evomap让动态地图分析更简单，支持随时间变化的可视化关系建模。
evomap: A Toolbox for Dynamic Mapping in Python
- 基于EvoMap框架，将传统静态映射方法扩展为动态分析
- 支持MDS、t-SNE等多类映射算法，可追踪关系演变过程
- 适合需要分析数据随时间变化关系的研究者使用
本文介绍evomap，一个用于动态地图分析的Python工具包。地图方法广泛应用于各学科，以空间形式可视化对象间的关系。然而，现有统计软件大多仅支持静态地图，只能捕捉某一时刻的对象关系，缺乏分析关系演变的工具。evomap填补了这一空白，实现了Matthe、Ringel和Skiera（2023）提出的动态地图框架EvoMap，将传统静态映射方法拓展至动态分析。该工具包支持多种映射技术，包括多维尺度分析（MDS）、Sammon映射和t分布随机邻域嵌入（t-SNE），并提供数据预处理、探索与结果评估的配套工具，构成完整的动态地图分析套件。本文阐述了静态与动态地图的基础理论，介绍了evomap的架构与功能，并通过详尽的应用示例展示其用法。
原文摘要 · Abstract (English)
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.
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