Generate igraph objects from measured turtles and links metrics

Generate igraph objects from measured turtles and links metrics

Usage

nl_to_graph(nl)

Arguments

nl

nl object

Generate igraph objects from measured turtles and links metrics. Output has to be attached to the simdesign first with simoutput(nl) <- results I graph objects are created automatically for each combination of random-seed, siminputrow and step. An additional column with igraph objects is attached to the original output results tibble of the nl object. In order to generate igraph objects some metrics are mandatory: The metrics.turtles slot of the experiment must contain "who" numbers (see example experiment). Additional turtle metrics will be stored as properties of the igraph vertices. The metrics.links slot of the experiment must contain "who" numbers of link end1 and end2 (see example experiment). Additional link metrics will be stored as properties of the igraph edges.

Examples

if (FALSE) {
## Example running the Giant Component model from the NetLogo models library:
library(nlrx)
library(igraph)
# Windows default NetLogo installation path (adjust to your needs!):
netlogopath <- file.path("C:/Program Files/NetLogo 6.0.4")
modelpath <- file.path(netlogopath, "app/models/Sample Models/Networks/Giant Component.nlogo")
outpath <- file.path("C:/out")
# Unix default NetLogo installation path (adjust to your needs!):
netlogopath <- file.path("/home/NetLogo 6.0.4")
modelpath <- file.path(netlogopath, "app/models/Sample Models/Networks/Giant Component.nlogo")
outpath <- file.path("/home/out")

nl <- nl(nlversion = "6.0.4",
         nlpath = netlogopath,
         modelpath = modelpath,
         jvmmem = 1024)

nl@experiment <- experiment(expname="networks",
                            outpath=outpath,
                            repetition=1,
                            tickmetrics="false",
                            idsetup="setup",
                            idgo="go",
                            runtime=50,
                            metrics.turtles = list("turtles" = c("who", "color")),
                            metrics.links = list("links" = c("[who] of end1", "[who] of end2")),
                            constants = list("num-nodes" = 80,
                                             "layout?" = "true"))

nl@simdesign <- simdesign_simple(nl, 1)
nl@simdesign@simoutput <- run_nl_all(nl)
nl.graph <- nl_to_graph(nl)

## Extract graph of tick 1:
nl.graph.i <- nl.graph$spatial.links[[1]]
## Set vertex colors by measured color variable:
vcols <- c("7" = "grey", "15" = "red")
V(nl.graph.i)$color <- vcols[as.character(V(nl.graph.i)$color)]
## Set edge colors by measured link breed:
ecols <- c("links" = "black")
E(nl.graph.i)$color <- ecols[E(nl.graph.i)$breed]

## Plot:
plot.igraph(nl.graph.i, vertex.size=8, vertex.label=NA, edge.arrow.size=0.2)

}