Revert "[WIP] Update bregman.py : barycenter_sinkhorn function (Pytho…

…nOT#195)" (PythonOT#196)

This reverts commit b2eae39.

ot/bregman.py

@@ -1116,7 +1116,7 @@ def barycenter_sinkhorn(A, M, reg, weights=None, numItermax=1000,
     err = 1
 
     UKv = np.dot(K, np.divide(A.T, np.sum(K, axis=0)).T)
-    u = (geometricBar(weights, UKv) / UKv.T).T
+    u = (geometricMean(UKv) / UKv.T).T
 
     while (err > stopThr and cpt < numItermax):
         cpt = cpt + 1

ot/optim.py

@@ -136,7 +136,7 @@ def solve_linesearch(cost, G, deltaG, Mi, f_val,
 
 def cg(a, b, M, reg, f, df, G0=None, numItermax=200, numItermaxEmd=100000,
        stopThr=1e-9, stopThr2=1e-9, verbose=False, log=False, **kwargs):
-    r"""
+    """
     Solve the general regularized OT problem with conditional gradient
 
         The function solves the following optimization problem:
@@ -275,7 +275,7 @@ def cost(G):
 
 def gcg(a, b, M, reg1, reg2, f, df, G0=None, numItermax=10,
         numInnerItermax=200, stopThr=1e-9, stopThr2=1e-9, verbose=False, log=False):
-    r"""
+    """
     Solve the general regularized OT problem with the generalized conditional gradient
 
         The function solves the following optimization problem:
@@ -413,7 +413,7 @@ def cost(G):
 
 
 def solve_1d_linesearch_quad(a, b, c):
-    r"""
+    """
     For any convex or non-convex 1d quadratic function f, solve on [0,1] the following problem:
     .. math::
         \argmin f(x)=a*x^{2}+b*x+c