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

2023/10/17 by Brenda Praggastis, Sinan G. Aksoy, Praggastis, Brenda +13 · 2 citations
Computer Science · Physics and Astronomy · Psychology · #Complex Network Analysis Techniques #Data Visualization and Analytics #FOS: Computer and information sciences #Mathematical Software (cs.MS) #Mental Health Research Topics

paper · pdf · doi:10.48550/arxiv.2310.11626

openalex publication_date 2023/10/17 · openalex created_date 2023/10/21 · openalex updated_date 2026/07/28

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.

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