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author | tlacombe <lacombe1993@gmail.com> | 2020-03-10 18:55:19 +0100 |
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committer | tlacombe <lacombe1993@gmail.com> | 2020-03-10 18:56:43 +0100 |
commit | c9d6e27495c8927d736d593afb0450360b46ccc9 (patch) | |
tree | c0d671a923d29eb128e111029135a5349a8e474a /src/python/gudhi | |
parent | 753290475ab6e95c2de1baad97ee6f755a0ce19a (diff) |
fix indentation in wasserstein
Diffstat (limited to 'src/python/gudhi')
-rw-r--r-- | src/python/gudhi/wasserstein.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/src/python/gudhi/wasserstein.py b/src/python/gudhi/wasserstein.py index 83a682df..3dd993f9 100644 --- a/src/python/gudhi/wasserstein.py +++ b/src/python/gudhi/wasserstein.py @@ -70,13 +70,13 @@ def wasserstein_distance(X, Y, matching=False, order=2., internal_p=2.): (i.e. with infinite coordinate). :param Y: (m x 2) numpy.array encoding the second diagram. :param matching: if True, computes and returns the optimal matching between X and Y, encoded as - a (n x 2) np.array [...[i,j]...], meaning the i-th point in X is matched to - the j-th point in Y, with the convention (-1) represents the diagonal. + a (n x 2) np.array [...[i,j]...], meaning the i-th point in X is matched to + the j-th point in Y, with the convention (-1) represents the diagonal. :param order: exponent for Wasserstein; Default value is 2. :param internal_p: Ground metric on the (upper-half) plane (i.e. norm L^p in R^2); - Default value is 2 (Euclidean norm). + Default value is 2 (Euclidean norm). :returns: the Wasserstein distance of order q (1 <= q < infinity) between persistence diagrams with - respect to the internal_p-norm as ground metric. + respect to the internal_p-norm as ground metric. If matching is set to True, also returns the optimal matching between X and Y. ''' n = len(X) |