[MRG] Actually run sphinx-gallery (#146)

* generate gallery

* remove mock

* add sklearn to requirermnt?txt for example

* remove latex from fgw example

* add networks for graph example

* remove all

* add requirement.txt rtd

* rtd debug

* update readme

* eradthedoc with redirection

* add conf rtd

1 files changed, 0 insertions, 177 deletions

diff --git a/docs/source/auto_examples/plot_UOT_1D.rst b/docs/source/auto_examples/plot_UOT_1D.rst
deleted file mode 100644
index f43b0c1..0000000
--- a/docs/source/auto_examples/plot_UOT_1D.rst
+++ /dev/null
@@ -1,177 +0,0 @@
-.. only:: html
-
-    .. note::
-        :class: sphx-glr-download-link-note
-
-        Click :ref:`here <sphx_glr_download_auto_examples_plot_UOT_1D.py>`     to download the full example code
-    .. rst-class:: sphx-glr-example-title
-
-    .. _sphx_glr_auto_examples_plot_UOT_1D.py:
-
-
-===============================
-1D Unbalanced optimal transport
-===============================
-
-This example illustrates the computation of Unbalanced Optimal transport
-using a Kullback-Leibler relaxation.
-
-
-.. code-block:: default
-
-
-    # Author: Hicham Janati <hicham.janati@inria.fr>
-    #
-    # License: MIT License
-
-    import numpy as np
-    import matplotlib.pylab as pl
-    import ot
-    import ot.plot
-    from ot.datasets import make_1D_gauss as gauss
-
-
-
-
-
-
-
-
-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)
-
-    # make distributions unbalanced
-    b *= 5.
-
-    # 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_UOT_1D_001.png
-            :class: sphx-glr-multi-img
-
-    *
-
-      .. image:: /auto_examples/images/sphx_glr_plot_UOT_1D_002.png
-            :class: sphx-glr-multi-img
-
-
-
-
-
-Solve Unbalanced Sinkhorn
---------------
-
-
-.. code-block:: default
-
-
-
-    # Sinkhorn
-
-    epsilon = 0.1  # entropy parameter
-    alpha = 1.  # Unbalanced KL relaxation parameter
-    Gs = ot.unbalanced.sinkhorn_unbalanced(a, b, M, epsilon, alpha, verbose=True)
-
-    pl.figure(4, figsize=(5, 5))
-    ot.plot.plot1D_mat(a, b, Gs, 'UOT matrix Sinkhorn')
-
-    pl.show()
-
-
-
-.. image:: /auto_examples/images/sphx_glr_plot_UOT_1D_003.png
-    :class: sphx-glr-single-img
-
-
-.. rst-class:: sphx-glr-script-out
-
- Out:
-
- .. code-block:: none
-
-    /home/rflamary/PYTHON/POT/examples/plot_UOT_1D.py:76: 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  0.274 seconds)
-
-
-.. _sphx_glr_download_auto_examples_plot_UOT_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_UOT_1D.py <plot_UOT_1D.py>`
-
-
-
-  .. container:: sphx-glr-download sphx-glr-download-jupyter
-
-     :download:`Download Jupyter notebook: plot_UOT_1D.ipynb <plot_UOT_1D.ipynb>`
-
-
-.. only:: html
-
- .. rst-class:: sphx-glr-signature
-
-    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_