avoiding loops
Ingmar Visser asks:
Thanks for this. I was afraid someone was going to say this ... Does this mean the only way of getting this to run faster is by moving to C code?
Perhaps, but that's not all that difficult for this kind of operation, surely? Even portability across platforms should be pretty manageable.
The cases I'm thinking of applying this in have dimensions of A that are much larger than the example, eg n by n by T where n has a max of 10 or so but T could
be hundreds or even thousands.
What I would try first, then is a loop which makes maximum use of
vectorisation. In this case it would be two loops, of course:
d <- dim(A)
for(i in 1:d[1])
for(j in 1:d[2])
A[i,j,] <- A[i,j,] * B
But the following non-loop solution might be your best option:
A <- aperm(aperm(A, c(3,1,2)) * as.vector(B), c(2,3,1))
If you can get your head around working with an A array where what is
now the third dimension becomes the first, then you can eliminate the
aperm()s and it becomes about as fast as C code (which it is, in
effect). Permuting large arrays can be heavy on memory usage.
Bill Venables.
Best, Ingmar On Mar 27, 2008, at 12:11 AM, <Bill.Venables at csiro.au> <Bill.Venables at csiro.au> wrote:
If you have lots of memory there is an obvious strategy: d12 <- prod(dim(A)[1:2]) A <- A * array(rep(B, each = d12), dim = dim(A)) I don't really see much wrong with the obvious for() loop, though: for(b in 1:length(B)) A[,,b] <- A[,,b] * B[b] Bill Venables CSIRO Laboratories PO Box 120, Cleveland, 4163 AUSTRALIA Office Phone (email preferred): +61 7 3826 7251 Fax (if absolutely necessary): +61 7 3826 7304 Mobile: +61 4 8819 4402 Home Phone: +61 7 3286 7700 mailto:Bill.Venables at csiro.au http://www.cmis.csiro.au/bill.venables/ -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- project.org] On Behalf Of Ingmar Visser Sent: Thursday, 27 March 2008 7:58 AM To: R-help at r-project.org Subject: [R] avoiding loops Hi, I need to compute an array from a matrix and an array: A <- array(1:20,c(2,2,5)) B <- matrix(1:10,5) And I would like the result to be an array consisting of the following: rbind(A[1,,1]*B[1,], A[2,,1]*B[1,]) rbind(A[1,,2]*B[2,], A[2,,2]*B[2,]) rbind(A[1,,3]*B[2,], A[2,,3]*B[2,]) etc. Hence the result should have the same dimension as A, ie a series of 2 by 2 matrices. Short of a for loop over the the last index of A I have struggled with versions of apply but to no avail ... Any insights much appreciated, Best, Ingmar
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