This layout is related to the stress-minimization algorithm known as Kamada-Kawai (available as the 'kk' layout), but uses another optimization strategy. It generally have better runtime, quality, and stability compared to the Kamada-Kawai layout and is thus generally preferred. The sparse version of the layout have better performance (especially on larger networks) at the expense of layout quality, but will generally outperform many other algorithms for large graphs in both runtime and quality (e.g. the 'drl' layout from igraph).
layout_tbl_graph_stress( graph, weights = NULL, niter = 500, tolerance = 1e-04, mds = TRUE, bbox = 50, circular = FALSE ) layout_tbl_graph_sparse_stress( graph, pivots, weights = NULL, niter = 500, circular = FALSE )
a tbl_graph object
An expression evaluated on the edge data to provide edge weights for the layout. Currently ignored for the sparse version
number of iterations during stress optimization
stopping criterion for stress optimization
should an MDS layout be used as initial layout (default: TRUE)
constrain dimension of output. Only relevant to determine the placement of disconnected graphs.
The number of pivot nodes.
A data.frame with the columns
well as any information stored as node variables in the tbl_graph object.
Gansner, E. R., Koren, Y., & North, S. (2004). Graph drawing by stress majorization. In International Symposium on Graph Drawing (pp. 239-250). Springer, Berlin, Heidelberg.
Ortmann, M. and Klimenta, M. and Brandes, U. (2016). A Sparse Stress Model. https://arxiv.org/pdf/1608.08909.pdf