> Uwe Ligges
> on Sun, 7 Aug 2016 09:51:58 +0200 writes:
> On 06.08.2016 17:30, Duncan Murdoch wrote:
>> On 06/08/2016 10:18 AM, Martin Maechler wrote:
[.]
>>> Of course, an ifelse2() should also be more efficient than
>>> ifelse() in typical "atomic" cases.
>>
>> I don't think it is obvious how to make it more efficient. ifelse()
>> already skips evaluation of yes or no if not needed. (An argument could
>> be made that it would be better to guarantee evaluation of both, but
>> it's usually easy enough to do this explicitly, so I don't see a need.)
> Same from here: I do not see how this can easily be made more efficient,
> since evaluating ony parts causes a lot of copies of objects whichs
> slows stuff down, hence you need some complexity in yes and no to make
> evaluations of parts of them more efficient on R level.
Yes, Duncan and Uwe are right, and my comment "wish" above was
mostly misleading. Some of the many small changes to ifelse()
since its initial [1998, R version 0.63.3] simple
ifelseR0633 <- function (test, yes, no)
{
ans <- test
test <- as.logical(test)
nas <- is.na(test)
ans[ test] <- rep(yes, length = length(ans))[ test]
ans[!test] <- rep(no, length = length(ans))[!test]
ans[nas] <- NA
ans
}
were exactly for adding speed in some of these cases.
> Anyway, to solve the problem, we may want an add argument to ifelse2()
> that allows for specification of the type of the result (as vapply does)?
A good idea, probably only needed / desirable if we'd consider a
C based version {as vapply} but for the moment I did not want to
go there.
The current ifelse() is nice with "pre-S3" objects, such as
as atomic (named) vectors and (dimnamed) arrays, including matrices,
by keeping most attributes for those... and does that relatively
efficiently.
What I really meant, not above, but earlier when talking about
ifelse()'s inefficiency should really *not* have been related to
this thread, I'm sorry for that confusion.
I mean the fact that many many usages of ifelse() are of the
form
ifelse(logiFn(x), f1(x), f2(x))
{with f1() or f2() often even being constant}
and e.g., in the case where logiFn(x) gives few TRUEs and f1(.)
is expensive and f2(.) very cheap (say "constant" NA), it is
much more efficient to use
ans <- x
Y <- logiFn(x)
ans[ Y] <- f1(x[ Y])
ans[!Y] <- f2(x[!Y])
as the expensive function is only called on a small subset of
the full x.
I'm working at the main topic and *am* thanking Duncan
for his conceptual analysis and the (few) proposals.
Martin
> Best,
> Uwe
>> Duncan Murdoch
>>
>>>
>>>
>>> Thank you for your ideas and suggestions.
>>> Again, there's no promise of implementation coming along with this
>>> e-mail.
>>>
>>> Martin Maechler
>>> ETH Zurich
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