A perhaps faster approach takes advantage of the column major ordering
of arrays and the expand.grid() function. I say "perhaps" faster,
because "apply" family functions are still actually loops at the R
level.
Anyway, try this (using your little example):
## create a data frame (which is also a list) of i,j,k,index combinations:
z <- expand.grid(i=1:2, j= 1:2, k = 1:2)
## Use do.call() to feed the columns of z to mapply
yourarray <- array(do.call(mapply,c(prod,z)),dim=c(2,2,2))
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Feb 1, 2016 at 6:29 AM, Jue Lin-Ye <jl.i...@gmail.com> wrote:
>>
>> Date: Sat, 30 Jan 2016 01:03:30 +0000
>> From: Matteo Richiardi <
>>
>> matteo.richia...@maths.ox.ac.uk>
>> To: r-help@r-project.org
>> Subject: [R] updating elements of a list of matrixes without 'for'
>> cycles
>> Message-ID:
>> <
>> cabsru1lkohuz8m9jw1ju+nemksprirrtd_0wzotrlwi3z6d...@mail.gmail.com>
>> Content-Type: text/plain; charset=UTF-8
>>
>> Hi, following an earlier suggestion from the list, I am storing my
>> data in a "cube", i.e. an array of matrixes.
>> Is there any smarter way of updating the elements of the cube through
>> a function, other than the three 'for' cycles in the example below?
>> (please note that the example is simplistic; in particular, my
>> function is more complicated).
>>
>> # parameters
>> I <- 2L
>> J <- 2L
>> H <- 2L
>>
>> # data container: an array of matrixes
>> mycube <- array(dim=c(I,J,H))
>>
>> # initialisation
>> for (h in 1:H) {
>> init <- matrix(c(rep(0,J)),nrow=I,ncol=J)
>> mycube[,,h] <- init
>> }
>>
>> # function
>> foo = function(i,j,h){
>> mycube[i,j,h] <<- i*j*h
>> }
>>
>> # update
>>
>> for(h in 1:H){
>> # males:
>> for(i in 1:I)
>> for(j in 1:J)
>> foo(i,j,h)
>> }
>>
>> Thanks a lot for your help. Matteo
>>
>>
>>
> Greetings! Have you tried sapply() on this script?
>
> --
> Jue
>
> [[alternative HTML version deleted]]
>
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