[SciPy-user] Making faster statistical distributions

[Travis Oliphant]

Christopher Fonnesbeck wrote:

> I am already using pieces of SciPy in my Markov chain Monte Carlo 
> package (PyMC), mostly for plotting functionality. I would also like 
> to exploit the distributions implemented in scipy.stats, but they are 
> far too slow for use in statistical simulation applications like MCMC, 
> where millions of random draws may be taken. Therefore, I am thinking 
> of implementing many of these distributions (at least the common ones) 
> as C or Fortran extensions. I am unsure whether to use Fortran through 
> f2py for this task, or C through weave.inline (for example). I have 
> used both in the past for various tasks, and was generally happy with 
> both. Any suggestions?


Could you specify which ones are too slow?  This is a rather broad 
statement as many are implemented in C and are very fast.   Some 
distributions, however,  do default to using a numerical solver to 
invert the cdf and apply this to uniform random variates.  You can 
improve the speed of these distributions by overriding the _ppf  method 
or the _rvs method of the object to use a faster, more specialized 
method.   I would use weave or fortran with f2py to do this.

Best,

-Travis O.

>
> Thanks,
> C.
> -- 
> Christopher J. Fonnesbeck ( c h r i s @ f o n n e s b e c k . o r g )
> Georgia Cooperative Fish & Wildlife Research Unit, University of Georgia
>
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