Han Chang, Jo Jaemin, Li Anyi, Lee Bongshin, Deussen Oliver, Wang Yunhai
IEEE Trans Vis Comput Graph. 2023 Jan;29(1):193-202. doi: 10.1109/TVCG.2022.3209450. Epub 2022 Dec 16.
We present SizePairs, a new technique to create stable and balanced treemap layouts that visualize values changing over time in hierarchical data. To achieve an overall high-quality result across all time steps in terms of stability and aspect ratio, SizePairs employs a new hierarchical size-based pairing algorithm that recursively pairs two nodes that complement their size changes over time and have similar sizes. SizePairs maximizes the visual quality and stability by optimizing the splitting orientation of each internal node and flipping leaf nodes, if necessary. We also present a comprehensive comparison of SizePairs against the state-of-the-art treemaps developed for visualizing time-dependent data. SizePairs outperforms existing techniques in both visual quality and stability, while being faster than the local moves technique.
我们提出了SizePairs，这是一种用于创建稳定且平衡的树形图布局的新技术，可将分层数据中随时间变化的值可视化。为了在稳定性和宽高比方面在所有时间步长上实现整体高质量的结果，SizePairs采用了一种基于大小的新分层配对算法，该算法递归地将两个节点配对，这两个节点在大小上随时间互补且大小相似。SizePairs通过优化每个内部节点的分割方向并在必要时翻转叶节点，从而使视觉质量和稳定性最大化。我们还对SizePairs与为可视化随时间变化的数据而开发的最新树形图进行了全面比较。SizePairs在视觉质量和稳定性方面均优于现有技术，同时比局部移动技术更快。
