Dennis Lee Bieber <wlfr...@ix.netcom.com> writes: > On Mon, 19 Nov 2018 19:05:44 -0200, Robert Girault <r...@dev.null> declaimed > the following: > >>I mean the fact that with 624 samples from the generator, you can >>determine the rest of the sequence completely. > > Being able to predict the sequence after a large sampling does not mean > that the /distribution of values/ is not (pseudo-) random.
The problem with determining its sequence is that it might defeat its purpose. If you use mt19937 to select a pivot in random Quicksort for example (where you plan to spend n lg n time in sorting), we can frustrate your plans and force it into n^2 every time, an effective DoS attack on your software. > After all, pretty much all random number generators will produce the > same sequence if given the same starting seed... You are, in effect, > treating your 624 samples as a very large seed... I think I disagree with your take here. With mt19937, given ANY seed, I can eventually predict all the sequence without having to query the oracle any further. If you're just writing a toy software, even K&R PRNG works just fine. If you're writing a weather simulation, I suppose you need real random-like properties and still need your generator to be reproducible. If you're using random Quicksort, you do need unpredictability and reproducibility. If you're writing a crypto application, then you need something way stronger. We need all of them. But mt19937 is now useful only in toy software. -- https://mail.python.org/mailman/listinfo/python-list
