How do I calculate weighted degree distributions with igraph in R?

Question

Consider a dataframe df where the first two columns are node pairs and successive columns V1 , V2 , ..., Vn represent flows between the nodes (potentially 0, implying no edge for that column's network). I would like to conduct analysis on degree, community detection, and other network measures using the flows as weights.

Then to analyze the graph with respect to the weights in V1 I do:

# create graph and explore unweighted degrees with respect to V1
g <- graph.data.frame( df[df$V1!=0,] )
qplot(degree(g))
x <- 0:max(degree(g))
qplot(x,degree.distribution(g))

# set weights and explore weighted degrees using V1
E(g)$weights <- E(g)$V1
qplot(degree(g))

The output from the third qplot is no different than the first. What am I doing wrong?

Update:

So graph.strength is what I am looking for, but graph.strength(g) in my case gives standard degree output followed by:

Warning message:
In graph.strength(g) :
At structural_properties.c:4928 :No edge weights for strength calculation,
normal degree

I must be setting the weights incorrectly, is it not sufficient to do E(g)$weights <- E(g)$V1 and why can g$weights differ from E(g)$weights ?

Answer 1

The function graph.strength can be given a weights vector with the weights argument. I think what is going wrong in your code is that you should call the weights attribute E(g)$weight not E(g)$weights .

Answer 2

I created an equivalent degree.distribution function for weighted graphs for my own code by taking the degree.distribution code and making one change:

graph.strength.distribution <- function (graph, cumulative = FALSE, ...)
{
  if (!is.igraph(graph)) {
    stop("Not a graph object")
  }
  # graph.strength() instead of degree()
  cs <- graph.strength(graph, ...)
  hi <- hist(cs, -1:max(cs), plot = FALSE)$density
  if (!cumulative) {
    res <- hi
  }
  else {
    res <- rev(cumsum(rev(hi)))
  }
  res
}