Measuring function execution time in R

Is there a standardized way in R of measuring execution time of function?

Obviously I can take system.time before and after execution and then take the difference of those, but I would like to know if there is some standardized way or function (would like to not invent the wheel).

I seem to remember that I have once used something like below:

somesysfunction("myfunction(with,arguments)")
> Start time : 2001-01-01 00:00:00  # output of somesysfunction
> "Result" "of" "myfunction"        # output of myfunction
> End time : 2001-01-01 00:00:10    # output of somesysfunction
> Total Execution time : 10 seconds # output of somesysfunction

Solution 1:

Another possible way of doing this would be to use Sys.time():

start.time <- Sys.time()
...Relevent codes...
end.time <- Sys.time()
time.taken <- end.time - start.time
time.taken

Not the most elegant way to do it, compared to the answere above , but definitely a way to do it.

Solution 2:

The built-in function system.time() will do it.

Use like: system.time(result <- myfunction(with, arguments))

Solution 3:

As Andrie said, system.time() works fine. For short function I prefer to put replicate() in it:

system.time( replicate(10000, myfunction(with,arguments) ) )

Solution 4:

microbenchmark is a lightweight (~50kB) package and more-or-less a standard way in R for benchmarking multiple expressions and functions:

microbenchmark(myfunction(with,arguments))

For example:

> microbenchmark::microbenchmark(log10(5), log(5)/log(10), times = 10000)
Unit: nanoseconds
           expr min lq    mean median uq   max neval cld
       log10(5)   0  0 25.5738      0  1 10265 10000   a
 log(5)/log(10)   0  0 28.1838      0  1 10265 10000

Here both the expressions were evaluated 10000 times, with mean execution time being around 25-30 ns.

Solution 5:

A slightly nicer way of measuring execution time, is to use the rbenchmark package. This package (easily) allows you to specify how many times to replicate your test and would the relative benchmark should be.

See also a related question at stats.stackexchange