Daniel, allow me to step off the party line here for a moment, in a problem like this it's better to code your function in C and then call it from R. You get vast amount of performance improvement instantly. (From what I see the process of recoding in C should be quite straight forward.)
H. -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Daniel Folkinshteyn Sent: Friday, June 06, 2008 4:35 PM To: hadley wickham Cc: r-help@r-project.org; Patrick Burns Subject: Re: [R] Improving data processing efficiency > install.packages("profr") > library(profr) > p <- profr(fcn_create_nonissuing_match_by_quarterssinceissue(...)) > plot(p) > > That should at least help you see where the slow bits are. > > Hadley > so profiling reveals that '[.data.frame' and '[[.data.frame' and '[' are the biggest timesuckers... i suppose i'll try using matrices and see how that stacks up (since all my cols are numeric, should be a problem-free approach). but i'm really wondering if there isn't some neat vectorized approach i could use to avoid at least one of the nested loops... ______________________________________________ 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.
