LSQT：用于捆绑和布局的低拉伸准树
LSQT: Low-Stretch Quasi-Trees for Bundling and Layout
摘要：
我们引入低拉伸树的可视化社区与LSQT，我们的新技术，使用准树的布局和边缘捆绑。我们的方法提供了强大的计算速度和复杂性的保证，利用低拉伸树，准确地反映了任意图的拓扑结构，具有优越的保真度相比，任意生成树的方便属性。低拉伸准树也有可证明的稀疏性保证，为毛球图的积极去杂波提供算法支持。LSQT不依赖于先前计算的顶点位置，并且在任何几何布局发生之前基于拓扑结构计算束。边缘束被有效地计算并存储在显式数据结构中，该显式数据结构支持复杂的视觉编码和交互技术，包括动态布局调整和交互式束查询。我们的未优化实现在8秒内处理超过100，000条边的图形，提供比以前方法更高的性能。
英文摘要：
We introduce low-stretch trees to the visualization community with LSQT, our novel technique that uses quasi-trees for both layout and edge bundling. Our method offers strong computational speed and complexity guarantees by leveraging the convenient properties of low-stretch trees, which accurately reflect the topological structure of arbitrary graphs with superior fidelity compared to arbitrary spanning trees. Low-stretch quasi-trees also have provable sparseness guarantees, providing algorithmic support for aggressive de-cluttering of hairball graphs. LSQT does not rely on previously computed vertex positions and computes bundles based on topological structure before any geometric layout occurs. Edge bundles are computed efficiently and stored in an explicit data structure that supports sophisticated visual encoding and interaction techniques, including dynamic layout adjustment and interactive bundle querying. Our unoptimized implementation handles graphs of over 100,000 edges in eight seconds, providing substantially higher performance than previous approaches.
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