[Numpy-discussion] OT: A Way to Approximate and Compress a 3DSurface

[Christopher Barker]

Nadav Horesh wrote:
> Wouldn't a random or regular subsampling of the set will do the job?

 > I have N tabulated data points { (x_i, y_i, z_i) } that describes a 3D
 > surface. The surface is pretty "smooth."

If it's equally "smooth" everywhere, then yes, a subsampling would work 
fine, but I'm guessing the OP wants something smarter than that.

> For data interpolation: 2D-Delaunay triangulation based method (I think you can find one in the scipy cookbook).

yup -- but  then you need the decimation to remove the "unneeded" 
points. I don't think Scipy has that.

the GNU Triangulated Surface Library:

http://gts.sourceforge.net/

should do what you want, but I don't know of any Python bindings -- you 
may be able to write some to the routines you need without too much pain.

CGAL may have something too, and it does have Python bindings.

http://cgal-python.gforge.inria.fr/

-Chris


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