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| author | Marc Glisse <marc.glisse@inria.fr> | 2020-04-20 19:42:34 +0200 |
|---|---|---|
| committer | Marc Glisse <marc.glisse@inria.fr> | 2020-04-20 19:42:34 +0200 |
| commit | 4ad650bc3184f57e1dda91f6b0a6358830f0562f (patch) | |
| tree | 67867af8d331a0e52d72b2766a7aebd92334bd7d /src/python/gudhi/wasserstein/wasserstein.py | |
| parent | bac284bf7f65c40f03ec8e47316d4f0fd0059c91 (diff) | |
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Diffstat (limited to 'src/python/gudhi/wasserstein/wasserstein.py')
| -rw-r--r-- | src/python/gudhi/wasserstein/wasserstein.py | 1 |
1 files changed, 0 insertions, 1 deletions
diff --git a/src/python/gudhi/wasserstein/wasserstein.py b/src/python/gudhi/wasserstein/wasserstein.py index 5b61d176..42c8dc2d 100644 --- a/src/python/gudhi/wasserstein/wasserstein.py +++ b/src/python/gudhi/wasserstein/wasserstein.py @@ -167,7 +167,6 @@ def wasserstein_distance(X, Y, matching=False, order=2., internal_p=2., enable_a dists.append(_perstot_autodiff(Y_orig[diag2], order, internal_p)) dists = [dist.reshape(1) for dist in dists] return ep.concatenate(dists).norms.lp(order).raw - # Should just compute the L^order norm manually? # We can also concatenate the 3 vectors to compute just one norm. # Comptuation of the otcost using the ot.emd2 library. |