[SciPy-Dev] Introduction and feature proposal.

[Pablo Winant]

On 21/02/2013 14:54, Robert Kern wrote:
> On Thu, Feb 21, 2013 at 12:30 AM, Christopher Miller
> <cmiller730 at gmail.com> wrote:
>> Hello,
>>
>> My name is Chris Miller and I'm a recent applied math PhD from
>> University of Maryland. I have some matlab and C/C++ code for computing
>> multi-dimensional integrals using Smolyak sparse grids that I think
>> might fit well inside scipy.integrate. Sparse grid quadrature delays the
>> onset of the so called "curse of dimensionality," and is very efficient
>> for evaluating integrals with a 'moderate' number of variables, say
>> ~<50. Sparse grids rules can also be tailored to perform integration
>> with respect to various measures (uniform, Gaussian, beta-distribution,
>> etc.). I'd appreciate any feedback on whether or not people would find
>> this useful.
> That sounds really cool! Yes, please!
>
I'm very interested by it too, mostly by interpolation routines. How 
does the code you have compare to the "sparse grid interpolation 
toolbox" by andreas Klimke ? This one has adaptive dimensions and 
several types of grid, but I found it quite slow and not very useful 
when repeatedly evaluate an interpolated function.

I also have a piece of code in Python for sparse products of Chebychev 
polynomials : 
https://github.com/albop/dolo/tree/master/dolo/numeric/interpolation 
(sorry to send that link again). It is pure vectorized numpy and I'm 
curious to see how it would compare (have no doubt it is very memory 
hungry).

Pablo