layout_with_drl: The DrL graph layout generator
In igraph: Network Analysis and Visualization

layout_with_drl

R Documentation

The DrL graph layout generator

Description

DrL is a force-directed graph layout toolbox focused on real-world large-scale graphs, developed by Shawn Martin and colleagues at Sandia National Laboratories.

Usage

layout_with_drl(
  graph,
  use.seed = FALSE,
  seed = matrix(runif(vcount(graph) * 2), ncol = 2),
  options = drl_defaults$default,
  weights = NULL,
  dim = 2
)

with_drl(...)

Arguments

`graph`	The input graph, in can be directed or undirected.
`use.seed`	Logical scalar, whether to use the coordinates given in the `seed` argument as a starting point.
`seed`	A matrix with two columns, the starting coordinates for the vertices is `use.seed` is `TRUE`. It is ignored otherwise.
`options`	Options for the layout generator, a named list. See details below.
`weights`	The weights of the edges. It must be a positive numeric vector, `NULL` or `NA`. If it is `NULL` and the input graph has a ‘weight’ edge attribute, then that attribute will be used. If `NULL` and no such attribute is present, then the edges will have equal weights. Set this to `NA` if the graph was a ‘weight’ edge attribute, but you don't want to use it for the layout. Larger edge weights correspond to stronger connections.
`dim`	Either ‘2’ or ‘3’, it specifies whether we want a two dimensional or a three dimensional layout. Note that because of the nature of the DrL algorithm, the three dimensional layout takes significantly longer to compute.
`...`	Passed to `layout_with_drl()`.

Details

This function implements the force-directed DrL layout generator.

The generator has the following parameters:

edge.cut: Edge cutting is done in the late stages of the algorithm in order to achieve less dense layouts. Edges are cut if there is a lot of stress on them (a large value in the objective function sum). The edge cutting parameter is a value between 0 and 1 with 0 representing no edge cutting and 1 representing maximal edge cutting.
init.iterations: Number of iterations in the first phase.
init.temperature: Start temperature, first phase.
init.attraction: Attraction, first phase.
init.damping.mult: Damping, first phase.
liquid.iterations: Number of iterations, liquid phase.
liquid.temperature: Start temperature, liquid phase.
liquid.attraction: Attraction, liquid phase.
liquid.damping.mult: Damping, liquid phase.
expansion.iterations: Number of iterations, expansion phase.
expansion.temperature: Start temperature, expansion phase.
expansion.attraction: Attraction, expansion phase.
expansion.damping.mult: Damping, expansion phase.
cooldown.iterations: Number of iterations, cooldown phase.
cooldown.temperature: Start temperature, cooldown phase.
cooldown.attraction: Attraction, cooldown phase.
cooldown.damping.mult: Damping, cooldown phase.
crunch.iterations: Number of iterations, crunch phase.
crunch.temperature: Start temperature, crunch phase.
crunch.attraction: Attraction, crunch phase.
crunch.damping.mult: Damping, crunch phase.
simmer.iterations: Number of iterations, simmer phase.
simmer.temperature: Start temperature, simmer phase.
simmer.attraction: Attraction, simmer phase.
simmer.damping.mult: Damping, simmer phase.

There are five pre-defined parameter settings as well, these are called drl_defaults$default, drl_defaults$coarsen, drl_defaults$coarsest, drl_defaults$refine and drl_defaults$final.

Value

A numeric matrix with two columns.

Author(s)

Shawn Martin (http://www.cs.otago.ac.nz/homepages/smartin/) and Gabor Csardi csardi.gabor@gmail.com for the R/igraph interface and the three dimensional version.

References

See the following technical report: Martin, S., Brown, W.M., Klavans, R., Boyack, K.W., DrL: Distributed Recursive (Graph) Layout. SAND Reports, 2008. 2936: p. 1-10.

Examples


g <- as_undirected(sample_pa(100, m = 1))
l <- layout_with_drl(g, options = list(simmer.attraction = 0))
plot(g, layout = l, vertex.size = 3, vertex.label = NA)

igraph documentation built on Oct. 20, 2024, 1:06 a.m.