# [Rd] wish list: generalized apply

David Winsemius dwinsemius at comcast.net
Thu Dec 8 22:59:20 CET 2016

```> On Dec 8, 2016, at 12:09 PM, John P. Nolan <jpnolan at 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) ) , 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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