On 1/25/2013 2:29 PM, emorway wrote:
I played around with your example on the smaller dataset, and it seemed like
it was doing what I wanted. However, applying it to the larger problem, I
didn't get a resized 2D dataset that preserved the order I was hoping for.
Hopefully the following illustrates the larger problem:
x<-matrix(0,nrow=29328,ncol=7)
# Now set the 70,000th element to 1 to find out where it ends up?
# Iterating on columns first, then rows, the 70,000th element is
# at index [10000,7]
x[10000,7]<-1
y<-t(matrix(x,nrow=546))
dim(y)
# [1] 376 546
# Does 1 appear at index [129,112] as I expect
# (128 complete rows x 546 cols = 69888 + 112 = 70,000) thus, row 129, col
112
y[129,112]
# [1] 0
# No, so where is it?
grep(1,y)
# [1] 123293
Where is that?
which(y==1, arr.ind=TRUE)
# row col
# [1,] 341 328
You need an extra transposition
y <- t(matrix(t(x), nrow=546))
y[129,112]
# [1] 1
which(y==1, arr.ind=TRUE)
# row col
# [1,] 129 112
--
Brian S. Diggs, PhD
Senior Research Associate, Department of Surgery
Oregon Health & Science University
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