Reputation: 472
Consider the code:
a=runif(1000)
microbenchmark::microbenchmark(order(a,method="radix"))
microbenchmark::microbenchmark(sort.list(a,method="radix"))
Running this code I see better performance of order()
compared to sort.list()
. On the other hand, if I use a sample size of 100000 the performance of both functions is nearly the same.
Why does it happen?
Upvotes: 0
Views: 298
Reputation: 3888
Take a look at the function sort.list()
, it calls order()
ie. they will be the same when this part amounts to the time-intensive part (large vector):
> base::sort.list
function (x, partial = NULL, na.last = TRUE, decreasing = FALSE,
method = c("shell", "quick", "radix"))
{
if (is.integer(x) || is.factor(x))
method <- "radix"
method <- match.arg(method)
if (!is.atomic(x))
stop("'x' must be atomic for 'sort.list'\nHave you called 'sort' on a list?")
if (!is.null(partial))
.NotYetUsed("partial != NULL")
if (method == "quick") {
if (is.factor(x))
x <- as.integer(x)
if (is.numeric(x))
return(sort(x, na.last = na.last, decreasing = decreasing,
method = "quick", index.return = TRUE)$ix)
else stop("method = \"quick\" is only for numeric 'x'")
}
if (is.na(na.last)) {
x <- x[!is.na(x)]
na.last <- TRUE
}
if (method == "radix") {
return(order(x, na.last = na.last, decreasing = decreasing,
method = "radix"))
}
.Internal(order(na.last, decreasing, x))
}
Upvotes: 6