Puneet Varma (Editor)

Graph tool

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Developer(s)
  
Tiago de Paula Peixoto

Operating system
  
OS X, Linux

Written in
  
Python, C++

Type
  
Software library

Stable release
  
2.12 / 6 November 2015; 16 months ago (2015-11-06)

Repository
  
https://git.skewed.de/count0/graph-tool,
https://github.com/count0/graph-tool.git

graph-tool is a Python module for manipulation and statistical analysis of graphs (AKA networks). The core data structures and algorithms of graph-tool are implemented in C++, making extensive use of metaprogramming, based heavily on the Boost Graph Library. This type of approach can confer a level of performance which is comparable (both in memory usage and computation time) to that of a pure C++ library, which can be several orders of magnitude better than pure Python.

Contents

Furthermore, many algorithms are implemented in parallel using OpenMP, which provides increased performance on multi-core architectures.

Features

  • Creation and manipulation of directed or undirected graphs.
  • Association of arbitrary information to the vertices, edges or even the graph itself, by means of property maps.
  • Filter vertices and/or edges "on the fly", such that they appear to have been removed.
  • Support for dot, Graph Modelling Language and GraphML formats.
  • Convenient and powerful graph drawing based on cairo or Graphviz.
  • Support for typical statistical measurements: degree/property histogram, combined degree/property histogram, vertex-vertex correlations, assortativity, average vertex-vertex shortest path, etc.
  • Support for several graph-theoretical algorithms: such as graph isomorphism, subgraph isomorphism, minimum spanning tree, connected components, dominator tree, maximum flow, etc.
  • Support for several centrality measures.
  • Support for clustering coefficients, as well as network motif statistics and community structure detection.
  • Generation of random graphs, with arbitrary degree distribution and correlations.
  • Support for well-established network models: Price, Barabási-Albert, Geometric Networks, Multidimensional lattice graph, etc.

    • Suitabilty

    Graph-tool can be used to work with very large graphs in a variety of contexts, including simulation of cellular tissue, data mining, analysis of social networks, analysis of P2P systems, large-scale modeling of agent-based systems, study of academic Genealogy trees, theoretical assessment and modeling of network clustering, large-scale call graph analysis, and analysis of the brain's Connectome.

    References

    Graph-tool Wikipedia
    (Text) CC BY-SA


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