It seems to me that it's not really just "large" that is the issue, but only if you have a range larger than std::numeric_limits<float>::max(). Ideally, you'd not really want to be messing with too very many numbers that are within many orders of magnitude of the max float value, as your precision will be awful. Are you just edge-case testing, or do you have a real reason to generate uniform distributions over this range?
Brian The documentation doesn't say anything about the input range of the distribution. So I expect it to work with *any* range. As for the real reason, I need to unit-test a function of my own code
Le 25/11/2013 22:03, Brian Budge a écrit : that takes a float as an argument. I want to test that my function behaves correctly for any given float. Using a few thousands of randomly generated floats and calling my function with that seems a good idea. Jeremy