1 files changed, 199 insertions, 0 deletions
diff --git a/docs/source/auto_examples/plot_OT_1D.rst b/docs/source/auto_examples/plot_OT_1D.rst
new file mode 100644
index 0000000..b97d67c
--- /dev/null
+++ b/docs/source/auto_examples/plot_OT_1D.rst
@@ -0,0 +1,199 @@
+
+
+.. _sphx_glr_auto_examples_plot_OT_1D.py:
+
+
+====================
+1D optimal transport
+====================
+
+This example illustrates the computation of EMD and Sinkhorn transport plans
+and their visualization.
+
+
+
+
+.. code-block:: python
+
+
+    # Author: Remi Flamary <remi.flamary@unice.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)
+
+    # 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_OT_1D_001.png
+            :scale: 47
+
+    *
+
+      .. image:: /auto_examples/images/sphx_glr_plot_OT_1D_002.png
+            :scale: 47
+
+
+
+
+Solve EMD
+---------
+
+
+
+.. code-block:: python
+
+
+
+    #%% EMD
+
+    G0 = ot.emd(a, b, M)
+
+    pl.figure(3, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
+
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_OT_1D_005.png
+    :align: center
+
+
+
+
+Solve Sinkhorn
+--------------
+
+
+
+.. code-block:: python
+
+
+
+    #%% Sinkhorn
+
+    lambd = 1e-3
+    Gs = ot.sinkhorn(a, b, M, lambd, verbose=True)
+
+    pl.figure(4, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, Gs, 'OT matrix Sinkhorn')
+
+    pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_OT_1D_007.png
+    :align: center
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out::
+
+    It.  |Err         
+    -------------------
+        0|8.187970e-02|
+       10|3.460174e-02|
+       20|6.633335e-03|
+       30|9.797798e-04|
+       40|1.389606e-04|
+       50|1.959016e-05|
+       60|2.759079e-06|
+       70|3.885166e-07|
+       80|5.470605e-08|
+       90|7.702918e-09|
+      100|1.084609e-09|
+      110|1.527180e-10|
+
+
+**Total running time of the script:** ( 0 minutes  0.561 seconds)
+
+
+
+.. only :: html
+
+ .. container:: sphx-glr-footer
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Python source code: plot_OT_1D.py <plot_OT_1D.py>`
+
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Jupyter notebook: plot_OT_1D.ipynb <plot_OT_1D.ipynb>`
+
+
+.. only:: html
+
+ .. rst-class:: sphx-glr-signature
+
+    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_