Many sampling algorithms take as input random numbers in the `[0..1)`

interval. On the other hand, Pseudo-Random Number Generators usually produce their output as (unsigned) integer 32-bit or 64-bit numbers.

It is trivial to turn an `u:u32`

integer into an `f:[0..1]`

floating-point value, dividing `u`

by `2^32-1`

. This is because `u`

ranges in `[0..2^32-1]`

.

One might think that `u/2^32`

would produce a floating-point value lower than 1. But it does *not*, as evidenced by this loop:

The number printed out happens to be `0x100000101`

which is `2^32+257`

.

`( u / static_cast< f32_t >( 0x100000101ull ) )`

is the `f:[0..1)`

we were looking for.

`( u / static_cast< f64_t >( 0x100000080ull ) )`

does the same in double-precision.