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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_network_science_plot_cluster_layout.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_network_science_plot_cluster_layout.py:


Cluster of Southern Women
=========================

This example from networkx shows how to use coloring and custom layout as a dictionary.

.. GENERATED FROM PYTHON SOURCE LINES 7-71



.. image-sg:: /gallery/network_science/images/sphx_glr_plot_cluster_layout_001.png
   :alt: plot cluster layout
   :srcset: /gallery/network_science/images/sphx_glr_plot_cluster_layout_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    [<iplotx.network.NetworkArtist object at 0x7dd1a57f2ad0>]





|

.. code-block:: Python


    import networkx as nx
    import numpy as np
    import matplotlib.pyplot as plt
    import iplotx as ipx

    G = nx.davis_southern_women_graph()
    communities = nx.community.greedy_modularity_communities(G)

    # Layout does not appear deterministic, so we use a fixed layout from one run of spring_layout
    pos = {
        "Evelyn Jefferson": np.array([-25.68131066, -10.80854424]),
        "Laura Mandeville": np.array([-25.55280383, -10.99674201]),
        "Theresa Anderson": np.array([-25.38187247, -10.86875164]),
        "Brenda Rogers": np.array([-25.67901346, -11.17009239]),
        "Charlotte McDowd": np.array([-25.85576192, -11.09635554]),
        "Frances Anderson": np.array([-24.97100665, -10.80341997]),
        "Eleanor Nye": np.array([-25.22178561, -11.61473984]),
        "Pearl Oglethorpe": np.array([-24.43628739, -11.25006292]),
        "Ruth DeSand": np.array([-25.15041064, -11.82194973]),
        "E1": np.array([-26.10000875, -11.13170858]),
        "E2": np.array([-25.52047415, -10.41822091]),
        "E3": np.array([-25.48205106, -10.7056092]),
        "E4": np.array([-25.96271954, -10.75283759]),
        "E5": np.array([-25.35150057, -11.23805354]),
        "E6": np.array([-25.1129681, -11.11829674]),
        "E7": np.array([-25.5206234, -11.4515497]),
        "E13": np.array([-29.38952624, -9.82903937]),
        "Nora Fayette": np.array([-30.14866675, -9.89241409]),
        "Olivia Carleton": np.array([-30.44992786, -8.93390847]),
        "Katherina Rogers": np.array([-29.87511453, -10.05207037]),
        "Helen Lloyd": np.array([-30.70287724, -10.18706022]),
        "E12": np.array([-29.97554058, -10.44474811]),
        "E14": np.array([-30.32816285, -10.28626239]),
        "Sylvia Avondale": np.array([-29.68181361, -10.1960916]),
        "Myra Liddel": np.array([-29.50794269, -10.44247286]),
        "E9": np.array([-29.86346377, -9.54678644]),
        "Flora Price": np.array([-30.07123751, -8.8956997]),
        "E10": np.array([-30.15355559, -10.54517655]),
        "E11": np.array([-30.59292037, -9.39236595]),
        "E8": np.array([-19.26284314, -9.57050676]),
        "Dorothy Murchison": np.array([-19.48148306, -10.57263599]),
        "Verne Sanderson": np.array([-19.0455969, -8.57476521]),
    }

    # Nodes colored by cluster
    node_color = {}
    for nodes, clr in zip(communities, ("tab:blue", "tab:orange", "tab:green")):
        for node in nodes:
            node_color[node] = clr

    fig, ax = plt.subplots(figsize=(6, 6))
    ipx.plot(
        G,
        layout=pos,
        style={
            "vertex": {
                "facecolor": node_color,
                "linewidth": 0,
                "size": 25,
            }
        },
        ax=ax,
    )


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

   **Total running time of the script:** (0 minutes 0.111 seconds)


.. _sphx_glr_download_gallery_network_science_plot_cluster_layout.py:

.. only:: html

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-python

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_cluster_layout.zip <plot_cluster_layout.zip>`


.. only:: html

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

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