Shape-based metrics measure how faithfully a drawing D represents the structure of a graph G, using the proximity graph S of D. While some limited graph classes admit proximity drawings (i.e., optimally shape-faithful drawings, where S = G), algorithms for shape-faithful drawings of general graphs have not been investigated. In this paper, we present the first study for shape-faithful drawings of general graphs. First, we conduct extensive comparison experiments for popular graph layouts using the shape-based metrics, and examine the properties of highly shape-faithful drawings. Then, we present ShFR and ShSM, algorithms for shape-faithful drawings based on force-directed and stress-based algorithms, by introducing new proximity forces/stress. Experiments show that ShFR and ShSM obtain significant improvement over FR (Fruchterman-Reingold) and SM (Stress Majorization), on average 12% and 35% respectively, on shape-based metrics.

翻译：以形状为基础的度量测量图D如何忠实地代表图形G的结构,使用D的近距离图S。虽然一些有限的图表类别接受近距离图(即最优形状忠心的图画,即S=G),但一般图的形状忠心图的算法尚未调查。在本文中,我们介绍了关于一般图的形状忠心图的第一次研究。首先,我们用形状为基础的度量表对广受欢迎的图表布局进行了广泛的比较实验,并检查了高度形状忠心的图画的特性。然后,我们介绍了基于以力量为方向和以压力为根据的算法的形状忠心图的算法。实验显示,根据基于形状的测量法(Fruchterman-Reingold)和SM(Sstress Majoriz)分别平均12%和35%的基于形状的测量法(FR(Fruchtermanan-Reingold)和SM(Sstress Maj)取得了显著的改进。