Hello :-)
twisted.positioning has just (read: last night) grown a new module, called util, which has two functions I needed for statistical analysis: the error function (erf) and the inverse normal cumulative distribution function (Phi). As most of you on this mailing list probably know, code headed for trunk needs to be reviewed. The reason I need to ask for this specifically is because the reviewer does not need to know anything about Twisted, but does need some experience with how numerical algorithms work -- and that's about the opposite of most Twisted reviewers ;-) The default is to attempt to use scipy's implementation (which is hopefully faster), but otherwise fall back to a pure Python implementation (which from my tests is still way more than fast enough). The implementations rely on Chebyshev polynomial interpolation. The error function is a pretty simple one, the inverse normal cdf is slightly harder (three parts: the center is a simple rational, the 'tails' are rationals expressed in a linearizing parameter). There are two things that make this easier: 1. Other people have done similar things, and said coefficients can be looked up in other places (I'm not the first person to do the math -- I'm just the first person to implement both in Python with a shared Horner scheme evaluator, apparently) 2. It can be shown to be accurate by comparing the results at random points with scipy's reference implementation if we do it for 10**5 or 10**6 points or so -- there's already an automated unit test that does it for a much smaller number If you're not 100% sure you're up to it from just seeing the code, I can also talk you through it and show how I got there :-) It might be more useful to create a separate ticket for this piece of code for reviewing purposes, if anyone else feels that's the case I'll make the ticket. People who are interested: you can reply to this mail, mail me personally, or contact me on freenode (nick: lvh). (Oh, and before someone tells me I'm reinventing the wheel: yes, but not really -- the only commonly available python implementation is Scipy, that's *already* used as the default, and we do need something in case of no scipy (adding a dependency just because of one function on all of scipy is not exactly good either) and the only other simpler alternative would be a giant LUT with linear interpolation which would have been *much* worse near the edges of the interval of invncdf, which also happen to be the *interesting* bits of that function...) tia lvh _______________________________________________ Twisted-Python mailing list Twisted-Python@twistedmatrix.com http://twistedmatrix.com/cgi-bin/mailman/listinfo/twisted-python
