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Quality Metrics for Symmetric Graph Drawings

D. A. Keim, A. Meidiana, S.-H. Hong, P. Eades

2020 IEEE Pacific Visualization Symposium (PacificVis) : Proceedings, DOI:10.1109/PacificVis48177.2020.1022, 2020

In this paper, we present a framework for quality metrics that measure symmetry, that is, how faithfully a drawing of a graph displays the ground truth geometric automorphisms as symmetries. The quality metrics are based on group theory as well as geometry. More specifically, we introduce two types of symmetry quality metrics for displaying: (1) a single geometric automorphism as a symmetry (axial or rotational) and (2) a group of geometric automorphisms (cyclic or dihedral). We also present algorithms to compute the symmetry quality metrics in O(n log n) time. We validate our symmetry quality metrics using deformation experiments. We then use the metrics to evaluate existing graph layouts to compare how faithfully they display geometric automorphisms of a graph as symmetries.

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