there are two main ideas to improve the efficiency:
1. the comparison with the limit can be done at first
2. a matrix with boxsize*boxsize rows can be defined so that
you can apply function "apply" without using inner loops
<<*>>=
# parameters
size<-1024; limit<-0.7
# some data
set.seed(17); data<-runif(size^2)
m<-matrix(data,size,size)
bcount.vec<-NULL
m<-m>limit
for (boxsize in 2^(1:8)) {
# inner loop:
m<-array(m,c(boxsize,size/boxsize,size))
m<-aperm(m,c(1,3,2))
m<-matrix(m,nrow=boxsize*boxsize)
bcount.vec<-c(bcount.vec,sum(apply(m,2,max)))
}
bcount<-sum(bcount.vec)
print(bcount.vec)
print(bcount)
@
output-start
[1] 199099 65306 16384 4096 1024 256 64 16
[1] 286245
output-end
Some remarks on your code:
The first expression in your outer loop is setting bcount to 0.
In the inner loops bcount is incremented.
But the outer loop sets bcount to the value 0 again!?
What do you want to count?
Peter
Rajarshi Guha wrote:
Hi,
I have a matrix of say 1024x1024 and I want to look at it in chunks.
That is I'd like to divide into a series of submatrices of order 2x2.
| 1 2 3 4 5 6 7 8 ... |
| 1 2 3 4 5 6 7 8 ... |
| 1 2 3 4 5 6 7 8 ... |
| 1 2 3 4 5 6 7 8 ... |
...
So the first submatrix would be
| 1 2 |
| 1 2 |
the second one would be
| 3 4 |
| 3 4 |
and so on. That is I want the matrix to be evenly divided into 2x2
submatrices. Now I'm also doing this subdivision into 4x4, 8x8 ...
256x256 submatrices.
Currently I'm using loops and I'm sure there is a mroe efficient way to
do it:
m <- matrix(runif(1024*1024), nrow=1024)
boxsize <- 2^(1:8)
for (b in boxsize) {
bcount <- 0
bstart <- seq(1,1024, by=b)
for (x in bstart) {
for (y in bstart) {
xend <- x + b - 1
yend <- y + b - 1
if (length(which( m[ x:xend, y:yend ] > 0.7)) > 0) {
bcount <- bcount + 1
}
}
}
}
Is there any way to vectorize the two inner loops?
Thanks,
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