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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_arxiv_ml_edge_bundle.py:


ArXiv ML Word Cloud Style
-------------------------

Demonstrating the word cloud style using the ArXiv ML dataset.

.. GENERATED FROM PYTHON SOURCE LINES 7-50



.. image-sg:: /auto_examples/images/sphx_glr_plot_arxiv_ml_edge_bundle_001.png
   :alt: ArXiv ML Landscape, A data map of papers from the Machine Learning section of ArXiv
   :srcset: /auto_examples/images/sphx_glr_plot_arxiv_ml_edge_bundle_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


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    Resetting positions to accord with alignment






|

.. code-block:: Python


    import datamapplot
    import numpy as np
    import requests
    import PIL
    import matplotlib.pyplot as plt
    import colorcet

    plt.rcParams["savefig.bbox"] = "tight"

    arxivml_data_map = np.load("arxiv_ml_data_map.npz")["arr_0"]
    arxivml_labels = np.load("arxiv_ml_cluster_labels.npz", allow_pickle=True)["arr_0"]

    arxiv_logo_response = requests.get(
        "https://upload.wikimedia.org/wikipedia/commons/7/7a/ArXiv_logo_2022.png",
        stream=True,
        headers={"User-Agent": "My User Agent 1.0"},
    )
    arxiv_logo = np.asarray(PIL.Image.open(arxiv_logo_response.raw).convert("RGBA"))

    fig, ax = datamapplot.create_plot(
        arxivml_data_map,
        arxivml_labels,
        title="ArXiv ML Landscape",
        sub_title="A data map of papers from the Machine Learning section of ArXiv",
        label_wrap_width=10,
        label_over_points=True,
        dynamic_label_size=True,
        max_font_size=36,
        min_font_size=4,
        min_font_weight=100,
        max_font_weight=1000,
        font_family="Roboto Condensed",
        cmap=colorcet.cm.CET_C2,
        logo=arxiv_logo,
        edge_bundle=True,
        add_glow=False,
        edge_bundle_keywords={"n_neighbors": 15, "color_map_nn": 15},
        darkmode=True,
        logo_width=0.1,
    )
    fig.savefig("plot_arxiv_ml_edge_bundle.png", bbox_inches="tight")
    plt.show()


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

   **Total running time of the script:** (1 minutes 8.248 seconds)


.. _sphx_glr_download_auto_examples_plot_arxiv_ml_edge_bundle.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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