English

Manipulating Weights to Improve Stress-Graph Drawings of 3-Connected Planar Graphs

Computational Geometry 2023-09-01 v2 Data Structures and Algorithms

Abstract

We study methods to manipulate weights in stress-graph embeddings to improve convex straight-line planar drawings of 3-connected planar graphs. Stress-graph embeddings are weighted versions of Tutte embeddings, where solving a linear system places vertices at a minimum-energy configuration for a system of springs. A major drawback of the unweighted Tutte embedding is that it often results in drawings with exponential area. We present a number of approaches for choosing better weights. One approach constructs weights (in linear time) that uniformly spread all vertices in a chosen direction, such as parallel to the xx- or yy-axis. A second approach morphs xx- and yy-spread drawings to produce a more aesthetically pleasing and uncluttered drawing. We further explore a "kaleidoscope" paradigm for this xyxy-morph approach, where we rotate the coordinate axes so as to find the best spreads and morphs. A third approach chooses the weight of each edge according to its depth in a spanning tree rooted at the outer vertices, such as a Schnyder wood or BFS tree, in order to pull vertices closer to the boundary.

Keywords

Cite

@article{arxiv.2307.10527,
  title  = {Manipulating Weights to Improve Stress-Graph Drawings of 3-Connected Planar Graphs},
  author = {Alvin Chiu and David Eppstein and Michael T. Goodrich},
  journal= {arXiv preprint arXiv:2307.10527},
  year   = {2023}
}

Comments

Appears in the Proceedings of the 31st International Symposium on Graph Drawing and Network Visualization (GD 2023)