plotAON: Prep data for AON plot

In eliotmiller/networkTricks: Functions for analyzing social interactions

Description

Prepare data for an attribute-ordered network plot.

Usage

plotAON(prepped, dom.color, sub.color, edge.width.scaler, edge.curvature, ...)

Arguments

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.

Details

User should format edge.list so it looks like the example data (exInput).

Value

A list object, prepped for use in plotting an attribute-ordered network.

Author(s)

Elizabeth A. Hobson, https://sites.google.com/site/hobsonresearch/

References

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.

Examples

#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)

eliotmiller/networkTricks documentation built on Oct. 6, 2020, 4:23 p.m.