From b5e45bbc83fd8cd8c1634a78f2f983d1cf28af73 Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Wed, 30 May 2018 09:58:51 +0200
Subject: update examples and notebooks

---
 docs/source/auto_examples/plot_otda_classes.rst | 61 +++++++++++++------------
 1 file changed, 33 insertions(+), 28 deletions(-)

(limited to 'docs/source/auto_examples/plot_otda_classes.rst')

diff --git a/docs/source/auto_examples/plot_otda_classes.rst b/docs/source/auto_examples/plot_otda_classes.rst
index a5ab285..19756ff 100644
--- a/docs/source/auto_examples/plot_otda_classes.rst
+++ b/docs/source/auto_examples/plot_otda_classes.rst
@@ -42,8 +42,8 @@ Generate data
     n_source_samples = 150
     n_target_samples = 150
 
-    Xs, ys = ot.datasets.get_data_classif('3gauss', n_source_samples)
-    Xt, yt = ot.datasets.get_data_classif('3gauss2', n_target_samples)
+    Xs, ys = ot.datasets.make_data_classif('3gauss', n_source_samples)
+    Xt, yt = ot.datasets.make_data_classif('3gauss2', n_target_samples)
 
 
 
@@ -94,29 +94,29 @@ Instantiate the different transport algorithms and fit them
 
     It.  |Loss        |Delta loss
     --------------------------------
-        0|1.003747e+01|0.000000e+00
-        1|1.953263e+00|-4.138821e+00
-        2|1.744456e+00|-1.196969e-01
-        3|1.689268e+00|-3.267022e-02
-        4|1.666355e+00|-1.374998e-02
-        5|1.656125e+00|-6.177356e-03
-        6|1.651753e+00|-2.646960e-03
-        7|1.647261e+00|-2.726957e-03
-        8|1.642274e+00|-3.036672e-03
-        9|1.639926e+00|-1.431818e-03
-       10|1.638750e+00|-7.173837e-04
-       11|1.637558e+00|-7.281753e-04
-       12|1.636248e+00|-8.002067e-04
-       13|1.634555e+00|-1.036074e-03
-       14|1.633547e+00|-6.166646e-04
-       15|1.633531e+00|-1.022614e-05
-       16|1.632957e+00|-3.510986e-04
-       17|1.632853e+00|-6.380944e-05
-       18|1.632704e+00|-9.122988e-05
-       19|1.632237e+00|-2.861276e-04
+        0|9.566309e+00|0.000000e+00
+        1|2.169680e+00|-3.409088e+00
+        2|1.914989e+00|-1.329986e-01
+        3|1.860251e+00|-2.942498e-02
+        4|1.838073e+00|-1.206621e-02
+        5|1.827064e+00|-6.025122e-03
+        6|1.820899e+00|-3.386082e-03
+        7|1.817290e+00|-1.985705e-03
+        8|1.814644e+00|-1.458223e-03
+        9|1.812661e+00|-1.093816e-03
+       10|1.810239e+00|-1.338121e-03
+       11|1.809100e+00|-6.296940e-04
+       12|1.807939e+00|-6.420646e-04
+       13|1.806965e+00|-5.389118e-04
+       14|1.806822e+00|-7.889599e-05
+       15|1.806193e+00|-3.482356e-04
+       16|1.805735e+00|-2.536930e-04
+       17|1.805321e+00|-2.292667e-04
+       18|1.804389e+00|-5.170222e-04
+       19|1.803908e+00|-2.661907e-04
     It.  |Loss        |Delta loss
     --------------------------------
-       20|1.632174e+00|-3.896483e-05
+       20|1.803696e+00|-1.178279e-04
 
 
 Fig 1 : plots source and target samples
@@ -161,7 +161,7 @@ Fig 2 : plot optimal couplings and transported samples
 .. code-block:: python
 
 
-    param_img = {'interpolation': 'nearest', 'cmap': 'spectral'}
+    param_img = {'interpolation': 'nearest'}
 
     pl.figure(2, figsize=(15, 8))
     pl.subplot(2, 4, 1)
@@ -236,11 +236,13 @@ Fig 2 : plot optimal couplings and transported samples
 
 
 
-**Total running time of the script:** ( 0 minutes  2.308 seconds)
+**Total running time of the script:** ( 0 minutes  1.423 seconds)
 
 
 
-.. container:: sphx-glr-footer
+.. only :: html
+
+ .. container:: sphx-glr-footer
 
 
   .. container:: sphx-glr-download
@@ -253,6 +255,9 @@ Fig 2 : plot optimal couplings and transported samples
 
      :download:`Download Jupyter notebook: plot_otda_classes.ipynb <plot_otda_classes.ipynb>`
 
-.. rst-class:: sphx-glr-signature
 
-    `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
+.. only:: html
+
+ .. rst-class:: sphx-glr-signature
+
+    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_
-- 
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