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Selecting the Aspect Ratio of a Scatter Plot Based on Its Delaunay Triangulation

机译:基于Delaunay三角剖分的散点图长宽比选择

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Scatter plots are diagrams that visualize two-dimensional data as sets of points in the plane. They allow users to detect correlations and clusters in the data. Whether or not a user can accomplish these tasks highly depends on the aspect ratio selected for the plot, i.e., the ratio between the horizontal and the vertical extent of the diagram. We argue that an aspect ratio is good if the Delaunay triangulation of the scatter plot at this aspect ratio has some nice geometric property, e.g., a large minimum angle or a small total edge length. More precisely, we consider the following optimization problem. Given a set Q of points in the plane, find a scale factor s such that scaling the x-coordinates of the points in Q by s and the y-coordinates by 1=s yields a point set P(s) that optimizes a property of the Delaunay triangulation of P(s), over all choices of s. We present an algorithm that solves this problem efficiently and demonstrate its usefulness on real-world instances. Moreover, we discuss an empirical test in which we asked 64 participants to choose the aspect ratios of 18 scatter plots. We tested six different quality measures that our algorithm can optimize. In conclusion, minimizing the total edge length and minimizing what we call the 'uncompactness' of the triangles of the Delaunay triangulation yielded the aspect ratios that were most similar to those chosen by the participants in the test.
机译:散点图是将二维数据可视化为平面中的点集的图。它们使用户可以检测数据中的相关性和聚类。用户能否完成这些任务很大程度上取决于为绘图选择的纵横比,即图表的水平和垂直范围之间的比例。我们认为,如果散点图的Delaunay三角剖分在此长宽比下具有一些不错的几何特性(例如,较大的最小角度或较小的总边长),则长宽比良好。更准确地说,我们考虑以下优化问题。给定平面中的一组点Q,请找到一个比例因子s,使Q中的点的x坐标按s缩放,而y坐标按1 = s缩放可生成优化属性的点集P(s)。在s的所有选择上,P(s)的Delaunay三角剖分的。我们提出了一种可以有效解决此问题的算法,并证明了其在实际实例中的有用性。此外,我们讨论了一项经验测试,其中我们要求64位参与者选择18个散点图的纵横比。我们测试了算法可以优化的六种不同质量指标。总之,最小化总边缘长度并最小化Delaunay三角剖分三角形的所谓“非紧实度”,可以得到与测试参与者选择的最相似的长宽比。

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