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Py3plex: A Library for Scalable Multilayer Network Analysis and Visualization

机译:Py3plex:用于可伸缩多层网络分析和可视化的库

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Real-life systems are commonly represented as networks of interacting entities. While homogeneous networks consist of nodes of a single node type, multilayer networks are characterized by multiple types of nodes or edges, all present in the same system. Analysis and visualization of such networks represent a challenge for real-life complex network applications. The presented Py3plex Python-based library facilitates the exploration and visualization of multilayer networks. The library includes a diagonal projection-based network visualization, developed specifically for large networks with multiple node (and edge) types. The library also includes state-of-the-art methods for network decomposition and statistical analysis. The Py3plex functionality is showcased on real-world multilayer networks from the domains of biology and on synthetic networks.
机译:现实生活中的系统通常表示为交互实体的网络。同类网络由单个节点类型的节点组成,而多层网络则具有多种类型的节点或边的特征,所有这些都存在于同一系统中。对此类网络的分析和可视化是现实生活中复杂网络应用的挑战。所展示的基于Python的Py3plex库促进了多层网络的探索和可视化。该库包括基于对角线投影的网络可视化,专门针对具有多个节点(和边缘)类型的大型网络而开发。该库还包括用于网络分解和统计分析的最新方法。 Py3plex功能已在生物学领域和合成网络上的现实世界多层网络中得以展示。

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