python-louvain

by taynaud

Louvain Community Detection

502 Stars 135 Forks Last release: Not found Other 99 Commits 0 Releases

Available items

No Items, yet!

The developer of this repository has not created any items for sale yet. Need a bug fixed? Help with integration? A different license? Create a request here:

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

import community as 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

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.