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

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.
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HyperNetX:一个Python包,用于将复杂网络数据建模为超图
HyperNetX (HNX)是一个开源的Python库,用于分析和可视化建模为超图的复杂网络数据。HNX最初于2019年发布,使用代数拓扑、组合学、广义超图和图论方法对结构化数据输入进行复杂网络的探索性数据分析。随着2023年的发布,该库支持将元数据(数值和分类)附加到节点(顶点)和超边缘,以及节点-超边缘配对(发生率)。HNX有一个可定制的基于matplotlib的可视化模块,以及hypernetx - widget,它的JavaScript插件用于在Jupyter notebook中进行超图的交互式探索和可视化。这两个包都可以在GitHub和PyPI上获得。随着用户和合作者社区的不断壮大,HNX已经成为超图分析的卓越工具。
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