Nothing
`degree_w` <-
function(net, measure = c("degree", "output"), type = "out", alpha=1){
# 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")
# Reverse data if calculating in-degrees
if(type == "in") {
net <- data.frame(i=net[,2], j=net[,1], w=net[,3])
net <- net[order(net[,"i"],net[,"j"]),]
}
# Create an index for each node
index <- cumsum(!duplicated(net[,1]))
# Create output object
k.list <- cbind(unique(net[,1]), NaN, NaN, NaN)
# Assign names
dimnames(k.list)[[2]] <- c("node", "degree", "output","alpha")
# Calculating degree
if(sum(c("degree","alpha") %in% measure)>0)
k.list[,"degree"] <- tapply(net[, "w"], index, length)
# Calculating strength
if(sum(c("output","alpha") %in% measure)>0)
k.list[,"output"] <- tapply(net[, "w"], index, sum)
# Calculating alpha parameter
if("alpha" %in% measure)
k.list[,"alpha"] <- k.list[,"degree"]*((k.list[,"output"]/k.list[,"degree"])^alpha)
# Add rows to the output object if isolates exists
if(max(net[,c("i", "j")]) != nrow(k.list)) {
k.list <- rbind(k.list, cbind(1:max(net[, c("i", "j")]), 0, 0, 0))
k.list <- k.list[order(k.list[, "node"]), ]
k.list <- k.list[!duplicated(k.list[, "node"]), ]
}
# Extract just relevant columns, and return
return(k.list[,c("node", measure)])
}
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