3 ms·

If you want max entropy and normally distributed values then, I think, there's no other way to go. Nice post btw

• orlp 5y ago
  What do you mean by "normally distributed values"? Your reply also doesn't follow a normal distribution by the way. Did you mean uniform? For uniform values there is a way to go and my other reply exactly describes how.
  • torotonnato 5y ago
    Of course, it's uniform. I always swap the two names randomly hehe. I understand your code. The difference with the snippet I posted (which, btw, is not mine) is that the difference between successive floats is always a constant, i.e. there is no rounding. It's fast, has 23 bits of entropy and it's suited for constrained platforms/small demos [0], since it can be coded with very few asm instructions. I'm not saying that your solution hasn't its merits, well done. [0] The author of the code is a known member of the demoscene
    • orlp 5y ago
      Oh, I know very well who iq is :) And for a visual demo it might make perfect sense to sacrifice completeness of a solution for speed / code size. But to me, "pick a random number from {k/2^23 : 0 <= k < 2^23, k ∈ ℕ}" and "pick a random number uniformly at random from [0, 1)" are not the same. All operations (add/sub, mul/div, sin, exp, log, etc...), with IEEE754 floats are defined using real arithmetic, and then assumed to round to the nearest representable floating point value. I don't see why random number generation, at least as a default before micro-optimizing, should be any different.
      • torotonnato 5y ago
        You are right, I was uncomfortable with the uneven density of the floats approaching zero, but it's just an inherent property of their representation. Have a nice day :)