.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/network_science/plot_arrowlawn.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_arrowlawn.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_network_science_plot_arrowlawn.py:


Arrow lawn
==========

This example demonstrates the visualisation of a network with 1,000 nodes and a few thousand
edges, using a custom layout that resembles a lawn of arrows.

.. GENERATED FROM PYTHON SOURCE LINES 8-46

.. code-block:: Python


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

    n = 1000  # Number of nodes
    k = 3
    layout = np.random.rand(n, 2)
    nodes = np.arange(n)
    edges = []
    for i, v1 in enumerate(layout):
        found = 0
        dv = layout - v1
        for j in (dv**2).sum(axis=1).argsort()[1:]:
            angle = 180 / np.pi * np.arctan2(dv[j, 1], dv[j, 0])
            # Only make an edge for neighbors towards the north-east
            if 10 < angle < 80:
                edges.append((i, j))
                found += 1
                if found == k:
                    break

    # Plot the network using iplotx
    fig, ax = plt.subplots(figsize=(7, 7))
    ipx.network(
        {'nodes': nodes, 'edges': edges, 'directed': True},
        layout=layout,
        ax=ax,
        vertex_size=5,
        vertex_alpha=0.8,
        vertex_facecolor="seagreen",
        vertex_edgecolor="none",
        edge_arrow_width=3,
        edge_alpha=0.5,
    )
    fig.tight_layout()





.. image-sg:: /gallery/network_science/images/sphx_glr_plot_arrowlawn_001.png
   :alt: plot arrowlawn
   :srcset: /gallery/network_science/images/sphx_glr_plot_arrowlawn_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 47-50

If you want to start pushing the scalability of iplotx, you can try with 10,000 nodes and
~30,000 edges. This takes ~14 seconds on a modern laptop, of which 5 are spent on building
the network and 9 are spent inside of ``iplotx`` visualising it:

.. GENERATED FROM PYTHON SOURCE LINES 50-82

.. code-block:: Python


    n = 10000  # Number of nodes
    k = 3
    layout = np.random.rand(n, 2)
    nodes = np.arange(n)
    edges = []
    for i, v1 in enumerate(layout):
        found = 0
        dv = layout - v1
        for j in (dv**2).sum(axis=1).argsort()[1:]:
            angle = 180 / np.pi * np.arctan2(dv[j, 1], dv[j, 0])
            # Only make an edge for neighbors towards the north-east
            if 10 < angle < 80:
                edges.append((i, j))
                found += 1
                if found == k:
                    break

    # Plot the network using iplotx
    fig, ax = plt.subplots(figsize=(9, 9))
    ipx.network(
        {'nodes': nodes, 'edges': edges, 'directed': True},
        layout=layout,
        ax=ax,
        vertex_size=5,
        vertex_alpha=0.8,
        vertex_facecolor="seagreen",
        vertex_edgecolor="none",
        edge_arrow_width=3,
        edge_alpha=0.5,
    )
    fig.tight_layout()



.. image-sg:: /gallery/network_science/images/sphx_glr_plot_arrowlawn_002.png
   :alt: plot arrowlawn
   :srcset: /gallery/network_science/images/sphx_glr_plot_arrowlawn_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 49.499 seconds)


.. _sphx_glr_download_gallery_network_science_plot_arrowlawn.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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