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

.. only:: html

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

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

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

.. _sphx_glr_gallery_style_plot_voronoi.py:


Voronoi tessellation
====================

This example shows how to combine `iplotx` visualisations with other tools
such as `scipy` and vanilla `matplotlib`. This is one of the key strengths
of `iplotx` over custom visualisations in many other packages: `iplotx`
produces fully compliant matplotlib artists that can be combined with other
matplotlib tools, including `seaborn`.

.. GENERATED FROM PYTHON SOURCE LINES 12-68



.. image-sg:: /gallery/style/images/sphx_glr_plot_voronoi_001.png
   :alt: plot voronoi
   :srcset: /gallery/style/images/sphx_glr_plot_voronoi_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    <matplotlib.collections.PathCollection object at 0x7dd1a6047610>





|

.. code-block:: Python


    import igraph as ig
    import numpy as np
    import matplotlib.pyplot as plt
    import iplotx as ipx
    from scipy.spatial import Voronoi, voronoi_plot_2d
    from scipy.spatial.distance import cdist

    # Plot a graph with iplotx
    g = ig.Graph.Ring(8, directed=True)
    fig, ax = plt.subplots()
    art = ipx.plot(
        g,
        ax=ax,
        layout="circle",
        aspect=1,
    )[0]

    # Add a Voronoi tasselation via scipy
    vor = Voronoi(art.get_layout().values)
    voronoi_plot_2d(
        vor,
        ax=ax,
        show_points=False,
        show_vertices=False,
        line_colors="tomato",
        line_style="-",
        line_width=2,
    )
    xmin, xmax = ax.get_xlim()
    ymin, ymax = ax.get_ylim()

    # Add random points and color them based on Voronoi region
    palette = [
        "tomato",
        "steelblue",
        "purple",
        "yellow",
        "deeppink",
        "lawngreen",
        "grey",
        "black",
    ]
    rngpoints = np.random.rand(10000, 2)
    rngpoints *= np.array([xmax - xmin, ymax - ymin])
    rngpoints += np.array([xmin, ymin])

    colors = np.array(palette)[cdist(art.get_layout().values, rngpoints).argmin(axis=0)]
    ax.scatter(
        rngpoints[:, 0],
        rngpoints[:, 1],
        c=colors,
        s=20,
        alpha=0.3,
        zorder=0.5,
    )


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

   **Total running time of the script:** (0 minutes 0.193 seconds)


.. _sphx_glr_download_gallery_style_plot_voronoi.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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