A new nonlinear dot plots visualization based on an undirected reassignment algorithm
A new nonlinear dot plots visualization based on an undirected reassignment algorithm
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DOI：
10.1007/s12650-020-00711-5
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发表时间：
2021-01
影响因子：
1.7
通讯作者：
Yun Xiao;Changqing Wang;Kang Li;Baoying Liu;Jun Guo;Wei Wang
中科院分区：
文献类型：
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作者：
Yun Xiao;Changqing Wang;Kang Li;Baoying Liu;Jun Guo;Wei Wang
原始的非线性点图是通过双向扫描算法为不同大小的点设计的。然而，该算法使用双向扫描的起始点的平均值来确定列位置，这可能导致所获得的数据列的位置不准确。同时，双向扫描算法在高密度数据区域存在表达不清晰的缺点。为了解决这个问题，我们提出了一个改进的非线性点图的基础上无向重新分配算法。改进的非线性点图可以处理和分配数据，以实现优化布局，可以确定合适的点位置和数据分布。该算法在显示离群点和避免重叠方面更有效。在非线性点图中可以呈现具有大差异的点。我们提出的方法可以进一步与其他数据可视化属性相结合，用于数据分析目的。利用一系列真实的数据集，将改进的非线性点图与传统的点图和原始的非线性点图进行了比较。实验结果表明，改进后的非线性点图不仅能显示不同大小的点，而且能以极高的密度清晰地显示数据。
The original nonlinear dot plots were designed for dots of varying sizes by the two-way sweep algorithm. However, this algorithm uses the average of the starting point of the two-way sweep to determine the column position, which can lead to inaccurate position of the obtained data columns. Meanwhile, the two-way sweep algorithm has the shortcoming of unclear expression in high-density data area. In order to address this problem, we propose an improved nonlinear dot plot based on an undirected reassignment algorithm. The improved nonlinear dot plots can process and assign data in order to achieve an optimized layout that can identify the suitable dot position and data distribution. The proposed algorithm is more effective at displaying outliers and avoiding overlaps. Dots with large differences can be presented in the nonlinear dot plots. Our proposed method can further be combined with other data visualization attributions for data analysis purposes. Using a series of real datasets, the improved nonlinear dot plots are compared with both the conventional dot plots and the original nonlinear dot plots. Results show that our improved nonlinear dot plots not only allow for dots of varying sizes, but also clearly display the data with extremely high density.Graphic abstract