{"title":"超图综合仿真框架:基于 Python 的方法","authors":"Quoc Chuong Nguyen, Trung Kien Le","doi":"arxiv-2401.03917","DOIUrl":null,"url":null,"abstract":"Hypergraphs, or generalization of graphs such that edges can contain more\nthan two nodes, have become increasingly prominent in understanding complex\nnetwork analysis. Unlike graphs, hypergraphs have relatively few supporting\nplatforms, and such dearth presents a barrier to more widespread adaptation of\nhypergraph computational toolboxes that could enable further research in\nseveral areas. Here, we introduce HyperRD, a Python package for hypergraph\ncomputation, simulation, and interoperability with other powerful Python\npackages in graph and hypergraph research. Then, we will introduce two models\non hypergraph, the general Schelling's model and the SIR model, and simulate\nthem with HyperRD.","PeriodicalId":501256,"journal":{"name":"arXiv - CS - Mathematical Software","volume":"28 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Toward a comprehensive simulation framework for hypergraphs: a Python-base approach\",\"authors\":\"Quoc Chuong Nguyen, Trung Kien Le\",\"doi\":\"arxiv-2401.03917\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hypergraphs, or generalization of graphs such that edges can contain more\\nthan two nodes, have become increasingly prominent in understanding complex\\nnetwork analysis. Unlike graphs, hypergraphs have relatively few supporting\\nplatforms, and such dearth presents a barrier to more widespread adaptation of\\nhypergraph computational toolboxes that could enable further research in\\nseveral areas. Here, we introduce HyperRD, a Python package for hypergraph\\ncomputation, simulation, and interoperability with other powerful Python\\npackages in graph and hypergraph research. Then, we will introduce two models\\non hypergraph, the general Schelling's model and the SIR model, and simulate\\nthem with HyperRD.\",\"PeriodicalId\":501256,\"journal\":{\"name\":\"arXiv - CS - Mathematical Software\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-08\",\"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-2401.03917\",\"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-2401.03917","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
超图,即边缘可以包含两个以上节点的图的广义化,在理解复杂网络分析方面日益突出。与图不同,超图的支持平台相对较少,这种匮乏阻碍了超图计算工具箱的广泛应用,而这些工具箱可以促进多个领域的进一步研究。在这里,我们将介绍 HyperRD,这是一个用于超图计算、仿真以及与图和超图研究领域其他强大 Python 软件包互操作的 Python 软件包。然后,我们将介绍两种超图模型:一般谢林模型和 SIR 模型,并用 HyperRD 对它们进行仿真。
Toward a comprehensive simulation framework for hypergraphs: a Python-base approach
Hypergraphs, or generalization of graphs such that edges can contain more
than two nodes, have become increasingly prominent in understanding complex
network analysis. Unlike graphs, hypergraphs have relatively few supporting
platforms, and such dearth presents a barrier to more widespread adaptation of
hypergraph computational toolboxes that could enable further research in
several areas. Here, we introduce HyperRD, a Python package for hypergraph
computation, simulation, and interoperability with other powerful Python
packages in graph and hypergraph research. Then, we will introduce two models
on hypergraph, the general Schelling's model and the SIR model, and simulate
them with HyperRD.