弧长纵横比选择的数学基础

Fubo Han, Yunhai Wang, Jian Zhang, O. Deussen, Baoquan Chen
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引用次数: 4

摘要

图的纵横比可以强烈地影响对数据趋势的感知。基于弧长的纵横比选择(AL)与以往的方法相比显示出许多经验优势。然而,目前还不清楚为什么以及何时这种方法起作用。本文试图通过探究其数学基础来揭开其神秘面纱。首先,我们解释了为什么该方法是参数化不变的基本原理,并遵循相同的基本原理来扩展以前的非参数化不变的方法。因此,我们提出了最大化加权局部曲率(MLC),这是局部定向分辨率(LOR)的一种参数化不变形式,并揭示了平均斜率(As)和合成向量(RV)之间的理论联系。此外,我们建立了人工智能与45度倾斜度之间的数学联系,并推导了其平均绝对斜率的上界和下界。最后,我们进行了定量比较,从三个方面修正了对纵横比选择方法的理解:(1)表明AL、AWO和RV的表现总是非常相似,而MS则不是;(2)证明了RV相对于AL的鲁棒性优势;(3)提供一个反例,其中所有先前的方法产生较差的结果,而MLC工作良好。
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Mathematical foundations of arc length-based aspect ratio selection
The aspect ratio of a plot can strongly influence the perception of trends in the data. Arc length based aspect ratio selection (AL) has demonstrated many empirical advantages over previous methods. However, it is still not clear why and when this method works. In this paper, we attempt to unravel its mystery by exploring its mathematical foundation. First, we explain the rationale why this method is parameterization invariant and follow the same rationale to extend previous methods which are not parameterization invariant. As such, we propose maximizing weighted local curvature (MLC), a parameterization invariant form of local orientation resolution (LOR) and reveal the theoretical connection between average slope (AS) and resultant vector (RV). Furthermore, we establish a mathematical connection between AL and banking to 45 degrees and derive the upper and lower bounds of its average absolute slopes. Finally, we conduct a quantitative comparison that revises the understanding of aspect ratio selection methods in three aspects: (1) showing that AL, AWO and RV always perform very similarly while MS is not; (2) demonstrating the advantages in the robustness of RV over AL; (3) providing a counterexample where all previous methods produce poor results while MLC works well.
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