[R] python

[Patrick Burns]

One little thing that I think Barry
meant to say.

If the bottleneck is in your code, you
may be able to improve the situation
enough by merely rewriting the R code
of your function.  If that doesn't work,
then you can move to C.



Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of "The R Inferno" and "A Guide for the Unwilling S User")

Barry Rowlingson wrote:
> On Sat, Nov 21, 2009 at 2:29 PM, Jean Legeande <jean.legeande at gmail.com> wrote:
>> Dear R users,
>>
>> I would like to make my R code for MCMC faster. It is possible to integrate
>> C code into R but I think C is too complicated for me. I would need a C
>> introduction only for MCMC and I do not know if such a thing exists.
>>
>> I was thinking of Python (and scipy). Where could I read about its
>> integration into R ? How developed are the statistical packages in Python ?
>> I could not find a Python package on the web with functions to simulate
>> Wishart, or multivariate gamma or student distributions.
>>
>> Since I am a little bit lost, I write this message to the R help list. Sorry
>> for these naive questions and thanks for your help.
>>
> 
>  Have you done a profile of your MCMC code to see where the bottleneck
> is? Without doing that first any effort could be a total waste of
> time.
> 
>  R can do a lot of it's calculations at the same level as C, so if 80%
> of your time is spent inverting matrices then converting to Python or
> C (or even assembly language) isn't going to help much since R's
> matrix inversion is done using C code (and quite possibly very
> optimised C code with maybe some assembly language too).
> 
>  So do a profile (see ?Rprof) and work out the bottleneck. It might be
> one of your functions, in which case just re-writing that in C and
> linking to R (see programmers guide and a good C book) will do the
> job.
> 
>  My hunch is that Python and R run at about the same speed, and both
> use C libraries for speedups (Python primarily via the numpy package).
> 
>  You can call the GSL from Python, and there are probably tricks for
> getting the distributions you want:
> 
> http://www.mailinglistarchive.com/help-gsl@gnu.org/msg00096.html
> 
>  describes how to get samples from a Wishart.
> 
>  However using the GSL from Python probably wont be much faster than
> using R because again it's all at the C level already. Did I suggest
> you profile your code?
> 
> Barry
> 
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