[SciPy-Dev] Introduction and feature proposal.

Pablo Winant pablo.winant@gmail....
Thu Feb 21 09:58:39 CST 2013

On 21/02/2013 14:54, Robert Kern wrote:
> On Thu, Feb 21, 2013 at 12:30 AM, Christopher Miller
> <cmiller730@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 : 
(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 


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