HyperNetX:一个Python包,用于将复杂网络数据建模为超图

Brenda Praggastis, Sinan Aksoy, Dustin Arendt, Mark Bonicillo, Cliff Joslyn, Emilie Purvine, Madelyn Shapiro, Ji Young Yun
{"title":"HyperNetX:一个Python包,用于将复杂网络数据建模为超图","authors":"Brenda Praggastis, Sinan Aksoy, Dustin Arendt, Mark Bonicillo, Cliff Joslyn, Emilie Purvine, Madelyn Shapiro, Ji Young Yun","doi":"arxiv-2310.11626","DOIUrl":null,"url":null,"abstract":"HyperNetX (HNX) is an open source Python library for the analysis and\nvisualization of complex network data modeled as hypergraphs. Initially\nreleased in 2019, HNX facilitates exploratory data analysis of complex networks\nusing algebraic topology, combinatorics, and generalized hypergraph and graph\ntheoretical methods on structured data inputs. With its 2023 release, the\nlibrary supports attaching metadata, numerical and categorical, to nodes\n(vertices) and hyperedges, as well as to node-hyperedge pairings (incidences).\nHNX has a customizable Matplotlib-based visualization module as well as\nHypernetX-Widget, its JavaScript addon for interactive exploration and\nvisualization of hypergraphs within Jupyter Notebooks. Both packages are\navailable on GitHub and PyPI. With a growing community of users and\ncollaborators, HNX has become a preeminent tool for hypergraph analysis.","PeriodicalId":501256,"journal":{"name":"arXiv - CS - Mathematical Software","volume":"15 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\",\"doi\":\"arxiv-2310.11626\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"HyperNetX (HNX) is an open source Python library for the analysis and\\nvisualization of complex network data modeled as hypergraphs. Initially\\nreleased in 2019, HNX facilitates exploratory data analysis of complex networks\\nusing algebraic topology, combinatorics, and generalized hypergraph and graph\\ntheoretical methods on structured data inputs. With its 2023 release, the\\nlibrary supports attaching metadata, numerical and categorical, to nodes\\n(vertices) and hyperedges, as well as to node-hyperedge pairings (incidences).\\nHNX has a customizable Matplotlib-based visualization module as well as\\nHypernetX-Widget, its JavaScript addon for interactive exploration and\\nvisualization of hypergraphs within Jupyter Notebooks. Both packages are\\navailable on GitHub and PyPI. With a growing community of users and\\ncollaborators, HNX has become a preeminent tool for hypergraph analysis.\",\"PeriodicalId\":501256,\"journal\":{\"name\":\"arXiv - CS - Mathematical Software\",\"volume\":\"15 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Mathematical Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2310.11626\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Mathematical Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2310.11626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HyperNetX: A Python package for modeling complex network data as hypergraphs
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信