> I think the sum way is the best. On my Linux machine running R-3.0.0 the sum way is slightly faster: > x <- rexp(1e6, 2) > system.time(for(i in 1:100)sum(x>.3 & x<.5)) user system elapsed 4.664 0.340 5.018 > system.time(for(i in 1:100)length(which(x>.3 & x<.5))) user system elapsed 5.017 0.160 5.186
If you are doing many of these counts on the same dataset you can save time by using functions like cut(), table(), ecdf(), and findInterval(). E.g., > system.time(r1 <- vapply(seq(0,1,by=1/128)[-1], function(i)sum(x>(i-1/128) & > x<=i), FUN.VALUE=0L)) user system elapsed 5.332 0.568 5.909 > system.time(r2 <- table(cut(x, seq(0,1,by=1/128)))) user system elapsed 0.500 0.008 0.511 > all.equal(as.vector(r1), as.vector(r2)) [1] TRUE You should do the timings yourself, as the relative speeds will depend on the version or dialect of the R interpreter and how it was compiled. E.g., with the current development version of 'TIBCO Enterprise Runtime for R' (aka 'TERR') on this same 8-core Linux box the sum way is considerably faster then the length(which) way: > x <- rexp(1e6, 2) > system.time(for(i in 1:100)sum(x>.3 & x<.5)) user system elapsed 1.87 0.03 0.48 > system.time(for(i in 1:100)length(which(x>.3 & x<.5))) user system elapsed 3.21 0.04 0.83 > system.time(r1 <- vapply(seq(0,1,by=1/128)[-1], function(i)sum(x>(i-1/128) & x<=i), FUN.VALUE=0L)) user system elapsed 2.19 0.04 0.56 > system.time(r2 <- table(cut(x, seq(0,1,by=1/128)))) user system elapsed 0.27 0.01 0.13 > all.equal(as.vector(r1), as.vector(r2)) [1] TRUE Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf > Of lcn > Sent: Friday, April 26, 2013 12:09 PM > To: Mikhail Umorin > Cc: r-help@r-project.org > Subject: Re: [R] speed of a vector operation question > > I think the sum way is the best. > > > On Fri, Apr 26, 2013 at 9:12 AM, Mikhail Umorin <mike...@gmail.com> wrote: > > > Hello, > > > > I am dealing with numeric vectors 10^5 to 10^6 elements long. The values > > are > > sorted (with duplicates) in the vector (v). I am obtaining the length of > > vectors such as (v < c) or (v > c1 & v < c2), where c, c1, c2 are some > > scalar > > variables. What is the most efficient way to do this? > > > > I am using sum(v < c) since TRUE's are 1's and FALSE's are 0's. This seems > > to > > me more efficient than length(which(v < c)), but, please, correct me if I'm > > wrong. So, is there anything faster than what I already use? > > > > I'm running R 2.14.2 on Linux kernel 3.4.34. > > > > I appreciate your time, > > > > Mikhail > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > 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. > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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.