add free support barycenter algorithm

1 files changed, 18 insertions, 17 deletions

diff --git a/examples/plot_free_support_barycenter.py b/examples/plot_free_support_barycenter.py
index 61671cf..42e22fc 100644
--- a/examples/plot_free_support_barycenter.py
+++ b/examples/plot_free_support_barycenter.py
@@ -21,7 +21,7 @@ import ot.plot
 # Generate data
 # -------------
 #%% parameters and data generation
-N = 6
+N = 3
 d = 2
 measures_locations = []
 measures_weights = []
@@ -33,24 +33,25 @@ for i in range(N):
     mu = np.random.normal(0., 4., (d,))
 
     A = np.random.rand(d, d)
-    cov = np.dot(A,A.transpose())
+    cov = np.dot(A, A.transpose())
 
-    xs = ot.datasets.make_2D_samples_gauss(n, mu, cov)
-    b = np.random.uniform(0., 1., (n,))
-    b = b/np.sum(b)
+    x_i = ot.datasets.make_2D_samples_gauss(n, mu, cov)
+    b_i = np.random.uniform(0., 1., (n,))
+    b_i = b_i / np.sum(b_i)
 
-    measures_locations.append(xs)
-    measures_weights.append(b)
-
-k = 10
-X_init = np.random.normal(0., 1., (k,d))
-b_init = np.ones((k,)) / k
+    measures_locations.append(x_i)
+    measures_weights.append(b_i)
 
 
 ##############################################################################
 # Compute free support barycenter
 # -------------
-X = ot.lp.cvx.free_support_barycenter(measures_locations, measures_weights, X_init, b_init)
+
+k = 10
+X_init = np.random.normal(0., 1., (k, d))
+b = np.ones((k,)) / k
+
+X = ot.lp.cvx.free_support_barycenter(measures_locations, measures_weights, X_init, b)
 
 
 ##############################################################################
@@ -60,10 +61,10 @@ X = ot.lp.cvx.free_support_barycenter(measures_locations, measures_weights, X_in
 #%% plot samples
 
 pl.figure(1)
-for (xs, b) in zip(measures_locations, measures_weights):
-    color = np.random.randint(low=1, high=10*N)
-    pl.scatter(xs[:, 0], xs[:, 1], s=b*1000, label='input measure')
-pl.scatter(X[:, 0], X[:, 1], s=b_init*1000, c='black' , marker='^', label='2-Wasserstein barycenter')
+for (x_i, b_i) in zip(measures_locations, measures_weights):
+    color = np.random.randint(low=1, high=10 * N)
+    pl.scatter(x_i[:, 0], x_i[:, 1], s=b * 1000, label='input measure')
+pl.scatter(X[:, 0], X[:, 1], s=b * 1000, c='black', marker='^', label='2-Wasserstein barycenter')
 pl.title('Data measures and their barycenter')
 pl.legend(loc=0)
-pl.show()
\ No newline at end of file
+pl.show()