Authors: yunhai wang, Yanyan Wang, Yingqi Sun, Lifeng Zhu, Chi-Wing Fu, Michael Sedlmair, Oliver Deussen, Baoquan Chen, Kecheng Lu
Abstract: We present an improved stress majorization method that incorporates various constraints including directional constraints \ without the necessity of solving a constraint optimization problem. This is achieved by reformulating the stress function to impose \ constraints on both the edge vectors and lengths instead of just on the edge lengths (node distances). This is a unified framework for \ both constrained and unconstrained graph visualizations, where we can model most existing layout constraints, as well as develop \ new ones such as the star shapes and cluster separation constraints within stress majorization. This improvement also allows us to \ parallelize the computation with an efficient GPU conjugant gradient solver, which yields fast and stable solutions, even for large graphs. \ As a result, we can support constraint based exploration of large graphs with 10K nodes, to which previous methods cannot support.