[R] Speeding up "accumulation" code in large matrix calc?

[robertfeldt]

Hi,

I have R code like so:

num.columns.back.since.last.occurence <- function(m, outcome) {
	nrows <- dim(m)[1];
	ncols <- dim(m)[2];
	res <- matrix(rep.int(0, nrows*ncols), nrow=nrows);
	for(row in 1:nrows) {
		for(col in 2:ncols) {
			res[row,col] <- if(m[row,col-1]==outcome) {0} else {1+res[row,col-1]}
		}
	}
	res;
}

but on the very large matrices I apply this the execution times are a
problem. I would appreciate any help to rewrite this with more
"standard"/native R functions to speed things up.

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