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authorRémi Flamary <remi.flamary@gmail.com>2019-06-25 14:43:39 +0200
committerRémi Flamary <remi.flamary@gmail.com>2019-06-25 14:43:39 +0200
commit5e7c6ab04be3dc2035ca2a7f9deab3bb3bfb8faa (patch)
treea825f4da89d6b51c16b90ba6e69f5bb154cb325b /docs/source/auto_examples/plot_UOT_1D.rst
parentc9775bde23527f8b55db53020352969405f8b6b5 (diff)
doc add examples unbalanced
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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>`_