From e458b7a58d9790e7c5ff40dea235402d9c4c8662 Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Fri, 2 Dec 2016 15:38:59 +0100
Subject: add doc for gallery

---
 .../auto_examples/demo_OT_2D_sampleslarge.rst      | 106 +++++++++++++++++++++
 1 file changed, 106 insertions(+)
 create mode 100644 docs/source/auto_examples/demo_OT_2D_sampleslarge.rst

(limited to 'docs/source/auto_examples/demo_OT_2D_sampleslarge.rst')

diff --git a/docs/source/auto_examples/demo_OT_2D_sampleslarge.rst b/docs/source/auto_examples/demo_OT_2D_sampleslarge.rst
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+
+
+.. _sphx_glr_auto_examples_demo_OT_2D_sampleslarge.py:
+
+
+Demo for 2D Optimal transport between empirical distributions
+
+@author: rflamary
+
+
+
+.. code-block:: python
+
+
+    import numpy as np
+    import matplotlib.pylab as pl
+    import ot
+
+    #%% parameters and data generation
+
+    n=5000 # nb samples
+
+    mu_s=np.array([0,0])
+    cov_s=np.array([[1,0],[0,1]])
+
+    mu_t=np.array([4,4])
+    cov_t=np.array([[1,-.8],[-.8,1]])
+
+    xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)
+    xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)
+
+    a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
+
+    # loss matrix
+    M=ot.dist(xs,xt)
+    M/=M.max()
+
+    #%% plot samples
+
+    #pl.figure(1)
+    #pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
+    #pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+    #pl.legend(loc=0)
+    #pl.title('Source and traget distributions')
+    #
+    #pl.figure(2)
+    #pl.imshow(M,interpolation='nearest')
+    #pl.title('Cost matrix M')
+    #
+
+    #%% EMD
+
+    G0=ot.emd(a,b,M)
+
+    #pl.figure(3)
+    #pl.imshow(G0,interpolation='nearest')
+    #pl.title('OT matrix G0')
+    #
+    #pl.figure(4)
+    #ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
+    #pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
+    #pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+    #pl.legend(loc=0)
+    #pl.title('OT matrix with samples')
+
+
+    #%% sinkhorn
+
+    # reg term
+    lambd=5e-3
+
+    Gs=ot.sinkhorn(a,b,M,lambd)
+
+    #pl.figure(5)
+    #pl.imshow(Gs,interpolation='nearest')
+    #pl.title('OT matrix sinkhorn')
+    #
+    #pl.figure(6)
+    #ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])
+    #pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
+    #pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
+    #pl.legend(loc=0)
+    #pl.title('OT matrix Sinkhorn with samples')
+    #
+
+
+**Total running time of the script:** ( 0 minutes  0.000 seconds)
+
+
+
+.. container:: sphx-glr-footer
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Python source code: demo_OT_2D_sampleslarge.py <demo_OT_2D_sampleslarge.py>`
+
+
+
+  .. container:: sphx-glr-download
+
+     :download:`Download Jupyter notebook: demo_OT_2D_sampleslarge.ipynb <demo_OT_2D_sampleslarge.ipynb>`
+
+.. rst-class:: sphx-glr-signature
+
+    `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_
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