论文标题
LSQT：捆绑和布局的低螺丝式准树
LSQT: Low-Stretch Quasi-Trees for Bundling and Layout
论文作者
论文摘要
我们使用LSQT向可视化界介绍了低伸展的树，这是我们的新型技术，该技术都使用准树进行布局和边缘捆绑。我们的方法通过利用低伸展树的便利性能提供了强大的计算速度和复杂性，这与任意跨越的树相比，它准确地反映出具有优越性的任意图的拓扑结构。低伸展的准树也具有可证明的稀疏性保证，从而为毛球图的积极杂交提供了算法支持。 LSQT不依赖于先前计算的顶点位置，并且在发生任何几何布局之前，基于拓扑结构计算束。边缘捆绑包有效地计算并存储在明确的数据结构中，该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捆绑包查询。我们的未优化实现在八秒钟内处理了超过100,000个边缘的图形，其性能比以前的方法高得多。
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.
