# layout_centrality: radial centrality layout In graphlayouts: Additional Layout Algorithms for Network Visualizations

 layout_centrality R Documentation

### Description

arranges nodes in concentric circles according to a centrality index.

### Usage

``````layout_with_centrality(
g,
cent,
scale = TRUE,
iter = 500,
tol = 1e-04,
tseq = seq(0, 1, 0.2)
)

layout_igraph_centrality(
g,
cent,
scale = TRUE,
iter = 500,
tol = 1e-04,
tseq = seq(0, 1, 0.2),
circular
)
``````

### Arguments

 `g` igraph object `cent` centrality scores `scale` logical. should centrality scores be scaled to `[0,100]`? (Default: TRUE) `iter` number of iterations during stress optimization `tol` stopping criterion for stress optimization `tseq` numeric vector. increasing sequence of coefficients to combine regular stress and constraint stress. See details. `circular` not used

### Details

The function optimizes a convex combination of regular stress and a constrained stress function which forces nodes to be arranged on concentric circles. The vector `tseq` is the sequence of parameters used for the convex combination. In iteration i of the algorithm `tseq[i]` is used to combine regular and constraint stress as `(1-tseq[i])*stress_{regular}+tseq[i]*stress_{constraint}`. The sequence must be increasing, start at zero and end at one. The default setting should be a good choice for most graphs.

The layout_igraph_* function should not be used directly. It is only used as an argument for plotting with 'igraph'. 'ggraph' natively supports the layout.

### Value

matrix of xy coordinates

### References

Brandes, U., & Pich, C. (2011). More flexible radial layout. Journal of Graph Algorithms and Applications, 15(1), 157-173.

layout_centrality_group

### Examples

``````library(igraph)
library(ggraph)

g <- sample_gnp(10, 0.4)
## Not run:
ggraph(g, layout = "centrality", centrality = closeness(g)) +
draw_circle(use = "cent") +