# Re: [R] using apply to loop

From: Tyler Smith <tyler.smith_at_mail.mcgill.ca>
Date: Fri, 21 Dec 2007 04:27:31 +0000 (UTC)

On 2007-12-21, Louis Martin <louismartinbis_at_yahoo.fr> wrote:
> Hi,
>
> I am running the following loop, but it takes hours to run as n is big. Is there any way "apply" can be used? Thanks.
> ### Start
> nclass <- dim(data)[[2]] - 1
> z <- matrix(0, ncol = nclass, nrow = nclass)
> n <- dim(data)[[1]]
> x <- c(1:nclass)
> # loop starts
> for(loop in 1:n) { # looping over rows in data
> r <- data[loop, 1:nclass] # vector of length(nclass)
> classified <- x[r == max(r)] # index of rows == max(r)
>
> truth <- data[loop, nclass + 1] # next column, single value
> z[classified, truth] <- z[classified, truth] + 1 # increment
> the values of
> }
> # loop ends
>

Off the top, data is a bad choice for your dataframe, as it conflicts with a standard function. Also, including some actual data would make this easier to work with. I think you're using dim(data)[[1]] to get the number of rows of data? That can be more clearly expressed as nrow(data), and dim(data)[[2]] == ncol(data).

add.mat <- apply(data[,1:nclass], MAR = 1, FUN = function(x)

ifelse(x == max(x), 1, 0))

for(i in 1:n)

z[ , data[i, ncol(data)]] <- z[ , data[i, ncol(data)]] + add.mat[,i]

There's still a loop, but it might not be needed depending on what values 'truth' holds. Most of the calculations are shifted into the apply() call, so the one line loop should run at least a little faster than what you started with.

HTH, Tyler

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