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Computer Science > Mathematical Software

arXiv:2310.11626 (cs)
[Submitted on 17 Oct 2023]

Title:HyperNetX: A Python package for modeling complex network data as hypergraphs

Authors:Brenda Praggastis, Sinan Aksoy, Dustin Arendt, Mark Bonicillo, Cliff Joslyn, Emilie Purvine, Madelyn Shapiro, Ji Young Yun
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Abstract:HyperNetX (HNX) is an open source Python library for the analysis and visualization of complex network data modeled as hypergraphs. Initially released in 2019, HNX facilitates exploratory data analysis of complex networks using algebraic topology, combinatorics, and generalized hypergraph and graph theoretical methods on structured data inputs. With its 2023 release, the library supports attaching metadata, numerical and categorical, to nodes (vertices) and hyperedges, as well as to node-hyperedge pairings (incidences). HNX has a customizable Matplotlib-based visualization module as well as HypernetX-Widget, its JavaScript addon for interactive exploration and visualization of hypergraphs within Jupyter Notebooks. Both packages are available on GitHub and PyPI. With a growing community of users and collaborators, HNX has become a preeminent tool for hypergraph analysis.
Comments: 3 pages, 2 figures
Subjects: Mathematical Software (cs.MS)
Cite as: arXiv:2310.11626 [cs.MS]
  (or arXiv:2310.11626v1 [cs.MS] for this version)
  https://doi.org/10.48550/arXiv.2310.11626

Submission history

From: Brenda Praggastis PhD [view email]
[v1] Tue, 17 Oct 2023 23:24:11 UTC (2,222 KB)
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