Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data

Zhou, Youjia; Chalapathi, Nithin; Rathore, Archit; Zhao, Yaodong; Wang, Bei

Mapper algorithm is a popular tool from topological data analysis for extracting topological summaries of high-dimensional datasets. It has enjoyed great success in data science, from shape classification to cancer research and sports analytics. In this paper, we present Mapper Interactive, a web-based framework for the interactive analysis and visualization of high-dimensional point cloud data built upon the mapper algorithm. Different from existing implementations, Mapper Interactive implements the mapper algorithm in an interactive, scalable, and easily extendable way, thus supporting practical data analysis. In particular, its command-line API can compute mapper graphs for 1 million points of 512 dimensions in about 3 minutes (6 times faster than the vanilla implementation). Its visual interface allows on-the-fly computation and manipulation of the mapper graph based on user-specified parameters and supports the addition of new analysis modules with a few lines of code. Mapper Interactive makes the mapper algorithm accessible to nonspecialists and accelerates topological analysis workflows.