标题： evomap：用于Python中动态映射的工具箱 显示英文标题

标题： evomap: A Toolbox for Dynamic Mapping in Python

摘要： 本文介绍了evomap，一个用于动态制图的Python包。 制图方法被广泛应用于各个学科，以将对象之间的关系可视化为空间表示，或地图。 然而，大多数现有的统计软件仅支持静态制图，这只能在某一时间点捕捉对象之间的关系，并缺乏分析这些关系如何演变的工具。 evomap通过实现动态制图框架EvoMap填补了这一空白，该框架最初由Matthe、Ringel和Skiera（2023）提出，该框架将传统的静态制图方法适应于动态分析。 该包支持多种制图技术，包括多维缩放（MDS）的变体、Sammon映射和t分布随机邻域嵌入（t-SNE）。 它还包括数据预处理、探索和结果评估的实用程序，为动态制图应用提供了一个全面的工具包。 本文概述了静态和动态制图的基础，描述了evomap的架构和功能，并通过一个广泛的使用示例说明了其应用。 显示英文摘要

摘要： This paper presents evomap, a Python package for dynamic mapping. Mapping methods are widely used across disciplines to visualize relationships among objects as spatial representations, or maps. However, most existing statistical software supports only static mapping, which captures objects' relationships at a single point in time and lacks tools to analyze how these relationships evolve. evomap fills this gap by implementing the dynamic mapping framework EvoMap, originally proposed by Matthe, Ringel, and Skiera (2023), which adapts traditional static mapping methods for dynamic analyses. The package supports multiple mapping techniques, including variants of Multidimensional Scaling (MDS), Sammon Mapping, and t-distributed Stochastic Neighbor Embedding (t-SNE). It also includes utilities for data preprocessing, exploration, and result evaluation, offering a comprehensive toolkit for dynamic mapping applications. This paper outlines the foundations of static and dynamic mapping, describes the architecture and functionality of evomap, and illustrates its application through an extensive usage example.