From 36f4f7ed2116841d7fe9514ee250bbf16e77b72d Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Fri, 11 May 2018 17:07:56 +0200
Subject: better documentation

---
 ot/lp/__init__.py | 3 +++
 ot/lp/cvx.py      | 4 ++--
 2 files changed, 5 insertions(+), 2 deletions(-)

(limited to 'ot')

diff --git a/ot/lp/__init__.py b/ot/lp/__init__.py
index 6371feb..5dda82a 100644
--- a/ot/lp/__init__.py
+++ b/ot/lp/__init__.py
@@ -11,9 +11,12 @@ import multiprocessing
 
 import numpy as np
 
+from .import cvx
+
 # import compiled emd
 from .emd_wrap import emd_c, check_result
 from ..utils import parmap
+from .cvx import barycenter
 
 
 def emd(a, b, M, numItermax=100000, log=False):
diff --git a/ot/lp/cvx.py b/ot/lp/cvx.py
index 193c0f5..c62da6a 100644
--- a/ot/lp/cvx.py
+++ b/ot/lp/cvx.py
@@ -38,8 +38,8 @@ def barycenter(A, M, weights=None, verbose=False, log=False, solver='interior-po
     - :math:`W_1(\cdot,\cdot)` is the Wasserstein distance (see ot.emd.sinkhorn)
     - :math:`\mathbf{a}_i` are training distributions in the columns of matrix :math:`\mathbf{A}`
 
-    The linear program is solved using the default cvxopt solver if installed.
-    If cvxopt is not installed it uses the lp solver from scipy.optimize.
+    The linear program is solved using the interior point solver from scipy.optimize.
+    If cvxopt solver if installed it can use cvxopt.
 
     Parameters
     ----------
-- 
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