An ifelse-like function that only evaluated what was needed would be fine, but it would have to be different from ifelse itself. The trick is to come up with a good parameterization.
E.g., how would it deal with things like ifelse(is.na(x), mean(x, na.rm=TRUE), x) or ifelse(x>1, log(x), runif(length(x),-1,0)) or ifelse(x>1, log(x), -seq_along(x)) Would it reject such things? Deciding that the x in mean(x,na.rm=TRUE) should be replaced by x[is.na(x)] would be wrong. Deciding that runif(length(x)) should be replaced by runif(sum(x>1)) seems a bit much to expect. Replacing seq_along(x) with seq_len(sum(x>1)) is wrong. It would be better to parameterize the new function so it wouldn't have to think about those cases. Would you want it to depend only on a logical vector or perhaps also on a factor (a vectorized switch/case function)? 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 ivo welch > Sent: Tuesday, March 01, 2011 12:36 PM > To: Henrique Dallazuanna > Cc: r-help > Subject: Re: [R] inefficient ifelse() ? > > thanks, Henrique. did you mean > > as.vector(t(mapply(function(x, f)f(x), split(t, ((t %% 2)==0)), > list(f, g)))) ? > > otherwise, you get a matrix. > > its a good solution, but unfortunately I don't think this can be used > to redefine ifelse(cond,ift,iff) in a way that is transparent. the > ift and iff functions will always be evaluated before the function > call happens, even with lazy evaluation. :-( > > I still think that it makes sense to have a smarter vectorized %if% in > a vectorized language like R. just my 5 cents. > > /iaw > > ---- > Ivo Welch (ivo.we...@brown.edu, ivo.we...@gmail.com) > > > > > > On Tue, Mar 1, 2011 at 2:33 PM, Henrique Dallazuanna > <www...@gmail.com> wrote: > > Try this: > > > > mapply(function(x, f)f(x), split(t, t %% 2), list(g, f)) > > > > On Tue, Mar 1, 2011 at 4:19 PM, ivo welch <ivo...@gmail.com> wrote: > >> > >> dear R experts--- > >> > >> t <- 1:30 > >> f <- function(t) { cat("f for", t, "\n"); return(2*t) } > >> g <- function(t) { cat("g for", t, "\n"); return(3*t) } > >> s <- ifelse( t%%2==0, g(t), f(t)) > >> > >> shows that the ifelse function actually evaluates both f() > and g() for > >> all values first, and presumably then just picks left or > right results > >> based on t%%2. uggh... wouldn't it make more sense to > evaluate only > >> the relevant parts of each vector and then reassemble them? > >> > >> /iaw > >> ---- > >> Ivo Welch > >> > >> ______________________________________________ > >> 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. > > > > > > > > -- > > Henrique Dallazuanna > > Curitiba-Paraná-Brasil > > 25° 25' 40" S 49° 16' 22" O > > > > ______________________________________________ > 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.
