[Rd] Question re: NA, NaNs in R

Prof Brian Ripley ripley at stats.ox.ac.uk
Mon Feb 10 08:11:05 CET 2014


There is one NA but mulitple NaNs.

And please re-read 'man memcmp': your cast is wrong.

On 10/02/2014 06:52, Kevin Ushey wrote:
> Hi R-devel,
>
> I have a question about the differentiation between NA and NaN values
> as implemented in R. In arithmetic.c, we have
>
> int R_IsNA(double x)
> {
>      if (isnan(x)) {
> ieee_double y;
> y.value = x;
> return (y.word[lw] == 1954);
>      }
>      return 0;
> }
>
> ieee_double is just used for type punning so we can check the final
> bits and see if they're equal to 1954; if they are, x is NA, if
> they're not, x is NaN (as defined for R_IsNaN).
>
> My question is -- I can see a substantial increase in speed (on my
> computer, in certain cases) if I replace this check with
>
> int R_IsNA(double x)
> {
>      return memcmp(
>          (char*)(&x),
>          (char*)(&NA_REAL),
>          sizeof(double)
>      ) == 0;
> }
>
> IIUC, there is only one bit pattern used to encode R NA values, so
> this should be safe. But I would like to be sure:
>
> Is there any guarantee that the different functions in R would return
> NA as identical to the bit pattern defined for NA_REAL, for a given
> architecture? Similarly for NaN value(s) and R_NaN?
>
> My guess is that it is possible some functions used internally by R
> might encode NaN values differently; ie, setting the lower word to a
> value different than 1954 (hence being NaN, but potentially not
> identical to R_NaN), or perhaps this is architecture-dependent.
> However, NA should be one specific bit pattern (?). And, I wonder if
> there is any guarantee that the different functions used in R would
> return an NaN value as identical to R_NaN (which appears to be the
> 'IEEE NaN')?
>
> (interested parties can see + run a simple benchmark from the gist at
> https://gist.github.com/kevinushey/8911432)
>
> Thanks,
> Kevin
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



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