> On Dec 8, 2016, at 12:09 PM, John P. Nolan <jpno...@american.edu> wrote:
>
> Dear All,
>
> I regularly want to "apply" some function to an array in a way that the
> arguments to the user function depend on the index on which the apply is
> working. A simple example is:
>
> A <- array( runif(160), dim=c(5,4,8) )
> x <- matrix( runif(32), nrow=4, ncol=8 )
> b <- runif(8)
> f1 <- function( A, x, b ) { sum( A %*% x ) + b }
> result <- rep(0.0,8)
> for (i in 1:8) {
> result[i] <- f1( A[,,i], x[,i] , b[i] )
> }
>
> This works, but is slow. I'd like to be able to do something like:
> generalized.apply( A, MARGIN=3, FUN=f1, list(x=x,MARGIN=2),
> list(b=b,MARGIN=1) ), where the lists tell generalized.apply to pass x[,i]
> and b[i] to FUN in addition to A[,,i].
>
> Does such a generalized.apply already exist somewhere? While I can write a C
> function to do a particular case, it would be nice if there was a fast,
> general way to do this.
I would have thought that this would achieve the same result:
result <- sapply( seq_along(b) , function(i) { f1( A[,,i], x[,i] , b[i] )} )
Or:
result <- sapply( seq.int( dim(A)[3] ) , function(i) { f1( A[,,i], x[,i] , b[i]
)} )
(I doubt it will be any faster, but if 'i' is large, parallelism might help.
The inner function appears to be fairly efficient.)
--
David Winsemius
Alameda, CA, USA
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