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diff --git a/docs/source/auto_examples/plot_screenkhorn_1D.rst b/docs/source/auto_examples/plot_screenkhorn_1D.rst deleted file mode 100644 index 039479e..0000000 --- a/docs/source/auto_examples/plot_screenkhorn_1D.rst +++ /dev/null @@ -1,178 +0,0 @@ -.. 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>`_ |