On 30.08.2013 18:15, Pauli Virtanen wrote:
> 29.08.2013 19:01, Andreas Hilboll kirjoitti:
>> I'd like to have Akima interpolation in scipy.interpolate, as I
>> couldn't find any.
>
>> 1.) Did I miss something and there actually *is* an Akima
>> interpolation in scipy? 2.) Is there interest in having Akima
>> interpolation in Scipy? 3.) Does anyone have a good recommendation
>> which implementation I should consider for pulling into Scipy?
>
> 1) I don't think so, unless pchip is related.
>
> 2) Perhaps. Is it useful?

I would claim yes. Akima splines are more robust to outliers, and I
think they would make a nice addition

>
> 3) No idea.
>
> One thing to look out: based on a quick look, Akima interpolation is a
> form of spline interpolation, so it is probably possible to represent
> the result as a B-spline. If so, FITPACK's spline representation
> should be used, i.e., the same (t, c, k) format as in splrep.
>
> This allows reusing `splev` for evaluating the spline values, which
> will make life easier later on when we clean up scipy.interpolate.

I agree it would be nice to store the spline in the same tck format as
used by FITPACK. Unfortunately, all references I could find directly
compute the polynomial coefficients of the interpolants, and I couldn't
find a refernce about how to derive the B-spline coefficients, i.e., the
c, from the polynomial coefficients. I checked the bspline work by
Chuck, but there isn't any B-spline coeffient calculation from the pp
representation (yet?). Any ideas where to look?

Andreas.

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