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连续散点图中的不连续。

Discontinuities in continuous scatter plots.

机构信息

University of Magdeburg, Germany.

出版信息

IEEE Trans Vis Comput Graph. 2010 Nov-Dec;16(6):1291-300. doi: 10.1109/TVCG.2010.146.

Abstract

The concept of continuous scatterplot (CSP) is a modern visualization technique. The idea is to define a scalar density value based on the map between an n-dimensional spatial domain and an m-dimensional data domain, which describe the CSP space. Usually the data domain is two-dimensional to visually convey the underlying, density coded, data. In this paper we investigate kinds of map-based discontinuities, especially for the practical cases n = m = 2 and n = 3 | m = 2, and we depict relations between them and attributes of the resulting CSP itself. Additionally, we show that discontinuities build critical line structures, and we introduce algorithms to detect them. Further, we introduce a discontinuity-based visualization approach—called contribution map (CM)—which establishes a relationship between the CSP's data domain and the number of connected components in the spatial domain. We show that CMs enhance the CSP-based linking & brushing interaction. Finally, we apply our approaches to a number of synthetic as well as real data sets.

摘要

连续散点图(CSP)的概念是一种现代的可视化技术。其思想是基于 n 维空间域和 m 维数据域之间的映射定义标量密度值,这些映射描述了 CSP 空间。通常,数据域是二维的,以直观地传达基础的、密度编码的数据。在本文中,我们研究了基于映射的各种不连续性,特别是对于实际情况 n = m = 2 和 n = 3 | m = 2,并描述了它们与生成的 CSP 本身属性之间的关系。此外,我们还展示了不连续性构建关键线结构,并引入了用于检测它们的算法。此外,我们引入了一种基于不连续性的可视化方法——称为贡献图(CM)——它在 CSP 的数据域和空间域中连接组件的数量之间建立了关系。我们表明,CMs 增强了基于 CSP 的链接和刷选交互。最后,我们将我们的方法应用于一些合成数据集和真实数据集。

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