This should be faster. It uses apply() across the blocks.
> ilon <- seq(1,8,nx)
> ilat <- seq(1,4,ny)
> cells <- as.matrix(expand.grid(ilat, ilon))
> blocks <- apply(cells, 1, function(x) tst[x[1]:(x[1]+1), x[2]:(x[2]+1)])
> block.means <- colMeans(blocks)
> tst_2x2 <- matrix(block.means, 2, 4)
> tst_2x2
[,1] [,2] [,3] [,4]
[1,] 3.5 11.5 19.5 27.5
[2,] 5.5 13.5 21.5 29.5
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: R-help [mailto:r-help-boun...@r-poject.org] On Behalf Of Anthoni, Peter
(IMK)
Sent: Wednesday, July 27, 2016 6:14 AM
To: r-help@r-project.org
Subject: [R] Aggregate matrix in a 2 by 2 manor
Hi all,
I need to aggregate some matrix data (1440x720) to a lower dimension (720x360)
for lots of years and variables
I can do double for loop, but that will be slow. Anybody know a quicker way?
here an example with a smaller matrix size:
tst=matrix(1:(8*4),ncol=8,nrow=4)
tst_2x2=matrix(NA,ncol=4,nrow=2)
nx=2
ny=2
for(ilon in seq(1,8,nx)) {
for (ilat in seq(1,4,ny)) {
ilon_2x2=1+(ilon-1)/nx
ilat_2x2=1+(ilat-1)/ny
tst_2x2[ilat_2x2,ilon_2x2] = mean(tst[ilat+0:1,ilon+0:1])
}
}
tst
tst_2x2
> tst
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 1 5 9 13 17 21 25 29
[2,] 2 6 10 14 18 22 26 30
[3,] 3 7 11 15 19 23 27 31
[4,] 4 8 12 16 20 24 28 32
> tst_2x2
[,1] [,2] [,3] [,4]
[1,] 3.5 11.5 19.5 27.5
[2,] 5.5 13.5 21.5 29.5
I though a cast to 3d-array might do the trick and apply over the new
dimension, but that does not work, since it casts the data along the row.
> matrix(apply(array(tst,dim=c(nx,ny,8)),3,mean),nrow=nrow(tst)/ny)
[,1] [,2] [,3] [,4]
[1,] 2.5 10.5 18.5 26.5
[2,] 6.5 14.5 22.5 30.5
cheers
Peter
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
