by Yanchang Zhao, RDataMining.com
Below are simple examples of profiling R code, which help to find out which steps or functions are most time consuming. It is very useful for improving efficiency of R code.
# profiling of running time
Rprof(“myFunction.out”)
y <- myFunction(x) # this is the function to profile
Rprof(NULL)
summaryRprof(“myFunction.out”)
The example below profiles memory as well. Memory allocation can also be profiled with function Rprofmem().
# profiling of both time and memory
Rprof(“myFunction.out”, memory.profiling=T)
y <- myFunction(x)
Rprof(NULL)
summaryRprof(“myFunction.out”, memory=”both”)
A detailed example of profiling R code can be found at http://www.stat.berkeley.edu/~nolan/stat133/Fall05/lectures/profilingEx.html.
