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

.. only:: html

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

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

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

.. _sphx_glr_gallery_biology_plot_pollinators.py:


Pollinators
===========

This example demonstrates how to visualise the bipartite relationship between plants and their pollinators using ``iplotx``.

This particular example uses igraph to load and process the network data, but you can also use networkx, the internal
data structures of ``iplotx``, or any other library you prefer.

.. GENERATED FROM PYTHON SOURCE LINES 10-44

.. code-block:: Python


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


    # Load the data with the adjacency matrix. 1 means that pollinator j visits plant i.
    edge_data = pd.read_csv("https://dshizuka.github.io/networkanalysis/SampleData/Sample_bipartite.csv", index_col=0)

    # Convert it into a DataFrame for igraph
    edge_data = edge_data.T.stack()
    edge_data = edge_data[edge_data > 0].index.to_frame()
    edge_data.columns = ["from", "to"]
    g = ig.Graph.DataFrame(edge_data, directed=True, use_vids=False)

    # Set vertex types: plants (0) and pollinators (1)
    g.vs["type"] = [0 if name.startswith("Plant") else 1 for name in g.vs["name"]]

    # Compute bipartite layout
    layout = g.layout_bipartite()


    fig, ax = plt.subplots(figsize=(7, 4))
    ipx.network(
        g,
        layout=layout,
        style="hollow",
        ax=ax,
        vertex_labels=g.vs["name"],
    )
    fig.tight_layout()





.. image-sg:: /gallery/biology/images/sphx_glr_plot_pollinators_001.png
   :alt: plot pollinators
   :srcset: /gallery/biology/images/sphx_glr_plot_pollinators_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 45-46

We can add a bit of color and invert the y axis direction for clarity:

.. GENERATED FROM PYTHON SOURCE LINES 46-70

.. code-block:: Python


    color_map = {"hummingbird": "steelblue", "bat": "grey", "butterfly": "tomato", "moth": "brown", "bee": "gold"}
    vertex_facecolors = {}
    for i, name in enumerate(g.vs["name"]):
        vertex_facecolors[i] = color_map.get(name, "lightgreen")

    edge_colors = []
    for pollinator in edge_data["from"].values:
        edge_colors.append(color_map.get(pollinator, "lightgreen"))

    # sphinx_gallery_thumbnail_number = 2
    fig, ax = plt.subplots(figsize=(7, 4))
    ipx.network(
        g,
        layout=layout,
        style="hollow",
        ax=ax,
        vertex_labels=g.vs["name"],
        vertex_facecolor=vertex_facecolors,
        vertex_alpha=0.6,
        edge_color=edge_colors,
    )
    ax.invert_yaxis()
    fig.tight_layout()



.. image-sg:: /gallery/biology/images/sphx_glr_plot_pollinators_002.png
   :alt: plot pollinators
   :srcset: /gallery/biology/images/sphx_glr_plot_pollinators_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.254 seconds)


.. _sphx_glr_download_gallery_biology_plot_pollinators.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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