.. note::
    :class: sphx-glr-download-link-note

    Click :ref:`here <sphx_glr_download_gallery_plot_dominators.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_gallery_plot_dominators.py:


Grave Documentation
-------------------





.. image:: /gallery/images/sphx_glr_plot_dominators_001.png
    :class: sphx-glr-single-img





.. code-block:: python

    import networkx as nx
    from networkx.algorithms.approximation.dominating_set import min_weighted_dominating_set
    import matplotlib.pyplot as plt

    from grave import plot_network, use_attributes

    toy_network = nx.barbell_graph(10, 14)
    dom_set = min_weighted_dominating_set(toy_network)

    for node, node_attrs in toy_network.nodes(data=True):
        if node in dom_set:
            node_attrs['color'] = 'red'
        else:
            node_attrs['color'] = 'black'
        node_attrs['size'] = 50

    fig, ax = plt.subplots()
    plot_network(toy_network,
                 node_style=use_attributes())
    plt.show()

**Total running time of the script:** ( 0 minutes  0.043 seconds)


.. _sphx_glr_download_gallery_plot_dominators.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_dominators.py <plot_dominators.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_dominators.ipynb <plot_dominators.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_