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diff --git a/docs/source/auto_examples/plot_convolutional_barycenter.rst b/docs/source/auto_examples/plot_convolutional_barycenter.rst deleted file mode 100644 index a28db2f..0000000 --- a/docs/source/auto_examples/plot_convolutional_barycenter.rst +++ /dev/null @@ -1,151 +0,0 @@ - - -.. _sphx_glr_auto_examples_plot_convolutional_barycenter.py: - - -============================================ -Convolutional Wasserstein Barycenter example -============================================ - -This example is designed to illustrate how the Convolutional Wasserstein Barycenter -function of POT works. - - - -.. code-block:: python - - - # Author: Nicolas Courty <ncourty@irisa.fr> - # - # License: MIT License - - - import numpy as np - import pylab as pl - import ot - - - - - - - -Data preparation ----------------- - -The four distributions are constructed from 4 simple images - - - -.. code-block:: python - - - - f1 = 1 - pl.imread('../data/redcross.png')[:, :, 2] - f2 = 1 - pl.imread('../data/duck.png')[:, :, 2] - f3 = 1 - pl.imread('../data/heart.png')[:, :, 2] - f4 = 1 - pl.imread('../data/tooth.png')[:, :, 2] - - A = [] - f1 = f1 / np.sum(f1) - f2 = f2 / np.sum(f2) - f3 = f3 / np.sum(f3) - f4 = f4 / np.sum(f4) - A.append(f1) - A.append(f2) - A.append(f3) - A.append(f4) - A = np.array(A) - - nb_images = 5 - - # those are the four corners coordinates that will be interpolated by bilinear - # interpolation - v1 = np.array((1, 0, 0, 0)) - v2 = np.array((0, 1, 0, 0)) - v3 = np.array((0, 0, 1, 0)) - v4 = np.array((0, 0, 0, 1)) - - - - - - - - -Barycenter computation and visualization ----------------------------------------- - - - - -.. code-block:: python - - - pl.figure(figsize=(10, 10)) - pl.title('Convolutional Wasserstein Barycenters in POT') - cm = 'Blues' - # regularization parameter - reg = 0.004 - for i in range(nb_images): - for j in range(nb_images): - pl.subplot(nb_images, nb_images, i * nb_images + j + 1) - tx = float(i) / (nb_images - 1) - ty = float(j) / (nb_images - 1) - - # weights are constructed by bilinear interpolation - tmp1 = (1 - tx) * v1 + tx * v2 - tmp2 = (1 - tx) * v3 + tx * v4 - weights = (1 - ty) * tmp1 + ty * tmp2 - - if i == 0 and j == 0: - pl.imshow(f1, cmap=cm) - pl.axis('off') - elif i == 0 and j == (nb_images - 1): - pl.imshow(f3, cmap=cm) - pl.axis('off') - elif i == (nb_images - 1) and j == 0: - pl.imshow(f2, cmap=cm) - pl.axis('off') - elif i == (nb_images - 1) and j == (nb_images - 1): - pl.imshow(f4, cmap=cm) - pl.axis('off') - else: - # call to barycenter computation - pl.imshow(ot.bregman.convolutional_barycenter2d(A, reg, weights), cmap=cm) - pl.axis('off') - pl.show() - - - -.. image:: /auto_examples/images/sphx_glr_plot_convolutional_barycenter_001.png - :align: center - - - - -**Total running time of the script:** ( 1 minutes 11.608 seconds) - - - -.. only :: html - - .. container:: sphx-glr-footer - - - .. container:: sphx-glr-download - - :download:`Download Python source code: plot_convolutional_barycenter.py <plot_convolutional_barycenter.py>` - - - - .. container:: sphx-glr-download - - :download:`Download Jupyter notebook: plot_convolutional_barycenter.ipynb <plot_convolutional_barycenter.ipynb>` - - -.. only:: html - - .. rst-class:: sphx-glr-signature - - `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_ |