Description Usage Arguments Details Value Author(s) References Examples
Prepare data for an attribute-ordered network plot.
1 |
prepped |
The prepped element from the prepAON object. See example. |
dom.color |
Color to draw edges connecting dominant to subordinate nodes. Can take various forms, e.g. hexadecimal code or the name of the color. |
sub.color |
Color to draw edges connecting subordinate to dominant nodes. |
edge.width.scaler |
Varies the edge width connecting nodes. Functions as a scaler, not an absolute. In other words, rarely observed interactions should be plotted no matter what, but frequently observed interactions will be plotted less thickly. Larger values of this scaler more heavily 'thin' frequently observed interactions. |
edge.curvature |
Set to TRUE to use default degree of curvature in lines. Set to a numeric value to more carefully fine tune the degree of curvature. See example. Can set to FALSE, but resulting plot unlikely to be useful. |
... |
Other arguments can be passed to plot.igraph here, which should theoretically encompass all options available to igraph.plotting. |
User should format edge.list so it looks like the example data (exInput).
A list object, prepped for use in plotting an attribute-ordered network.
Elizabeth A. Hobson, https://sites.google.com/site/hobsonresearch/
Hobson, E. A., D. J. John, T. L. Mcintosh, M. L. Avery, and T. F. Wright. 2015. The effect of social context and social scale on the perception of relationships in monk parakeets. Current Zoology 61:55-69.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | #load in the example data
data(exInput)
#run the Bradley Terry function. takes a few seconds to run.
results <- myBTM(edge.list=exInput, cores=2)
#the names of these scores have weird periods in them. use agrep to solve
species <- unique(c(as.character(exInput$source), as.character(exInput$target)))
names(results) <- sub("..", "", x=names(results))
for(i in 1:length(results))
{
names(results)[i] <- species[agrep(names(results)[i], species, max.distance=0.1)]
}
prepped <- prepAON(results, exInput)
plotAON(prepped$prepped, dom.color="#00009985", sub.color="#CC000095", xlim=c(-1,-0.8),
vertex.size=0.1, vertex.color=NA, vertex.frame.color=NA, vertex.label.color="black",
vertex.label.cex=0.28, vertex.color="white", vertex.label.family="sans",
edge.width.scaler=10, edge.arrow.size=0, edge.curvature=TRUE)
#easy to modify things such as edge width, color, and how much they curve
plotAON(prepped$prepped, dom.color="#5ab4ac", sub.color="#d8b365", xlim=c(-1,-0.8),
vertex.size=0.1, vertex.color=NA, vertex.frame.color=NA, vertex.label.color="black",
vertex.label.cex=0.28, vertex.color="white", vertex.label.family="sans",
edge.width.scaler=6, edge.arrow.size=0, edge.curvature=2)
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