[SciPy-user] [Fwd: 3D interpolation over irregular data]

[José María García Pérez]

Hi Mark,
Try Radial Basis Functions. But I'm not sure if it's implemented at
SciPy/Numpy. I implemented myself long time ago, but better if there is
something already done within the project.
Regards,
José M.

2008/7/30 mark starnes <m.starnes05 at imperial.ac.uk>

> Hi everyone,
>
> I've looked through the list here and in Numpy-users, and checked the
> 'net but can't find an answer to this problem (with luck, I've missed
> something obvious!).
>
> I've an array of velocities at 80,000 points, irregularly spaced (from a
> CFD analysis).  I'd like to generate the interpolated velocity at any
> position in the domain, to map the data to an acoustics analysis on a
> different mesh.
>
> I tried a least squares approach but the errors are too large using
> polynomials and trigonometric functions.  My conclusion is that I need a
> nearest-neighbour type interpolation routine.
>
> Is there such a routine in Scipy or Numpy?  From inspection of Matlab's
> functions 'interp3' may be similar to what I would like, but I can't test.
>
> If there's nothing available, I'll end up converting one of the
> submitted scripts at the url,
>
>
> http://www.mathworks.com/matlabcentral/fileexchange/loadCategory.do?objectId=14&objectType=Category
>
>
> Thanks in advance,
>
> Mark.
>
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