IEEE Trans Vis Comput Graph. 2018 Jan;24(1):729-738. doi: 10.1109/TVCG.2017.2745140. Epub 2017 Aug 29.
Treemaps are a popular tool to visualize hierarchical data: items are represented by nested rectangles and the area of each rectangle corresponds to the data being visualized for this item. The visual quality of a treemap is commonly measured via the aspect ratio of the rectangles. If the data changes, then a second important quality criterion is the stability of the treemap: how much does the treemap change as the data changes. We present a novel stable treemapping algorithm that has very high visual quality. Whereas existing treemapping algorithms generally recompute the treemap every time the input changes, our algorithm changes the layout of the treemap using only local modifications. This approach not only gives us direct control over stability, but it also allows us to use a larger set of possible layouts, thus provably resulting in treemaps of higher visual quality compared to existing algorithms. We further prove that we can reach all possible treemap layouts using only our local modifications. Furthermore, we introduce a new measure for stability that better captures the relative positions of rectangles. We finally show via experiments on real-world data that our algorithm outperforms existing treemapping algorithms also in practice on either visual quality and/or stability. Our algorithm scores high on stability regardless of whether we use an existing stability measure or our new measure.
项目由嵌套的矩形表示，每个矩形的面积对应于为该项目可视化的数据。树图的视觉质量通常通过矩形的纵横比来衡量。如果数据发生变化，那么第二个重要的质量标准是树图的稳定性：数据变化时树图的变化有多大。我们提出了一种新颖的稳定树图算法，具有非常高的视觉质量。现有的树图算法通常在每次输入更改时重新计算树图，而我们的算法仅使用局部修改来更改树图的布局。这种方法不仅使我们可以直接控制稳定性，而且还允许我们使用更大的可能布局集，从而可以证明与现有算法相比，生成的树图具有更高的视觉质量。我们进一步证明，我们可以仅使用局部修改来达到所有可能的树图布局。此外，我们引入了一种新的稳定性度量标准，该度量标准更好地捕获了矩形的相对位置。我们最后通过对真实世界数据的实验表明，我们的算法在视觉质量和/或稳定性方面都优于现有的树图算法。无论我们使用现有的稳定性度量标准还是我们的新度量标准，我们的算法在稳定性方面的得分都很高。
