[SciPy-user] Making faster statistical distributions

[Travis Oliphant]

Robert Kern wrote:

>On Thu, Jan 29, 2004 at 03:53:10PM -0500, Christopher Fonnesbeck wrote:
>
>[snip]
>
>  
>
>>Well, the binomial and normal distributions, for sure, off the top of 
>>my head. Using the scipy distributions slows my MCMC code down 
>>significantly (they were the bottleneck, according to the profiling 
>>module). Using Fortran via f2py sped things up a lot. I'm not talking 
>>about the generation of random deviates, necessarily, but rather the 
>>pdf's, which are used for calculating likelihoods.
>>    
>>
>
>I'm willing to bet that the speed is lost by the generality of the
>framework. There's a lot of argument manipulation and not a lot of
>actual computation. It might be useful to add a fastdists module that
>computes pdfs and cdfs in a more specific (but fast) way for the more
>common distributions. And log-pdfs, too, please! In fact, log-pdfs
>first since in many instances like MCMC, they're much more suitable.
>
>One could then override pdf() and cdf() (not _pdf() and _cdf()) in the
>specific classes. But that's a design that appears to have been decided
>against.
>  
>

I wouldn't say anything has been decided against at this point.   We 
could pretty easily over-ride pdf and cdf for whatevern distribution you 
like.  Perhaps it would be a good idea to do so for the most common pdfs.  

-Travis O.