Re: [igraph] efficiency in reading a CSV file

[Tamas Nepusz]

> Disclaimer: I'm not a proficient programmer.
Disclaimer: neither am I and I don't even use R frequently, so there might be a 
better solution than the ones I propose here. :)

> for (aut in auts) {
>   if (!(aut %in% vertices)) vertices <- c(vertices,aut)
> }
As I can see, you can avoid having to use a for loop here if you write 
something like this:

vertices <- c(vertices, aut[!aut %in% vertices])

> if (length(auts)>1) {
>   collpairs <- combn(auts,2)
>   for (i in 1:length(collpairs[1,])) {
>     collpair <- sort(collpairs[,i])
>     if (!(list(collpair)%in%edges)) edges <- c(edges,list(collpair))
>   }
> }
Here I wouldn't waste time by calling sort() on each column of collpairs; I 
would simply write this:

edges <- c(edges, combn(auts, 2))

This would obviously create multiple edges in your network, but you can simply 
get rid of them by calling igraph::simplify() on the graph, which should be 
faster than the trickery with the for loops.

-- 
Tamas