README.md

In eliotmiller/networkTricks: Functions for analyzing social interactions

networkTricks

Code and sample data associated with our paper on dominance hierarchy of North American feeder birds

These functions are introduced in our biorxiv paper. More documentation is included in the help files for the functions. Example data is included with the R package, and the full dataset can be downloaded directly from Project Feederwatch. A few example functions are highlighted below.

How do I get networkTricks?

library(devtools)
install_github("eliotmiller/networkTricks")
library(networkTricks)

Calculate our slightly modified form of Bradley-Terry model dominance coefficients

# first load 1500 lines of sample interaction data from the larger FeederWatch dataset.
data(exInput)

# run the Bradley Terry function. takes a few seconds to run, can run in parallel.
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)]
}

# here are the species' level dominance coefficients
results

Threshold interactions between species

# here's an example of how to threshold a network, e.g. interactions between three species.
three <- c("Red-breasted Nuthatch","Downy Woodpecker","White-breasted Nuthatch")
small <- exInput[exInput$source %in% three & exInput$target %in% three,]

# convert into igraph network
complexNetwork <- igraph::graph.data.frame(small)

# plot to see what it looks like
plot(complexNetwork)

# simplify with a 50% conservative threshold
simpleNetwork <- networkSimplifier(complexNetwork, 0.5, TRUE)

# plot to see what it looks like
plot(simpleNetwork)

Plot an attribute-ordered network sensu Hobson et al. (2015)

# this relies on the results object defined above. first prep the object for plotting
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.