Hi,
Byron Ellis wrote:
> IIRC a for loop has more per-iteration overhead that lapply, but the
> real answer is "it depends on what you're doing exactly." I've seen it
> be a faster, slower and equal approach.
gen.iter = function(y=NA) {
function(x) {
y <<- if(is.na(y)) x else x+y
}
}
sapply + gen.iter is slithly faster on small vectors:
> x <- rep(1, 5000)
> system.time(tt <- sapply(x,gen.iter()))
user system elapsed
0.012 0.000 0.012
> x <- rep(1, 5000)
> system.time(tt <- for(i in 2:length(x)) {x[i] <- x[i-1]+x[i]})
user system elapsed
0.016 0.000 0.016
but much slower on big vectors:
> x <- rep(1, 10000000)
> system.time(tt <- sapply(x,gen.iter()))
user system elapsed
138.589 0.964 139.633
> x <- rep(1, 10000000)
> system.time(tt <- for(i in 2:length(x)) {x[i] <- x[i-1]+x[i]})
user system elapsed
29.978 0.480 30.454
Cheers,
H.
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