.. _imnetworkxrst:

========
networkx
========


.. only:: html

    **Links:** :download:`notebook <im_networkx.ipynb>`, :downloadlink:`html <im_networkx2html.html>`, :download:`PDF <im_networkx.pdf>`, :download:`python <im_networkx.py>`, :downloadlink:`slides <im_networkx.slides.html>`, :githublink:`GitHub|_doc/notebooks/2016/pydata/im_networkx.ipynb|*`


*networkx* draws networks. It does not work too well on big graphs (<
1000 vertices).

`documentation <https://networkx.github.io/>`__
`source <https://github.com/networkx/networkx>`__
`installation <https://networkx.readthedocs.io/en/stable/install.html>`__
`tutorial <https://networkx.readthedocs.io/en/stable/tutorial/index.html>`__
`gallerie <https://networkx.github.io/documentation/networkx-1.9.1/gallery.html>`__

.. code:: ipython3

    from jyquickhelper import add_notebook_menu
    add_notebook_menu()






.. contents::
    :local:





.. code:: ipython3

    %matplotlib inline

example
-------

.. code:: ipython3

    import networkx as nx
    import matplotlib.pyplot as plt
    
    G=nx.random_geometric_graph(200,0.125)
    # position is stored as node attribute data for random_geometric_graph
    pos=nx.get_node_attributes(G,'pos')
    
    # find node near center (0.5,0.5)
    dmin=1
    ncenter=0
    for n in pos:
        x,y=pos[n]
        d=(x-0.5)**2+(y-0.5)**2
        if d<dmin:
            ncenter=n
            dmin=d
    
    # color by path length from node near center
    p=nx.single_source_shortest_path_length(G,ncenter)
    
    plt.figure(figsize=(8,8))
    nx.draw_networkx_edges(G,pos,nodelist=[ncenter],alpha=0.4)
    nx.draw_networkx_nodes(G,pos,nodelist=p.keys(),
                           node_size=80)
    
    plt.xlim(-0.05,1.05)
    plt.ylim(-0.05,1.05)
    plt.axis('off')




.. parsed-literal::
    (-0.05, 1.05, -0.05, 1.05)




.. image:: im_networkx_5_1.png