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authorVincent Rouvreau <10407034+VincentRouvreau@users.noreply.github.com>2019-11-07 14:37:59 +0100
committerGitHub <noreply@github.com>2019-11-07 14:37:59 +0100
commit753e32e5ab3c4f68c0e8a61a0a4289dcfd0cd509 (patch)
tree70017dc639f12f951d2ec5986fc2e702219745c8 /src/python/doc/wasserstein_distance_user.rst
parent31903a79c915b221b1d31776af49720376f9c8bd (diff)
parentacd8a5a49083cd588aaa859dc4af104ce9090b22 (diff)
Merge pull request #128 from mglisse/extra-modules
Fix #125
Diffstat (limited to 'src/python/doc/wasserstein_distance_user.rst')
-rw-r--r--src/python/doc/wasserstein_distance_user.rst6
1 files changed, 3 insertions, 3 deletions
diff --git a/src/python/doc/wasserstein_distance_user.rst b/src/python/doc/wasserstein_distance_user.rst
index 9ec64e93..a049cfb5 100644
--- a/src/python/doc/wasserstein_distance_user.rst
+++ b/src/python/doc/wasserstein_distance_user.rst
@@ -13,7 +13,7 @@ This implementation is based on ideas from "Large Scale Computation of Means and
Function
--------
-.. autofunction:: gudhi.wasserstein_distance
+.. autofunction:: gudhi.wasserstein.wasserstein_distance
Basic example
@@ -24,13 +24,13 @@ Note that persistence diagrams must be submitted as (n x 2) numpy arrays and mus
.. testcode::
- import gudhi
+ import gudhi.wasserstein
import numpy as np
diag1 = np.array([[2.7, 3.7],[9.6, 14.],[34.2, 34.974]])
diag2 = np.array([[2.8, 4.45],[9.5, 14.1]])
- message = "Wasserstein distance value = " + '%.2f' % gudhi.wasserstein_distance(diag1, diag2, q=2., p=1.)
+ message = "Wasserstein distance value = " + '%.2f' % gudhi.wasserstein.wasserstein_distance(diag1, diag2, q=2., p=1.)
print(message)
The output is: