vbmod_python is python software for identifying modules in networks (e.g. "community detection"), as described in "a bayesian approach to network modularity."
this software is free for scientific use. please contact us if you plan to use this software for commercial purposes. do not further distribute without prior permission of the authors. if used in your scientific work, please cite as:
Jake M. Hofman and Chris H. Wiggins, "A Bayesian Approach to Network Modularity", Phys. Rev. Lett. 100, 258701 (2008)
vbmod_python doesn't require any installation, but does require the scipy package (http://www.scipy.org/Installing_SciPy).
it currently defaults to a version that uses weave (http://www.scipy.org/Weave) to include inline c code for better performance in the vbmod_estep_inline. (a version of this code in python is left as a comment, and can be used in lieu of the weave code in the event of compilation problems, etc.)
weave will take some time to compile the c code on the first run, but be much faster than the corresponding python code. this speedup arises because there is a for loop over nodes in the code, which is extremely slow when interpreted by python.
run 'vbmod.py' which generates an adjacency matrix for a modular random network and runs variational bayes to infer the modular structure from this adjacency matrix.
see documentation in files for further information.
copyright (c) 2007, 2008 jake hofman jhofman@gmail.com
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.