From dab572396be97fcf5439e4e20f887165b1ade62c Mon Sep 17 00:00:00 2001 From: Nicolas Courty Date: Fri, 7 Sep 2018 14:49:20 +0200 Subject: whitetrail pep8 --- ot/bregman.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) (limited to 'ot') diff --git a/ot/bregman.py b/ot/bregman.py index 748ac30..35e51f8 100644 --- a/ot/bregman.py +++ b/ot/bregman.py @@ -920,8 +920,8 @@ def barycenter(A, M, reg, weights=None, numItermax=1000, def convolutional_barycenter2d(A, reg, weights=None, numItermax=10000, stopThr=1e-9, stabThr=1e-30, verbose=False, log=False): - """Compute the entropic regularized wasserstein barycenter of distributions A - where A is a collection of 2D images. + """Compute the entropic regularized wasserstein barycenter of distributions A + where A is a collection of 2D images. The function solves the following optimization problem: @@ -949,7 +949,7 @@ def convolutional_barycenter2d(A, reg, weights=None, numItermax=10000, stopThr=1 stopThr : float, optional Stop threshol on error (>0) stabThr : float, optional - Stabilization threshold to avoid numerical precision issue + Stabilization threshold to avoid numerical precision issue verbose : bool, optional Print information along iterations log : bool, optional @@ -967,9 +967,9 @@ def convolutional_barycenter2d(A, reg, weights=None, numItermax=10000, stopThr=1 References ---------- - .. [21] Solomon, J., De Goes, F., Peyré, G., Cuturi, M., Butscher, A., Nguyen, A. & Guibas, L. (2015). - Convolutional wasserstein distances: Efficient optimal transportation on geometric domains - ACM Transactions on Graphics (TOG), 34(4), 66 + .. [21] Solomon, J., De Goes, F., Peyré, G., Cuturi, M., Butscher, A., Nguyen, A. & Guibas, L. (2015). + Convolutional wasserstein distances: Efficient optimal transportation on geometric domains + ACM Transactions on Graphics (TOG), 34(4), 66 """ -- cgit v1.2.3