.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "sphinx_gallery_output/plot_10_community_layout.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_sphinx_gallery_output_plot_10_community_layout.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_sphinx_gallery_output_plot_10_community_layout.py:


Community Node Layout / Bundled Edges
=====================================

.. GENERATED FROM PYTHON SOURCE LINES 6-40

.. code-block:: default


    import matplotlib.pyplot as plt
    import networkx as nx

    from netgraph import Graph

    # create a modular graph
    partition_sizes = [10, 20, 30, 40]
    g = nx.random_partition_graph(partition_sizes, 0.5, 0.1)

    # create a dictionary that maps nodes to the community they belong to
    node_to_community = dict()
    node = 0
    for community_id, size in enumerate(partition_sizes):
        for _ in range(size):
            node_to_community[node] = community_id
            node += 1

    community_to_color = {
        0 : 'tab:blue',
        1 : 'tab:orange',
        2 : 'tab:green',
        3 : 'tab:red',
    }
    node_color = {node: community_to_color[community_id] for node, community_id in node_to_community.items()}

    Graph(g,
          node_color=node_color, node_edge_width=0, edge_alpha=0.1,
          node_layout='community', node_layout_kwargs=dict(node_to_community=node_to_community),
          edge_layout='bundled', edge_layout_kwargs=dict(k=2000),
    )

    plt.show()




.. image-sg:: /sphinx_gallery_output/images/sphx_glr_plot_10_community_layout_001.png
   :alt: plot 10 community layout
   :srcset: /sphinx_gallery_output/images/sphx_glr_plot_10_community_layout_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    /home/paul/src/netgraph/netgraph/_edge_layout.py:692: RuntimeWarning: invalid value encountered in true_divide
      displacement = compatibility * delta / distance_squared[..., None]




.. GENERATED FROM PYTHON SOURCE LINES 41-43

Alternatively, the best partition into communities can be inferred, for example
using the Louvain algorithm (:code:`pip install python-louvain`):

.. GENERATED FROM PYTHON SOURCE LINES 43-46

.. code-block:: default


    from community import community_louvain
    node_to_community = community_louvain.best_partition(g)








.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 3 minutes  59.103 seconds)


.. _sphx_glr_download_sphinx_gallery_output_plot_10_community_layout.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_10_community_layout.py <plot_10_community_layout.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_10_community_layout.ipynb <plot_10_community_layout.ipynb>`


.. only:: html

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

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