On 10 May 2004, at 15:45, Jason Turner wrote:
I'm having a hard time figuring out what you want. Who is this mystery object "test"?
Ah - sorry all. That should be:
for(x in ind){
for(y in ind){
result[x,y] <- sum(mylist[[x]][mylist[[x]] %in% mylist[[y]]])
}
}
As a style point, ind <- seq(along=mylist) is a bit more foolproof in the
case of empty lists being accidentally passed to the code (been bitten
that way once or twice).
Yup - thanks for the hint.
Following up on Peter Dalgaard's suggestion, I've tried vectorizing the function properly. Now I get the same answers from both the two for() loops and the vectorized outer() call. What puzzles me slightly is that using outer is about 13 times slower. I realize that
loops aren't always bad but it seems odd that this should be so much slower. Have I got something wrong (the function phylo.overlap probably isn't optimal but this should effect relative timings)?
Thanks, David
myfunc <- function(x,y){mapply function(x,y){phylo.overlap(x,y,parrot.cm)},x,y)}
> system.time(outer.test <- outer(assemblages, assemblages, myfunc))
[1] 62.99 0.25 63.35 0.00 0.00
> x[1:10,1:5]
19916 19917 20275 20992 22787 23008 23009 23145 23146 23147
19916 17466 16443 17397 14368 12687 0 0 8396 9843 12687
19917 16443 17032 16374 14368 12687 0 0 8396 9843 12687
20275 17397 16374 18420 15391 13710 0 0 8396 10866 13710
20992 14368 14368 15391 19735 17812 0 0 10452 14968 17812
22787 12687 12687 13710 17812 19908 0 0 12548 17064 19908
> assemblage.len <- length(assemblages)
> ind <- seq(along=assemblages)
> loop.test <- array(dim=c(assemblage.len,assemblage.len))
>
> system.time(
+ for(x in ind){
+ if(x %% 100 == 0) cat(x,"\n")
+ for(y in ind){
+ loop.test[x,y] <- phylo.overlap(assemblages[[x]], assemblages[[y]], parrot.cm)
+ }
+ }
+ )
[1] 4.34 0.17 4.52 0.00 0.00
> result[1:10,1:5]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 17466 16443 17397 14368 12687 0 0 8396 9843 12687
[2,] 16443 17032 16374 14368 12687 0 0 8396 9843 12687
[3,] 17397 16374 18420 15391 13710 0 0 8396 10866 13710
[4,] 14368 14368 15391 19735 17812 0 0 10452 14968 17812
[5,] 12687 12687 13710 17812 19908 0 0 12548 17064 19908
>
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