Very interesting - thanks! Most of my problems are not limited by compute speed, but its clear that for some sorts of compute-intensive problems, sweep might be a limiting approach.
On 2/29/2024 6:12 PM, Richard M. Heiberger wrote: > I decided to do a direct comparison of transpose and sweep. > > > library(microbenchmark) > > NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix > lambda <- c(2, 3, 4) # Example vector > colNN <- t(NN) > > microbenchmark( > sweep = sweep(NN, 2, lambda, "/"), > transpose = t(t(NN)/lambda), > colNN = colNN/lambda > ) > > > Unit: nanoseconds > expr min lq mean median uq max neval cld > sweep 13817 14145 15115.06 14350 14657.5 75932 100 a > transpose 1845 1927 2151.68 2132 2214.0 7093 100 b > colNN 82 123 141.86 123 164.0 492 100 c > > Note that transpose is much faster than sweep because it is doing less work, > I believe essentially just changing the order of indexing. > > Using the natural sequencing for column-ordered matrices is much much faster. > >> On Feb 28, 2024, at 18:43, peter dalgaard<pda...@gmail.com> wrote: >> >>> rbind(1:3,4:6)/t(matrix(c(2,3,4), 3,2)) > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.