I think a more common idiom for the simpler case would be to use indexing vals <- c(0.1, 0.15, 0.2) mult <- vals[ASBclass]
(However, some people are on the move to enforce mult <- vals[as.numeric(ASBclass)] because people who confuse factors and character variables get even more confused about factor indexing being different from character indexing.) For the more complex cases, I think Chuck's split/unsplit principle is the ticket. For one thing, you avoid silliness like (X >= 0) * sqrt(X) + (X < 0) * -sqrt(-X) coming out with warnings from calculating the non-selected alternative. -pd > On 16 Sep 2015, at 07:56 , Anthoni, Peter (IMK) <peter.anth...@kit.edu> wrote: > > Hi, > > I guess this might work too and might be quite speedy: > > ASBclass = factor(c(1,2,2,3,2,1)) > Flow = c(1,1,1,1,1,1) > > mult = ((ASBclass==1) * 0.1 + (ASBclass==2) * 0.15 + (ASBclass==3) * 0.2) > deviation = mult * Flow > > or with the more complex arithmetic: > > deviation = ((ASBclass==1) * (Flow*2) + (ASBclass==2) * (Flow+3) + > (ASBclass==3) * sqrt(Flow)) > > cheers > Peter > > > >> On 16 Sep 2015, at 04:20, Charles C. Berry <ccbe...@ucsd.edu> wrote: >> >> On Tue, 15 Sep 2015, Bert Gunter wrote: >> >>> Thanks to both Davids. >>> >>> I realize that these things are often a matter of aesthetics -- and >>> hence have little rational justification -- but I agree with The Other >>> David: eval(parse) seems to me to violate R's soul( it makes R a macro >>> language instead of a functional one). >>> >>> However, mapply(... switch) effectively loops through the frame row by >>> row. Aesthetically, I like it; but it seems inefficient. If there are >>> e.g. 1e6 rows in say 10 categories, I think Jeff's approach should do >>> much better. I'll try to generate some actual data to see unless >>> someone else beats me to it. >> >> Use mapply like this on large problems: >> >> unsplit( >> mapply( >> function(x,z) eval( x, list( y=z )), >> expression( A=y*2, B=y+3, C=sqrt(y) ), >> split( dat$Flow, dat$ASB ), >> SIMPLIFY=FALSE), >> dat$ASB) >> >> Chuck >> >> ______________________________________________ >> 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. > > ______________________________________________ > 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. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.
