhi/wasserstein.py @@ -130,7 +130,6 @@ def wasserstein_distance(X, Y, matching=False, order=2., internal_p=2.): if matching: P = ot.emd(a=a,b=b,M=M, numItermax=2000000) ot_cost = np.sum(np.multiply(P,M)) - P[P < 0.5] = 0 # trick to avoid numerical issue, could it be improved? match = np.argwhere(P) # Now we turn to -1 points encoding the diagonal match = _clean_match(match, n, m) |