Neighborhood graphs and clustering algorithms are fundamental structures in both computational geometry and data analysis. Visualizing them can help build insight into their behavior and properties. The Ipe extensible drawing editor, developed by Otfried Cheong, is a widely used software system for generating figures. One particular aspect of Ipe is the ability to add Ipelets, which extend its functionality. Here we showcase a set of Ipelets designed to help visualize neighborhood graphs and clustering algorithms. These include: $\eps$-neighbor graphs, furthest-neighbor graphs, Gabriel graphs, $k$-nearest neighbor graphs, $k^{th}$-nearest neighbor graphs, $k$-mutual neighbor graphs, $k^{th}$-mutual neighbor graphs, asymmetric $k$-nearest neighbor graphs, asymmetric $k^{th}$-nearest neighbor graphs, relative-neighbor graphs, sphere-of-influence graphs, Urquhart graphs, Yao graphs, and clustering algorithms including complete-linkage, DBSCAN, HDBSCAN, $k$-means, $k$-means++, $k$-medoids, mean shift, and single-linkage. Our Ipelets are all programmed in Lua and are freely available.

翻译：邻域图与聚类算法是计算几何与数据分析领域的核心结构。通过可视化这些结构，有助于深入理解其特性与运行机制。由Otfried Cheong开发的Ipe可扩展绘图编辑器，是一款广泛应用于图形生成的软件系统。Ipe的特色之一在于支持通过添加Ipelets扩展功能。本文展示了一套专为可视化邻域图与聚类算法设计的Ipelets工具集，涵盖以下方法：$\eps$-邻域图、最远邻域图、Gabriel图、$k$近邻图、$k^{th}$近邻图、$k$互邻图、$k^{th}$互邻图、非对称$k$近邻图、非对称$k^{th}$近邻图、相对邻域图、球域影响图、Urquhart图、Yao图，以及包括全链接聚类、DBSCAN、HDBSCAN、$k$-means、$k$-means++、$k$-medoids、均值漂移、单链接聚类在内的聚类算法。所有Ipelets均采用Lua语言编写，并免费开源提供。