[SciPy-User] rbf interpolating

[denis]

Wolfgang,
  Rbf seems to do only scalar z, the source has
self.di = asarray(args[-1]).flatten()

(I wouldn't recommend RBF anyway, because
- arbitrary choice of function = gaussian ...
- one epsilon can't adapt to data fine here / coarse there
- the matrix A can be near-singular
- global, O(N) for each interpolation.)

I like (advt) the combination of scipy.spatial.cKDTree and inverse
distance weighting under
http://stackoverflow.com/questions/3104781/inverse-distance-weighted-idw-interpolation-with-python

cheers
  -- denis

On Mar 11, 1:11 pm, Wolfgang Kerzendorf <wkerzend... at googlemail.com>
wrote:
> Dear all
>
> I am currently trying to use interpolate.Rbf to interpolate my data. My
> data looks like that:
...

> So the first 5 items are the coordinates. the last is the data (which is
> not only a single number but is actually a 1D array. If I do this with
> griddata it works.
>
> I tried giving it to Rbf by doing Rbf(*data), but I get the following error:

>
> ValueError: incompatible dimensions