[SciPy-user] How to fit a surface from a list of measured 3D points ?

[LB]

I would like to estimate some geoemetric characteristic of this
surface and view the variation of radius of curvature.

> What's your eventual goal for the fit surface? There are a lot of  
> possible approaches possible with the tools in scipy (e.g. fit a  
> spline, as you have done, or fit a simpler parameteric surface in a  
> least-squares fashion, or go for a nonparametric approach and  
> interpolate between the points with radial basis functions).  The best  
> approach will likely depend on what you want to do with the surface...  
> but what you have seems like a reasonable start.
I think a 2D surface spline could do the trick, but  I think I didn't
fit it well :
- the estimated z can go far below the range of my inputs ( [48-62] )
- As you can see on small_data.jpg, the surface is really 3D, there is
a kind of crease in my surface, and there are two z value for (x,y) ~
(2,2). So I 'm not sure if this is the good approach

>
> Also, ndimage.map_coordinates is for resampling of an array (e.g.  
> image) at arbitrary coordinates: perhaps not of direct use here.
Ok