I have read a solution to this using tic(), toc() functions
tic <- function(gcFirst = TRUE, type=c("elapsed", "user.self", "sys.self"))
{
type <- match.arg(type)
assign(".type", type, envir=baseenv())
if(gcFirst) gc(FALSE)
tic <- proc.time()[type]
assign(".tic", tic, envir=baseenv())
invisible(tic)
}
toc <- function()
{
type <- get(".type", envir=baseenv())
toc <- proc.time()[type]
tic <- get(".tic", envir=baseenv())
print(toc - tic)
invisible(toc)
}
tic();
-----code----
toc();
elapsed
0.15
But I would like to get a lot of precision in milliseconds?
Also I was using this
ptm <- proc.time()
---code
proc.time() - ptm
and get this
user system elapsed
1.55 0.25 1.84
How to get more decimals or more precision?
1) Timing is operating-system dependent. On Windows you may only get milliseconds.
2) No need to define tic()
and toc()
, R has system.time()
. Here is an example:
R> system.time(replicate(100, sqrt(seq(1.0, 1.0e6))))
user system elapsed
2.210 0.650 2.867
R>
3) There are excellent add-on packages rbenchmark and microbenchmark.
3.1) rbenchmark is particularly useful for comparison of commands, but can also be used directly:
R> library(rbenchmark)
R> x <- seq(1.0, 1.0e6); benchmark(sqrt(x), log(x))
test replications elapsed relative user.self sys.self user.child sys.child
2 log(x) 100 5.408 2.85835 5.21 0.19 0 0
1 sqrt(x) 100 1.892 1.00000 1.62 0.26 0 0
R>
3.2) microbenchmark excels at highest precision measurements:
R> library(microbenchmark)
R> x <- seq(1.0, 1.0e6); microbenchmark(sqrt(x), log(x))
Unit: nanoseconds
expr min lq median uq max
1 log(x) 50589289 50703132 55283301 55353594 55917216
2 sqrt(x) 15309426 15412135 15452990 20011418 39551819
R>
and this last one, particularly on Linux, already gives you nano-seconds. It can also plot results etc so have a closer look at that package.