First measure what exactly is slow with Rprof().

Gabor


On Wed, Feb 26, 2014 at 9:41 PM, [email protected] <[email protected]>wrote:

>   Hi!
>
> Iam trying to find the maximum out-component in a erdos-renyi random graph.
>
> Using the array GSCCnod to record the vertices in the maximum strongly
> connected component,
> Goutnod to record that if a vertice is in the maximum out-component:
> Goutnod[i]==-1 means that vertice i is not in the maximum out-component
> and Goutnod[i]==1 means that vertice i is in the maximum out-component.
>
> But the graph contains too many vertices. It takes too much time to
> compute Goutnod. How can I make it faster.
>
> Here is the source code:
>
> ER2 <- erdos.renyi.game(100000, 200000, "gnm", TRUE)
>
> SGer2_CluMem=clusters(ER2, "strong")$membership
> SGer2_CluSiz=clusters(ER2, "strong")$csize
> SGer2_CluNum=clusters(ER2, "strong")$no
>
> Nummax <-0
> for (i in 1:SGer2_CluNum)
> {
>     if (SGer2_CluSiz[i] > Nummax)
>     {
>          Nummax <- SGer2_CluSiz[i]
>          Maxmem <- i
>      }
> }
>
> GSCCnod <- rep(0, Nummax)
> j <- 1
> for (i in 1:100000)
> {
>     if (SGer2_CluMem[i] == Maxmem)
>     {
>          GSCCnod[j] <- i
>          j <- j + 1
>      }
> }
>
> Goutnod <- rep(-1,100000)
> for (i in 1:Nummax)
> {
>       gout <- subcomponent(ER2, GSCCnod[i], "out")
>       len <- length(gout)
>       for (k in 1: len)
>            Goutnod[gout[k]] <- 1
> }
>
>
> Thank you
> Best
> Xueming
> ------------------------------
>  [email protected]
>
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>
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