From 5e7c6ab04be3dc2035ca2a7f9deab3bb3bfb8faa Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Tue, 25 Jun 2019 14:43:39 +0200
Subject: doc add examples unbalanced

---
 docs/source/auto_examples/plot_UOT_1D.rst | 173 ++++++++++++++++++++++++++++++
 1 file changed, 173 insertions(+)
 create mode 100644 docs/source/auto_examples/plot_UOT_1D.rst

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diff --git a/docs/source/auto_examples/plot_UOT_1D.rst b/docs/source/auto_examples/plot_UOT_1D.rst
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+
+
+.. _sphx_glr_auto_examples_plot_UOT_1D.py:
+
+
+===============================
+1D Unbalanced optimal transport
+===============================
+
+This example illustrates the computation of Unbalanced Optimal transport
+using a Kullback-Leibler relaxation.
+
+
+
+.. code-block:: python
+
+
+    # Author: Hicham Janati <hicham.janati@inria.fr>
+    #
+    # License: MIT License
+
+    import numpy as np
+    import matplotlib.pylab as pl
+    import ot
+    import ot.plot
+    from ot.datasets import make_1D_gauss as gauss
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+
+.. code-block:: python
+
+
+
+    #%% parameters
+
+    n = 100  # nb bins
+
+    # bin positions
+    x = np.arange(n, dtype=np.float64)
+
+    # Gaussian distributions
+    a = gauss(n, m=20, s=5)  # m= mean, s= std
+    b = gauss(n, m=60, s=10)
+
+    # make distributions unbalanced
+    b *= 5.
+
+    # loss matrix
+    M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
+    M /= M.max()
+
+
+
+
+
+
+
+
+Plot distributions and loss matrix
+----------------------------------
+
+
+
+.. code-block:: python
+
+
+    #%% plot the distributions
+
+    pl.figure(1, figsize=(6.4, 3))
+    pl.plot(x, a, 'b', label='Source distribution')
+    pl.plot(x, b, 'r', label='Target distribution')
+    pl.legend()
+
+    # plot distributions and loss matrix
+
+    pl.figure(2, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
+
+
+
+
+
+.. rst-class:: sphx-glr-horizontal
+
+
+    *
+
+      .. image:: /auto_examples/images/sphx_glr_plot_UOT_1D_001.png
+            :scale: 47
+
+    *
+
+      .. image:: /auto_examples/images/sphx_glr_plot_UOT_1D_002.png
+            :scale: 47
+
+
+
+
+Solve Unbalanced Sinkhorn
+--------------
+
+
+
+.. code-block:: python
+
+
+
+    # Sinkhorn
+
+    epsilon = 0.1  # entropy parameter
+    alpha = 1.  # Unbalanced KL relaxation parameter
+    Gs = ot.unbalanced.sinkhorn_unbalanced(a, b, M, epsilon, alpha, verbose=True)
+
+    pl.figure(4, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, Gs, 'UOT matrix Sinkhorn')
+
+    pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_UOT_1D_006.png
+    :align: center
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+    It.  |Err         
+    -------------------
+        0|1.838786e+00|
+       10|1.242379e-01|
+       20|2.581314e-03|
+       30|5.674552e-05|
+       40|1.252959e-06|
+       50|2.768136e-08|
+       60|6.116090e-10|
+
+
+**Total running time of the script:** ( 0 minutes  0.259 seconds)
+
+
+
+.. only :: html
+
+ .. container:: sphx-glr-footer
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Python source code: plot_UOT_1D.py <plot_UOT_1D.py>`
+
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Jupyter notebook: plot_UOT_1D.ipynb <plot_UOT_1D.ipynb>`
+
+
+.. only:: html
+
+ .. rst-class:: sphx-glr-signature
+
+    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_
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