Re: [igraph] Random Walk Sample

[Tamás Nepusz]

Hi Thomas,

1) instead of length(degree(g)), just use vcount(g)

2) neighbors(g, node1) can be queried outside the interval while() loop and 
then stored in a temporary variable because it won't change during the lifetime 
of the inner loop

3) if you are sampling from the range 1:n, use sample.int() instead of sample()

4) instead of rbinom(1, 1, p), use runif(1)<p -- it is probably faster

I think this should make things faster -- let me know if it is still too slow.

-- 
T.


On 24 Oct 2013, at 15:10, Thomas <address@hidden> wrote:

> I'm creating a sample of nodes according to the random walk procedure 
> described in Section 3.3.3 of:
> 
> http://www.stat.cmu.edu/~fienberg/Stat36-835/Leskovec-sampling-kdd06.pdf
> 
> The following R code samples no less than 300 nodes, although it might sample 
> the same node twice but it runs really slowly. Does anyone know why it might 
> be going so slow? Is there any better way to do this?
> 
> Thank you,
> 
> Thomas
> 
> #Random Walk Sample of nodes from network g
> #Read graph g in as UNDIRECTED
> 
> A <- sample(1:length(degree(g)), 1)
> oput <- c()
> oput <- c(oput, A)
> flag <- FALSE
> count <- 1
> 
> while(count <= 300)
> {
> node1 <- A
> while(flag==FALSE)
> {
> node2 <- sample(neighbors(g,node1),1)
> oput <- c(oput, node2)
> count <- count + 1
> node1 <- node2
> if(rbinom(1,1,0.15)==1){flag=TRUE}
> }#end of while flag loop
> }#end of while count loop
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