default random object?

[Don]

Andrei Alexandrescu wrote:
> Joel C. Salomon wrote:
>> Don wrote:
>>> There's a couple of difficult situations involving floating-point 
>>> numbers.
>> <snip>
>>> * any floating point range which includes 0 is difficult, because there
>>> are so many numbers which are almost zero. The probability of getting a
>>> zero for an 80-bit real is so small that you probably wouldn't encounter
>>> it in your lifetime. I think this weakens arguments based on analogy
>>> with the integer case.
>>
>> In that vein: for the floating-point case, do you want to emulate a
>> “true” uniform random distribution in the range [x, y), or make every
>> expressible IEEE 754 value in that range come out with equal likelihood?
>> One is the logarithm of the other, in some sense.
> 
> The former! Otherwise the distribution will be biased toward numbers 
> closer to 0 (which are denser than larger numbers).
> 
> That being said, for the range [0, 1) the exponent is constant so it's 
> nice to generate all possible mantissa values, something that simple 
> division by uint.max does not achieve.

You mean [1, 2). The code for complete uniform distribution is in 
tango.math.random, thanks to Fawzi.
Looking closely at his code, I find he's using (a,b) for the 
floating-point case, not the [a,b) which I had expected.