Nick Fotopoulos wrote:
> I've been looking over the wiki and am not sure where the best place
> would be for such a snippet. Would it go with the numpy examples
> under vectorize or perhaps in a cookbook somewhere?
Yes. It seems to me like a cookbook example. In the utopian future, when
ther
On Jul 16, 2006, at 12:01 AM, Travis Oliphant wrote:
> Thanks for the decorator. This should be put on the www.scipy.org
> wiki.
I've been looking over the wiki and am not sure where the best place
would be for such a snippet. Would it go with the numpy examples
under vectorize or perhaps
Nick Fotopoulos wrote:
> Dear all,
>
> I often make use of numpy.vectorize to make programs read more like
> the physics equations I write on paper. numpy.vectorize is basically
> a wrapper for numpy.frompyfunc. Reading Travis's Scipy Book (mine is
> dated Jan 6 2005) kind of suggests to me
2006/7/14, Nick Fotopoulos <[EMAIL PROTECTED]>:
Any other suggestions?Hi Nick, I had some success by coding the integrand in fortran and wrapping it with f2py. If your probability density function is standard, you may find it in the flib library of the PyMC module of Chris Fonnesbeck ( a library
On Jul 14, 2006, at 12:56 PM, Tim Hochberg wrote:
> I think I'd try psyco (http://psyco.sourceforge.net/). That's
> pretty painless to try and may result in a significant improvement.
I've been doing more and more development on my PPC Mac, where psyco
is not an option. If the speed issue
Nick Fotopoulos wrote:
> On Jul 13, 2006, at 10:17 PM, Tim Hochberg wrote:
>
>
>> Nick Fotopoulos wrote:
>>
>>> Dear all,
>>>
>>> I often make use of numpy.vectorize to make programs read more
>>> like the physics equations I write on paper. numpy.vectorize is
>>> basically a wrapper
On Jul 13, 2006, at 10:17 PM, Tim Hochberg wrote:
> Nick Fotopoulos wrote:
>> Dear all,
>>
>> I often make use of numpy.vectorize to make programs read more
>> like the physics equations I write on paper. numpy.vectorize is
>> basically a wrapper for numpy.frompyfunc. Reading Travis's Scip
