基于区间分类的螺旋图可视化边绑定方法

在时序数据可视化领域,螺旋图是一种常用的可视化方法,它既能将多个阶段的数据同时展示在一个平面空间内,又能在有限的空间内展示任意时长的数据。针对现有的螺旋图可视化方法在展示大量的时间序列数据时会出现因螺旋线交叉而导致视觉杂乱的问题,研究螺旋图可视化方法意义非凡。首先将状态圆环上的数据点进行分类；然后在相邻的状态圆环之间设置虚拟绑定圆环,通过边绑定的函数将状态圆环上的数据点映射到其对应的虚拟绑定圆环上；最后在状态圆环与其对应的虚拟绑定圆环之间绘制Bézier曲线,在虚拟绑定圆环与虚拟绑定圆环之间绘制螺旋线,从而实现边绑定的效果。实验结果表明,该边绑定算法能够有效地对大规模数据进行可视化,并能有效地缓解视觉杂乱的问题。

Edge Bundling Method of Spiral Graph Based on Interval Classification

Spiral graph is a common visualization method in visualizing time series data.It can not only simultaneous display the multiple-stages data in one plane space,but also demonstrate the data with different time length in a limited space.In order to solve the problem of visual clutter caused by the intersection of helical lines in the present spiral image visualization methods,a method of edge bundling is of great significance.First,the data points on the state circle are classified.Then the virtual bundling circles are set between the adjacent state circles,and the data points on the state ring are mapped to the corresponding virtual bundling circle by the function of edge bundling.Finally, in order to achieve the effect of curve bundling,the Bézier curve is drawn between the state circle and its corresponding virtual bundling circle,and the spiral curve is drawn between the virtual bundling circle and the virtual bundling circle.Experimental results show that the edge-bundling algorithm is effective for large-scale data visualization and can effectively alleviate the problem of visual clutter.