Exploring Network Structure, Dynamics, and Function using NetworkX
Proceedings of the 7th Python in Science Conference, page 11 - 15. Pasadena, CA USA, (2008)Abstract
NetworkX is a Python language package for exploration
and analysis of networks and network algorithms.
The core package provides data structures
for representing many types of networks, or graphs,
including simple graphs, directed graphs, and graphs
with parallel edges and self-loops. The nodes in NetworkX
graphs can be any (hashable) Python object
and edges can contain arbitrary data; this flexibility
makes NetworkX ideal for representing networks
found in many different scientific fields.
In addition to the basic data structures many graph
algorithms are implemented for calculating network
properties and structure measures: shortest paths,
betweenness centrality, clustering, and degree distribution
and many more. NetworkX can read and
write various graph formats for easy exchange with
existing data, and provides generators for many
classic graphs and popular graph models, such as
the Erdos-Renyi, Small World, and Barabasi-Albert
models.
The ease-of-use and flexibility of the Python programming
language together with connection to the
SciPy tools make NetworkX a powerful tool for scientific
computations. We discuss some of our recent
work studying synchronization of coupled oscillators
to demonstrate how NetworkX enables research in
the field of computational networks.
