Nothing
`symmetrise_w` <-
function(net,method="MAX"){
# Ensure that the network conforms to the tnet standard
if (is.null(attributes(net)$tnet)) net <- as.tnet(net, type = "weighted one-mode tnet")
if (attributes(net)$tnet != "weighted one-mode tnet") stop("Network not loaded properly")
# Join the net with it's reversed version
net <- rbind(net, cbind(i=net[,"j"], j=net[,"i"], w=0))
# Remove exact duplicates (i=i & j=j)
net <- net[!duplicated(net[,c("i","j")]),]
# Change ties so that i<j
net[net[,"i"]>net[,"j"],c("i","j")] <- net[net[,"i"]>net[,"j"],c("j","i")];
# Order ties (the greatest weight first)
net <- net[order(net[,"i"],net[,"j"], -net[,"w"]),]
# Create an index
dup <- cumsum(rep.int(c(1,0), nrow(net)/2))
# Create a weight vector
w <- switch(method,
MAX = net[rep(c(TRUE,FALSE), length=nrow(net)),"w"],
MIN = net[rep(c(FALSE,TRUE), length=nrow(net)),"w"],
AMEAN = tapply(net[,"w"], dup, mean),
SUM = tapply(net[,"w"], dup, sum),
GMEAN = tapply(net[,"w"], dup, function(a) sqrt(a[1]*a[2])),
PROD = tapply(net[,"w"], dup, function(a) a[1]*a[2]),
DIFF = tapply(net[,"w"], dup, function(a) abs(a[1]-a[2])))
# Extract only one entry per undirected tie
net <- net[rep(c(TRUE,FALSE), length=nrow(net)),]
# Add the weight vector to this list
net[,"w"] <- w;
# Only keep ties with a positive weight
net <- net[net[,3]>0,]
# Join this net with its reversed version
net <- rbind(cbind(net[,1],net[,2],net[,3]), cbind(net[,2],net[,1],net[,3]))
# Assign names to columns
dimnames(net)[[2]]<-c("i","j","w")
# Order net
net <- net[order(net[,"i"],net[,"j"]),]
row.names(net)<-NULL
return(net)
}
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