From ee19d423adc85a960c9a46e4f81c370196805dbf Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Fri, 16 Feb 2018 15:04:04 +0100
Subject: update notebooks

---
 docs/source/auto_examples/plot_gromov.py | 32 ++++++++++++++++++++++----------
 1 file changed, 22 insertions(+), 10 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 d3f724c..9188da9 100644
--- a/docs/source/auto_examples/plot_gromov.py
+++ b/docs/source/auto_examples/plot_gromov.py
@@ -20,7 +20,7 @@ from mpl_toolkits.mplot3d import Axes3D  # noqa
 import ot
 
 
-##############################################################################
+#
 # Sample two Gaussian distributions (2D and 3D)
 # ---------------------------------------------
 #
@@ -43,7 +43,7 @@ P = sp.linalg.sqrtm(cov_t)
 xt = np.random.randn(n_samples, 3).dot(P) + mu_t
 
 
-##############################################################################
+#
 # Plotting the distributions
 # --------------------------
 
@@ -56,7 +56,7 @@ ax2.scatter(xt[:, 0], xt[:, 1], xt[:, 2], color='r')
 pl.show()
 
 
-##############################################################################
+#
 # Compute distance kernels, normalize them and then display
 # ---------------------------------------------------------
 
@@ -74,20 +74,32 @@ pl.subplot(122)
 pl.imshow(C2)
 pl.show()
 
-##############################################################################
+#
 # Compute Gromov-Wasserstein plans and distance
 # ---------------------------------------------
 
-
 p = ot.unif(n_samples)
 q = ot.unif(n_samples)
 
-gw = ot.gromov_wasserstein(C1, C2, p, q, 'square_loss', epsilon=5e-4)
-gw_dist = ot.gromov_wasserstein2(C1, C2, p, q, 'square_loss', epsilon=5e-4)
+gw0, log0 = ot.gromov.gromov_wasserstein(
+    C1, C2, p, q, 'square_loss', verbose=True, log=True)
 
-print('Gromov-Wasserstein distances between the distribution: ' + str(gw_dist))
+gw, log = ot.gromov.entropic_gromov_wasserstein(
+    C1, C2, p, q, 'square_loss', epsilon=5e-4, log=True, verbose=True)
 
-pl.figure()
+
+print('Gromov-Wasserstein distances: ' + str(log0['gw_dist']))
+print('Entropic Gromov-Wasserstein distances: ' + str(log['gw_dist']))
+
+
+pl.figure(1, (10, 5))
+
+pl.subplot(1, 2, 1)
+pl.imshow(gw0, cmap='jet')
+pl.title('Gromov Wasserstein')
+
+pl.subplot(1, 2, 2)
 pl.imshow(gw, cmap='jet')
-pl.colorbar()
+pl.title('Entropic Gromov Wasserstein')
+
 pl.show()
-- 
cgit v1.2.3