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https://github.com/taynaud/python-louvain

Louvain Community Detection
https://github.com/taynaud/python-louvain

community-detection louvain-method networkx

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Louvain Community Detection

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Louvain Community Detection
===========================

.. image:: https://travis-ci.org/taynaud/python-louvain.svg?branch=master
:target: https://travis-ci.org/taynaud/python-louvain

.. image:: https://readthedocs.org/projects/python-louvain/badge/?version=latest
:target: http://python-louvain.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status

Installing
----------

To build and install from source, run

.. code-block:: shell

python setup.py install

You can also install from pip with

.. code-block:: shell

pip install python-louvain

The package name on pip is :code:`python-louvain`
but it is imported as :code:`community` in python.
More documentation for this module can be found at
`http://python-louvain.readthedocs.io/ `_

Usage
-----

To use as a Python library

.. code-block:: python

from community import community_louvain
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import networkx as nx

# load the karate club graph
G = nx.karate_club_graph()

# compute the best partition
partition = community_louvain.best_partition(G)

# draw the graph
pos = nx.spring_layout(G)
# color the nodes according to their partition
cmap = cm.get_cmap('viridis', max(partition.values()) + 1)
nx.draw_networkx_nodes(G, pos, partition.keys(), node_size=40,
cmap=cmap, node_color=list(partition.values()))
nx.draw_networkx_edges(G, pos, alpha=0.5)
plt.show()

It can also be run on the command line

.. code-block:: bash

$ community

where :code:`filename` is a binary file as generated by the
convert utility distributed with the C implementation at
`https://sites.google.com/site/findcommunities/ `_
However as this is mostly for debugging purposes its use should be avoided.
Instead importing this library for use in Python is recommended.

Documentation
-------------

You can find documentation at `https://python-louvain.readthedocs.io/ `_

To generate documentation, run

.. code-block:: shell

pip install numpydoc sphinx
cd docs
make

Tests
-----

To run tests, run

.. code-block:: shell

pip install nose
python setup.py test