"Don" <nos...@nospam.com> wrote in message news:gnb7mt$2os...@digitalmars.com... > Andrei Alexandrescu wrote: >> Benji Smith wrote: >>> Benji Smith wrote: >>>> Maybe a NumericInterval struct would be a good idea. It could be >>>> specialized to any numeric type (float, double, int, etc), it would >>>> know its own boundaries, and it'd keep track of whether those >>>> boundaries were open or closed. >>>> >>>> The random functions would take an RND and an interval (with some >>>> reasonable default intervals for common tasks like choosing elements >>>> from arrays and random-access ranges). >>>> >>>> I have a Java implementation around here somewhere that I could port to >>>> D if anyone is interested. >>>> >>>> --benji >>> >>> Incidentally, the NumericInterval has lots of other interesting >>> applications. For example >>> >>> auto i = NumericInterval.UBYTE.intersect(NumericInterval.SBYTE); >>> bool safelyPolysemious = i.contains(someByteValue); >>> >>> auto array = new double[123]; >>> auto i = NumericInterval.indexInterval(array); >>> bool indexIsLegal = i.contains(someIndex); >>> >>> Using a numeric interval for generating random numbers would be, in my >>> opinion, totally ideal. >>> >>> double d = uniform(NumericInterval.DOUBLE); // Any double value >> >> I've never been in a situation in my life where I thought, hey, a random >> double is exactly what I'd need right now. It's a ginormous interval! >> >> Andrei > > It's worse than that. Since the range of double includes infinity, a > uniform distribution must return +-infinity with probability 1. It's > nonsense.
I would think that, with the possible exception of mathematicians, most of the time anyone would want a random floating-point number they would consider +/-infinity a special case. Most non-math-oriented code isn't really designed to handle infinity anyway. Besides, technically, double also includes NaN ;)
