[R] Memory problems...leaky?

[Sam Yeaman]

Hi list folks,

I have been trying to figure out how I can run the script that I have 
included below. I have 1.2 gigs of memory on the computer, but this is 
not enough, given the size of the input datasets. The input matrix 
('input') is a little under 2400 x 2900 cells, and is about 60 megs when 
stored on hard drive...what is R doing, that this (small) size of file 
takes up so much memory? The script uses three variables of this size, 
but  I don't see why that would add up to over 1.2 gigs...Is the way 
that I call variables in the for-loops causing this problem, with some 
sort of leakiness? I had heard of leaky memory problems with version 
1.5.1, but I am using 1.9.1. Alternatively, I had wondered if it was 
just the way memory works in R, as I had read a post earlier today that 
suggested that R requires 5-10 times more memory than the input to 
meaninfully calculate anything...

Thanks...Sam



bflow <- 2
pie <- 3.141592654


input <-  read.table ("xxx.txt", sep="", header=FALSE, na.strings = "-9999")
rowsize <- dim(input)[1]
colsize <- dim(input)[2]

result <- matrix (NA, rowsize, colsize)

for (i in 1:rowsize)
for (j in 1:colsize)

    if (is.na (input [i,j]) == FALSE) {

        probability <- matrix (NA, rowsize, colsize)

        for (p in 1:rowsize) {
            or (q in 1:colsize){
            distance <- sqrt ((p - i)^2 + (q - j)^2)
            probability [p,q] <- (2 / (bflow * pie * (1 + (distance / 
bflow)^2)))   
            }   
        }
 
        kernsum <- sum ((probability * input / input), na = 
TRUE)                                               
        intmean <- sum (input * probability, na = TRUE) / 
kernsum                               
        result [i,j] <- sum (((input - intmean)^2 * probability), na = 
TRUE) / kernsum
    }

}
}