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

.. only:: html

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

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

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

.. _sphx_glr_gallery_basic_plot_grouping.py:


Grouping
========

This example shows how to use the `grouping` argument to visualise vertex
covers or clustering, including singletons (i.e. groups of one vertex).

The function takes a few different formats for the groups, but the easiest
is a dictionary of sets, in which each key is the name of the group and
each value is the set of vertices in that group.

.. GENERATED FROM PYTHON SOURCE LINES 13-31

.. code-block:: Python


    import igraph as ig
    import matplotlib.pyplot as plt
    import iplotx as ipx

    g = ig.Graph.Ring(8)

    ipx.network(
        network=g,
        layout="circle",
        grouping={
            "singleton": {0},
            "doublet": {1, 2},
            "multiplet": {3, 4, 5, 6, 7},
        },
    )
    plt.gca().set_aspect(1.0)




.. image-sg:: /gallery/basic/images/sphx_glr_plot_grouping_001.png
   :alt: plot grouping
   :srcset: /gallery/basic/images/sphx_glr_plot_grouping_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 32-38

.. note::
  Group layouts are computed as rounded convex hulls around each group of vertices.
  If you are interested in contributing an algorithm that computes concave group
  layouts, please reach out on GitHub!

Groups can be styles in a similar way as all other elements in `iplotx`:

.. GENERATED FROM PYTHON SOURCE LINES 38-59

.. code-block:: Python


    ipx.network(
        network=g,
        layout="circle",
        grouping={
            "singleton": {0},
            "doublet": {1, 2},
            "multiplet": {3, 4, 5, 6, 7},
        },
        vertex_size=18,
        vertex_labels=True,
        vertex_label_color="white",
        grouping_facecolor=["purple", "deeppink", "tomato"],
        grouping_edgecolor="black",
        grouping_linewidth=2,
        grouping_vertexpadding=21,
        network_zorder=2,
        grouping_zorder=1,
    )
    plt.gca().set_aspect(1.0)




.. image-sg:: /gallery/basic/images/sphx_glr_plot_grouping_002.png
   :alt: plot grouping
   :srcset: /gallery/basic/images/sphx_glr_plot_grouping_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 60-65

.. warning::
  `vertexpadding` and `vertex_size` are **approximately** the same units of measurements, but not exactly. If you need a tight padding, try reducing the
  padding value below the size of vertices until it's as tight a fit as you need, as shown in the code below.

This can also be achieved with two separate calls, the first one to draw the network and the second to draw the grouping.

.. GENERATED FROM PYTHON SOURCE LINES 65-97

.. code-block:: Python


    import igraph as ig
    import matplotlib.pyplot as plt
    import iplotx as ipx

    g = ig.Graph.Ring(8)
    layout = g.layout("circle")
    fig, ax = plt.subplots(figsize=(5, 5))
    ipx.network(
        network=g,
        layout=layout,
        ax=ax,
        vertex_size=18,
        vertex_labels=True,
        vertex_label_color="white",
        zorder=2,
    )
    ipx.network(
        grouping={
            "singleton": {0},
            "doublet": {1, 2},
            "multiplet": {3, 4, 5, 6, 7},
        },
        layout=layout,
        ax=ax,
        grouping_facecolor=["purple", "deeppink", "tomato"],
        grouping_edgecolor="black",
        grouping_linewidth=2,
        grouping_vertexpadding=12,  # Note the tighter padding
        zorder=1,
    )




.. image-sg:: /gallery/basic/images/sphx_glr_plot_grouping_003.png
   :alt: plot grouping
   :srcset: /gallery/basic/images/sphx_glr_plot_grouping_003.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    [<iplotx.network.groups.GroupingCollection object at 0x7dd1f9b17610>]



.. GENERATED FROM PYTHON SOURCE LINES 98-103

.. note::
  The argument `zorder` is applied to both network and grouping style, however
  since only one of them is plotted each time this is equivalent to setting
  `network_zorder` and `grouping_zorder`. If both are specified, `zorder` takes
  priority over its more specific cousins.


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

   **Total running time of the script:** (0 minutes 0.126 seconds)


.. _sphx_glr_download_gallery_basic_plot_grouping.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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