[SciPy-User] Splines in scipy.signal vs scipy.interpolation

Zachary Pincus zachary.pincus@yale....
Tue Feb 9 11:05:12 CST 2010

> Local splines are very simple, and the only kind I use.
> Global / least-squares-weighted splines
> which depend or more points are common;
> they're smoother (C2) but can surprise you  (see extrapolation
> plot ...)
> scipy.interpolate wraps fitpack which does least-squares weighting,
> don't know how.
> Of local splines, two kinds are common:
>    - interpolating: Catmull-Rom
>    - smoothing: B-spline.

I had always thought that the splines produced by fitpack were plain  
(and local) non-uniform B-splines (as opposed to the uniform kind,  
which Denis's really helpful demo code uses). However, the way that  
those B-splines are fit to the given data by fitpack is definitely  
global and can lead to odd artifacts if you're incautious.

Is this correct?

Then is reason that the B-splines from scipy.interpolate.fitpack and  
from scipy.signal are a bit different is that the latter are also  
strictly uniform? (E.g. evenly-spaced knot vector.) Probably this is  
easy to test...


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