Generalised Configuration Model random Graphs in Python
Project description
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.
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 gcmpyThe master distribution of gcmpy is hosted on GitHub. To obtain a copy, just clone the repo:
git clone git@github.com:PeterStAndrews/gcmpy.git
cd gcmpy
python setup.py installDocumentation
API documentation for gcmpy is available on ReadTheDocs
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