Am 27.02.18 um 03:27 schrieb Chris Angelico:
On Tue, Feb 27, 2018 at 12:57 PM, bartc <b...@freeuk.com> wrote:
Anyway, even this pure Python version can deliver pseudo random numbers at
some 200,000 per second, while the built-in generator does 450,000 per
second, so it's not bad going.
The built-in generator is using a completely different algorithm
though, so rate of generation isn't the entire story. How long is the
period of the one you're using? (How long before it loops?) If you
churn the generator to an arbitrary number and then take the next 100
values it generates, are they randomly distributed?
George Marsaglia is a researcher who invented a couple of PRNGs which
are both simple (one of the first was called KISS) yet surprisingly
good. See here: https://en.wikipedia.org/wiki/KISS_(algorithm)
They possess all these desirable properties you mention above and pass
the DIEHARD random number generator tests (also invented by Marsaglia).
Can you
reconstruct the RNG's internal state by watching it generate numbers
for a short while?
https://eprint.iacr.org/2011/007.pdf
Obviously no PRNG is going to be perfect at this, but there are
certainly degrees of quality to be compared.
It is a field of research and the generator shown by Bart is one of the
better generators constructed by an expert in the field.
Christian
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