(I asked this question on StackOverflow <http://stackoverflow.com/q/30035939/1191259> a short time ago; sorry if you're seeing it again. Feel free to answer there as well if you like. The code formatting and such on that site can be nice.)
I benchmarked matrix and vector subsetting to extract the diagonal of a square matrix against the diag() function, and the latter lost by a wide margin: nc <- 1e4 set.seed(1) m <- matrix(sample(letters,nc^2,replace=TRUE), ncol = nc) microbenchmark( diag = diag(m), cond = m[row(m)==col(m)], vec = m[(1:nc-1L)*nc+1:nc], mat = m[cbind(1:nc,1:nc)], times=10) # results Unit: microseconds expr min lq mean median uq max neval diag 604343.469 629819.260 710371.3320 706842.3890 793144.019 837115.504 10 cond 3862039.512 3985784.025 4175724.0390 4186317.5260 4312493.742 4617117.706 10 vec 317.088 329.017 432.9099 350.1005 629.460 651.376 10 mat 272.147 292.953 441.7045 345.9400 637.506 706.860 10 Looking in the diag() function, I suspect the fault is mostly due to its core operation of c(m)[v], where v is the vector in the "vec" benchmark above. This code seems to confirm it: v <- (1:nc-1L)*nc+1:nc microbenchmark(diaglike=c(m)[v],vec=m[v]) # Unit: microseconds # expr min lq mean median uq max neval # diaglike 579224.436 664853.7450 720372.8105 712649.706 767281.5070 931976.707 100 # vec 334.843 339.8365 568.7808 646.799 663.5825 1445.067 100 But I'm still wondering why diag() uses c()...? With it being so slow, I'd be inclined to write a qdiag() without the c() and just use that the next time I need matrix algebra. Any insight would be appreciated; thanks! -- View this message in context: http://r.789695.n4.nabble.com/Why-is-the-diag-function-so-slow-for-extraction-tp4706780.html Sent from the R devel mailing list archive at Nabble.com. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
