[SciPy-dev] random.set_state also in need of EXPERT attention

[David Goldsmith]

Awesome, Pauli, thanks!

DG

--- On Tue, 7/28/09, Pauli Virtanen <pav+sp at iki.fi> wrote:

> From: Pauli Virtanen <pav+sp at iki.fi>
> Subject: Re: [SciPy-dev] random.set_state also in need of EXPERT attention
> To: scipy-dev at scipy.org
> Date: Tuesday, July 28, 2009, 2:44 PM
> 
> (Disclaimer: I'm not a PRNG expert.)
> 
> On 2009-07-28, David Goldsmith <d_l_goldsmith at yahoo.com>
> wrote:
> > Hi, folks!  Ralf originally requested expert
> attention for this 
> > in its Discussion section; I over-confidently said I
> thought I 
> > could handle it; after too many hours of unproductive
> research 
> > (I seem to have found that there's a lot of "politics"
> in the 
> > field of random number generators? 
> 
> Looks like science as usual to me :) I think the natural 
> explanation is that everyone proposing a new PRNG of course
> wants 
> to advertise its merits. Also, as there is no clear-cut way
> to 
> quantify the "randomness" of a PRNG and because of speed 
> tradeoffs, there is something to argue about and many
> different 
> alternatives have been proposed.
> 
> > Despite widespread use: 
> > http://en.wikipedia.org/wiki/Mersenne_twister,
> Matsumoto & 
> > Nishimura and this algorithm don't appear to have much
> 
> > recognition in certain circles, e.g., those under the
> influence 
> > of Marsaglia, e.g., notably, "Numerical Recipes."
> 
> The second edition of Numerical recipes was written in
> 1992, so 
> that explains why it's not there.
> 
> If you Google it, for the third edition the authors of NR
> respond 
> [1] that they didn't include MT because it "has just too
> many 
> operations per random value generated". This is of course 
> understandable in a book that aims to give a focused
> introduction 
> on the subject. Whether it reflects the merits of the
> algorithm 
> is then a different question.
> 
> .. [1] http://www.nr.com/forum/showthread.php?t=1724
> 
> > I understand that Marsaglia is critical of MT, but for
> "NR" to 
> > completely ignore an algorithm in such widespread use,
> well, 
> > out of curiosity, if anyone knows, "what gives"?)
> 
> As I see it, the statements sourced in the Wikipedia
> article are 
> fairly mild, criticising mostly the complexity of the
> algorithm. 
> Also, they were not backed by anything, and probably should
> be 
> taken with a grain of salt.
> 
> Marsaglia seems to have proposed another types of PRNGs in
> 2003, 
> but these had flaws, which maybe were addressed by Brent
> later 
> on. (Cf. [2] and follow the references.)
> 
> The MT article is widely cited (123 citations as reported
> by ACM, 
> 1346 by Google Scholar), and sampling some of the
> review-type 
> ones (eg. [3,4]) the generator seems to have done
> reasonably in 
> various randomness tests and also be reasonable speed-wise.
> 
> Perhaps the algorithm is not optimal -- after all, it's
> already 
> more than ten years old -- but it appears to be well tested
> and 
> understood.
> 
> .. [2] http://wwwmaths.anu.edu.au/~brent/random.html
> .. [3] http://dx.doi.org/10.1016/j.csda.2006.05.019
> .. [4] http://www.iro.umontreal.ca/~simardr/testu01/tu01.html
> 
> -- 
> Pauli Virtanen
> 
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