Thankyou for the clarification, Brian. This is very helpful (as usual). However, I think the important point, which I misstated, is that whether it be for() or, e.g. lapply(), the "loop" contents must be evaluated at the interpreted R level, and this is where most time is typically spent. To get the speedup that most people hope for, avoiding the loop altogether (i.e. moving loop **and** evaluations) to C level, via R programming -- e.g. via use of matrix operations, indexing, or built-in .Internal functions, etc. -- is the key.
Please correct me if I'm (even partially) wrong. As you know, the issue arises frequently. -- Bert Gunter Genentech -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Prof Brian Ripley Sent: Friday, December 26, 2008 12:44 AM To: Oliver Bandel Cc: r-h...@stat.math.ethz.ch Subject: Re: [R] How can I avoid nested 'for' loops or quicken the process? On Thu, 25 Dec 2008, Oliver Bandel wrote: > Bert Gunter <gunter.berton <at> gene.com> writes: > >> >> FWIW: >> >> Good advice below! -- after all, the first rule of optimizing code is: >> Don't! >> >> For the record (yet again), the apply() family of functions (and their >> packaged derivatives, of course) are "merely" vary carefully written for() >> loops: their main advantage is in code readability, not in efficiency gains, >> which may well be small or nonexistent. True efficiency gains require >> "vectorization", which essentially moves the for() loops from interpreted >> code to (underlying) C code (on the underlying data structures): e.g. >> compare rowMeans() [vectorized] with ave() or apply(..,1,mean). > [...] > > The apply-functions do bring speed-advantages. > > This is not only what I read about it, > I have used the apply-functions and really got > results faster. > > The reason is simple: an apply-function does > make in C, what otherwise would be done on the level of R > with for-loops. Not true of apply(): true of lapply() and hence sapply(). I'll leave you to check eapply, mapply, rapply, tapply. So the issue is what is meant by 'the apply() family of functions': people often mean *apply(), of which apply() is an unusual member, if one at all. [Historical note: a decade ago lapply was internally a for() loop. I rewrote it in C in 2000: I also moved apply to C at the same time but it proved too little an advantage and was reverted. The speed of lapply comes mainly from reduced memory allocation: for() is also written in C.] -- Brian D. Ripley, rip...@stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
