diff options
Diffstat (limited to 'docs/source/auto_examples/plot_free_support_barycenter.rst')
-rw-r--r-- | docs/source/auto_examples/plot_free_support_barycenter.rst | 140 |
1 files changed, 0 insertions, 140 deletions
diff --git a/docs/source/auto_examples/plot_free_support_barycenter.rst b/docs/source/auto_examples/plot_free_support_barycenter.rst deleted file mode 100644 index d1b3b80..0000000 --- a/docs/source/auto_examples/plot_free_support_barycenter.rst +++ /dev/null @@ -1,140 +0,0 @@ - - -.. _sphx_glr_auto_examples_plot_free_support_barycenter.py: - - -==================================================== -2D free support Wasserstein barycenters of distributions -==================================================== - -Illustration of 2D Wasserstein barycenters if discributions that are weighted -sum of diracs. - - - - -.. code-block:: python - - - # Author: Vivien Seguy <vivien.seguy@iip.ist.i.kyoto-u.ac.jp> - # - # License: MIT License - - import numpy as np - import matplotlib.pylab as pl - import ot - - - - - - - - -Generate data - ------------- -%% parameters and data generation - - - -.. code-block:: python - - N = 3 - d = 2 - measures_locations = [] - measures_weights = [] - - for i in range(N): - - n_i = np.random.randint(low=1, high=20) # nb samples - - mu_i = np.random.normal(0., 4., (d,)) # Gaussian mean - - A_i = np.random.rand(d, d) - cov_i = np.dot(A_i, A_i.transpose()) # Gaussian covariance matrix - - x_i = ot.datasets.make_2D_samples_gauss(n_i, mu_i, cov_i) # Dirac locations - b_i = np.random.uniform(0., 1., (n_i,)) - b_i = b_i / np.sum(b_i) # Dirac weights - - measures_locations.append(x_i) - measures_weights.append(b_i) - - - - - - - - -Compute free support barycenter -------------- - - - -.. code-block:: python - - - k = 10 # number of Diracs of the barycenter - X_init = np.random.normal(0., 1., (k, d)) # initial Dirac locations - b = np.ones((k,)) / k # weights of the barycenter (it will not be optimized, only the locations are optimized) - - X = ot.lp.free_support_barycenter(measures_locations, measures_weights, X_init, b) - - - - - - - - -Plot data ---------- - - - -.. code-block:: python - - - pl.figure(1) - for (x_i, b_i) in zip(measures_locations, measures_weights): - color = np.random.randint(low=1, high=10 * N) - pl.scatter(x_i[:, 0], x_i[:, 1], s=b * 1000, label='input measure') - pl.scatter(X[:, 0], X[:, 1], s=b * 1000, c='black', marker='^', label='2-Wasserstein barycenter') - pl.title('Data measures and their barycenter') - pl.legend(loc=0) - pl.show() - - - -.. image:: /auto_examples/images/sphx_glr_plot_free_support_barycenter_001.png - :align: center - - - - -**Total running time of the script:** ( 0 minutes 0.129 seconds) - - - -.. only :: html - - .. container:: sphx-glr-footer - - - .. container:: sphx-glr-download - - :download:`Download Python source code: plot_free_support_barycenter.py <plot_free_support_barycenter.py>` - - - - .. container:: sphx-glr-download - - :download:`Download Jupyter notebook: plot_free_support_barycenter.ipynb <plot_free_support_barycenter.ipynb>` - - -.. only:: html - - .. rst-class:: sphx-glr-signature - - `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_ |