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+.. only:: html
+
+    .. note::
+        :class: sphx-glr-download-link-note
+
+        Click :ref:`here <sphx_glr_download_auto_examples_plot_screenkhorn_1D.py>`     to download the full example code
+    .. rst-class:: sphx-glr-example-title
+
+    .. _sphx_glr_auto_examples_plot_screenkhorn_1D.py:
+
+
+===============================
+1D Screened optimal transport
+===============================
+
+This example illustrates the computation of Screenkhorn:
+Screening Sinkhorn Algorithm for Optimal transport.
+
+
+.. code-block:: default
+
+
+    # Author: Mokhtar Z. Alaya <mokhtarzahdi.alaya@gmail.com>
+    #
+    # License: MIT License
+
+    import numpy as np
+    import matplotlib.pylab as pl
+    import ot.plot
+    from ot.datasets import make_1D_gauss as gauss
+    from ot.bregman import screenkhorn
+
+
+
+
+
+
+
+
+Generate data
+-------------
+
+
+.. code-block:: default
+
+
+    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:: default
+
+
+    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_screenkhorn_1D_001.png
+            :class: sphx-glr-multi-img
+
+    *
+
+      .. image:: /auto_examples/images/sphx_glr_plot_screenkhorn_1D_002.png
+            :class: sphx-glr-multi-img
+
+
+
+
+
+Solve Screenkhorn
+-----------------------
+
+
+.. code-block:: default
+
+
+    # Screenkhorn
+    lambd = 2e-03  # entropy parameter
+    ns_budget = 30  # budget number of points to be keeped in the source distribution
+    nt_budget = 30  # budget number of points to be keeped in the target distribution
+
+    G_screen = screenkhorn(a, b, M, lambd, ns_budget, nt_budget, uniform=False, restricted=True, verbose=True)
+    pl.figure(4, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, G_screen, 'OT matrix Screenkhorn')
+    pl.show()
+
+
+
+.. image:: /auto_examples/images/sphx_glr_plot_screenkhorn_1D_003.png
+    :class: sphx-glr-single-img
+
+
+.. rst-class:: sphx-glr-script-out
+
+ Out:
+
+ .. code-block:: none
+
+    /home/rflamary/PYTHON/POT/ot/bregman.py:2056: UserWarning: Bottleneck module is not installed. Install it from https://pypi.org/project/Bottleneck/ for better performance.
+      "Bottleneck module is not installed. Install it from https://pypi.org/project/Bottleneck/ for better performance.")
+    epsilon = 0.020986042861303855
+
+    kappa = 3.7476531411890917
+
+    Cardinality of selected points: |Isel| = 30      |Jsel| = 30 
+
+    /home/rflamary/PYTHON/POT/examples/plot_screenkhorn_1D.py:68: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
+      pl.show()
+
+
+
+
+
+.. rst-class:: sphx-glr-timing
+
+   **Total running time of the script:** ( 0 minutes  0.228 seconds)
+
+
+.. _sphx_glr_download_auto_examples_plot_screenkhorn_1D.py:
+
+
+.. only :: html
+
+ .. container:: sphx-glr-footer
+    :class: sphx-glr-footer-example
+
+
+
+  .. container:: sphx-glr-download sphx-glr-download-python
+
+     :download:`Download Python source code: plot_screenkhorn_1D.py <plot_screenkhorn_1D.py>`
+
+
+
+  .. container:: sphx-glr-download sphx-glr-download-jupyter
+
+     :download:`Download Jupyter notebook: plot_screenkhorn_1D.ipynb <plot_screenkhorn_1D.ipynb>`
+
+
+.. only:: html
+
+ .. rst-class:: sphx-glr-signature
+
+    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_