# A which for multidimensional arrays.
# Mark van der Loo 16.09.2011
#
# A Array of booleans
# returns a sum(A) x length(dim(A)) array of multi-indices where A == TRUE
#
multi.which <- function(A){
if ( is.vector(A) ) return(which(A))
d <- dim(A)
T <- which(A) - 1
nd <- length(d)
t( sapply(T, function(t){
I <- integer(nd)
I[1] <- t %% d[1]
sapply(2:nd, function(j){
I[j] <<- (t %/% prod(d[1:(j-1)])) %% d[j]
})
I
}) + 1 )
}
Created by Pretty R at inside-R.org
For example. Let's create a 2x3x2 logical array (2 rows, three columns, and this structure times 2):Created by Pretty R at inside-R.org
The standard which function gives 1-dimensional indices:> which(B)
[1] 1 2 5 10 11 12
Created by Pretty R at inside-R.org
If you don't need to see the result, this is fine. However, sometimes it is convenient to have the multi-index available. For example, the element in the first row of the first column of the first matrix of B equals TRUE. That is, element (1,1,1). The multi.which function returns all multi-indices where coefficients are TRUE:> multi.which(B)
[,1] [,2] [,3]
[1,] 1 1 1
[2,] 2 1 1
[3,] 1 3 1
[4,] 2 2 2
[5,] 1 3 2
[6,] 2 3 2
Created by Pretty R at inside-R.org
The result is a 2-dimensional array, where each row is a single multi-index. You can check the last row by confirming that the second row of the third column of the second matrix indeed has coefficient TRUE. As noted, the function works for any multidimensional array (including vectors and matrices).So, how does it all work? I will just give the basic equation here, but see this paper for a more thorough description and the inverse relation. Basically, you can regard the multi-index as a positional number system, with the first index running fastest. (Remember, that our decimal notation system is a positional system, but with the first number running slowest).
Denote the single index in a d1 x d2 x ... x dn - dimensional array with t. The multi-index I may be written as
I(t) = (i1,i2,...,in )
where
ij=(t div Πk=1j-1dk) mod dj,
and the product equals 1 if j=1. The symbols div and mod stand for integer division and remainder upon division. This equation assumes base 0 indexing, meaning that both the single and multi-indexing start at 0. Since R uses base 1 indexing, the first and 11th line in multi.which first subtract, then add one to correct for this.
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