From bf78141c8849cce9b94a4e518bd6c7360e66f8dd Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Fri, 16 Feb 2018 15:13:59 +0100
Subject: update notebooks

---
 docs/source/auto_examples/plot_gromov.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

(limited to 'docs/source/auto_examples/plot_gromov.py')

diff --git a/docs/source/auto_examples/plot_gromov.py b/docs/source/auto_examples/plot_gromov.py
index 9188da9..5cd40f6 100644
--- a/docs/source/auto_examples/plot_gromov.py
+++ b/docs/source/auto_examples/plot_gromov.py
@@ -19,7 +19,7 @@ import matplotlib.pylab as pl
 from mpl_toolkits.mplot3d import Axes3D  # noqa
 import ot
 
-
+#############################################################################
 #
 # Sample two Gaussian distributions (2D and 3D)
 # ---------------------------------------------
@@ -42,7 +42,7 @@ xs = ot.datasets.get_2D_samples_gauss(n_samples, mu_s, cov_s)
 P = sp.linalg.sqrtm(cov_t)
 xt = np.random.randn(n_samples, 3).dot(P) + mu_t
 
-
+#############################################################################
 #
 # Plotting the distributions
 # --------------------------
@@ -55,7 +55,7 @@ ax2 = fig.add_subplot(122, projection='3d')
 ax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')
 pl.show()
 
-
+#############################################################################
 #
 # Compute distance kernels, normalize them and then display
 # ---------------------------------------------------------
@@ -74,6 +74,7 @@ pl.subplot(122)
 pl.imshow(C2)
 pl.show()
 
+#############################################################################
 #
 # Compute Gromov-Wasserstein plans and distance
 # ---------------------------------------------
-- 
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