Algorithm 1044: PyGenStability, a Multiscale Community Detection Framework with Generalized Markov Stability

Author:

Arnaudon Alexis1ORCID,Schindler Dominik J.1ORCID,Peach Robert L.2ORCID,Gosztolai Adam3ORCID,Hodges Maxwell4ORCID,Schaub Michael T.5ORCID,Barahona Mauricio1ORCID

Affiliation:

1. Department of Mathematics, Imperial College London, London, United Kingdom

2. Department of Neurology, University Hospital Würzburg, Würzburg, Germany

3. Signal Processing Laboratory (LTS2), EPFL, Lausanne, Switzerland

4. Spotify, London, United Kingdom

5. Computational Network Science Group, RWTH Aachen University, Aachen, Germany

Abstract

We present PyGenStability, a general-use Python software package that provides a suite of analysis and visualization tools for unsupervised multiscale community detection in graphs. PyGenStability finds optimized partitions of a graph at different levels of resolution by maximizing the generalized Markov Stability quality function with the Louvain or Leiden algorithm. The package includes automatic detection of robust graph partitions and allows the flexibility to choose quality functions for weighted undirected, directed, and signed graphs and to include other user-defined quality functions.

Funder

EPSRC Centre for Mathematics of Precision Healthcare at Imperial College London

DFG, German Research Foundation

PhD studentship through the Department of Mathematics at Imperial College London

HFSP Cross-disciplinary Postdoctoral Fellowship

Publisher

Association for Computing Machinery (ACM)

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