[SciPy-User] rbf interpolating

[Wolfgang Kerzendorf]

Thanks. that explains it. I'm now using the idw.

I think it should become part of the interpolate package. it seems very 
well written...

cheers
   W
On 14/03/11 9:16 PM, denis wrote:
> 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
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