大型复杂图形绘制的亚线性时间引力计算

A. Meidiana, Seok-Hee Hong, Shijun Cai, Marnijati Torkel, P. Eades
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引用次数: 1

摘要

最近在图形可视化方面的工作试图使用采样来减少力导向算法的排斥力计算的运行时间,但是他们未能将引力计算的运行时间减少到边缘数量的次线性。我们提出了力导向算法中新的亚线性时间引力计算算法,并将其与亚线性时间排斥力计算相结合。大量实验表明,作为完全亚线性时间力计算框架的一部分,我们的算法计算图形布局的速度比现有的线性时间力计算算法平均快80%,并且在边缘交叉和基于形状的度量上具有惊人的显著提高的质量指标。
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Sublinear-Time Attraction Force Computation for Large Complex Graph Drawing
Recent works in graph visualization attempt to reduce the runtime of repulsion force computation of force-directed algorithms using sampling, however they fail to reduce the runtime for attraction force computation to sublinear in the number of edges.We present new sublinear-time algorithms for the attraction force computation of force-directed algorithms and integrate them with sublinear-time repulsion force computation.Extensive experiments show that our algorithms, operated as part of a fully sublinear-time force computation framework, compute graph layouts on average 80% faster than existing linear-time force computation algorithm, with surprisingly significantly better quality metrics on edge crossing and shape-based metrics.
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