On Sat, Aug 08, 2009 at 10:39:04AM -0400, Prof. John C Nash wrote:
> I'll save space and not include previous messages.
>
> My 2 cents: At the very least the documentation needs a fix. If it is
> easy to do, then Ted Harding's suggestion of a switch (default OFF) to
> check for sign difference would be sensible.
>
> I would urge inclusion in the documentation of the +0, -0 example(s) if
> there is NOT a way in R to distinguish these.
It is possible to distinguish 0 and -0 in R, since 1/0 == Inf and
1/(-0) == -Inf.
I do not know, whether there are also other such situations. In particular
(0)^(-1) == (-0)^(-1) # [1] TRUE
log(0) == log(-0) # [1] TRUE
> There are occasions where
> it is useful to be able to detect things like this (and NaN and Inf and
> -Inf etc.). They are usually not of interest to users, but sometimes are
> needed for developers to check edge effects. For those cases it may be
> time to consider a package FPIEEE754 or some similar name to allow
> testing and possibly setting of flags for some of the fancier features.
> Likely used by just a few of us in extreme situations.
I think that distinguishing 0 and -0 may be useful even for nonexpert
users for debugging purposes. Mainly, because x == y does not imply
that x and y behave equally as demonstrated above or by
x <- 0
y <- - 0
x == y # [1] TRUE
1/x == 1/y # [1] FALSE
I would like to recall the suggestion
On Sat, Aug 08, 2009 at 03:04:07PM +0200, Martin Maechler wrote:
> Maybe we should introduce a function that's basically
> isTRUE(all.equal(..., tol=0)) {but faster}, or
> do you want a 3rd argument to identical, say 'method'
> with default c("oneNaN", "use.==", "strict")
>
> oneNaN: my proposal of using memcmp() on doubles as its used for
> other types already (and hence distinguishing +0 and -0;
> otherwise keeping the feature that there's just one NaN
> which differs from 'NA' (and there's just one 'NA').
>
> use.==: the previous R behaviour, using '==' on doubles
> (and the "oneNaN" behavior)
>
> strict: be even stricter than oneNaN: Use memcmp()
> unconditionally for doubles. This would be the fastest
> version of all three.
In my opinion, for debugging purposes, the option
identical(x,y,method="strict"),
which implies that x and y behave equally, could be useful, if it is available
in R base,
At the R interactive level, negative zero as the value of -0 could possibly
be avoided. However, negative zero may also occur in numerical calculations,
since it may be obtained as x * 0, where x is negative. So, i think, negative
zero cannot be eliminated from consideration as something too infrequent.
Petr.
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