gcmpy 0.0.1

Generalised Configuration Model random Graphs in Python

Overview

gcmpy is a Python library that creates random graph models according to the generalised configuration model (GCM). Random graph models provide an excellent framework to integrate topology with dynamics. The topology of a network is crucial to the outcome of a dynamical process, such as an epidemic, occurring over a network.

To create the networks, gcmpy creates a joint degree distribution object through a variety of analytical or empirical methods. Once constructed, this joint distribution is sampled to obtain a joint degree sequence. The joint sequence is then used in the GCM algorithm to create an edge list.

gcmpy generates networks as edge lists and therefore can be integrated into any graph library such as networkx or iGraph.

Networks can be given storage tags to classify the properties for database look-up.

Installation

You can install gcmpy directly from PyPi using pip:

pip install gcmpy

The master distribution of gcmpy is hosted on GitHub. To obtain a copy, just clone the repo:

git clone [e-mail]:PeterStAndrews/gcmpy.git
cd gcmpy
python setup.py install

Documentation

API documentation for gcmpy is available on ReadTheDocs

Author and license

Copyright (c) 2021, Peter Mann <[e-mail]>

Licensed under the GNU General Public License v2 or later (GPLv2+).