On 07/12/2022 13:05, David Lowry-Duda wrote: > Inspired by the recent thread about pseudorandom number generators on > python-ideas (where I also mistakenly first wrote this message), I began > to wonder: suppose that I had a pseudorandom number generator that > attempted to generate a nonuniform distribution. Suppose for instance > that it was to generate a 0 bit 2/3 of the time, and a 1 bit 1/3 of the > time. > > How would one go about testing this PRNG against an idealized (similarly > biased) PRNG?
I believe things go like this. If you have a uniform PRNG, you test it against the state-of-the-art in statistical tests then build from it your nonuniform one. Now you have a nonuniform one that's tested. But you want things the other way around. Having a nonuniform one to start, you build a uniform one from the nonuniform one and then test it against the state-of-the-art in statistical tests. I believe you might be wondering how to build one from the other, but I'll let you check that. By the way, there's no such thing as an idealized PRNG. All PRNG fail all statistical tests. The question is when. A bad PRNG fails quickly and obviously. A good one requires large samples or a nontrivial test. -- https://mail.python.org/mailman/listinfo/python-list
