added test barycenter + modif target

Author: ievred

ot/bregman.py

@@ -1528,7 +1528,7 @@ def jcpot_barycenter(Xs, Ys, Xt, reg, metric='sqeuclidean', numItermax=100,
     The problem consist in solving a Wasserstein barycenter problem to estimate the proportions :math:`\mathbf{h}` in the target domain.
 
     The algorithm used for solving the problem is the Iterative Bregman projections algorithm
-    with two sets of marginal constraints related to the unknown vector :math:`\mathbf{h}` and uniform tarhet distribution.
+    with two sets of marginal constraints related to the unknown vector :math:`\mathbf{h}` and uniform target distribution.
 
     Parameters
     ----------

test/test_da.py

@@ -601,3 +601,31 @@ def test_jcpot_transport_class():
 
     # check that the oos method is working
     assert_equal(transp_Xs_new.shape, Xs_new.shape)
+
+
+def test_jcpot_barycenter():
+    """test_jcpot_barycenter
+    """
+
+    ns1 = 150
+    ns2 = 150
+    nt = 200
+
+    sigma = 0.1
+    np.random.seed(1985)
+
+    ps1 = .2
+    ps2 = .9
+    pt = .4
+
+    Xs1, ys1 = make_data_classif('2gauss_prop', ns1, nz=sigma, p=ps1)
+    Xs2, ys2 = make_data_classif('2gauss_prop', ns2, nz=sigma, p=ps2)
+    Xt, yt = make_data_classif('2gauss_prop', nt, nz=sigma, p=pt)
+
+    Xs = [Xs1, Xs2]
+    ys = [ys1, ys2]
+
+    _, prop, = ot.bregman.jcpot_barycenter(Xs, ys, Xt, reg=.5, metric='sqeuclidean',
+                                           numItermax=10000, stopThr=1e-9, verbose=False, log=False)
+
+    np.testing.assert_allclose(prop, [1 - pt, pt], rtol=1e-3, atol=1e-3)