[SciPy-User] Splines in scipy.signal vs scipy.interpolation
Tony S Yu
Tue Feb 9 11:47:18 CST 2010
On Feb 9, 2010, at 11:46 AM, denis wrote:
> Tony, Dag Sverre,
> let me try to give a bit of notation and background
> (as far as I know -- experts please correct me):
> - interpolating spline: goes through the data points
> - smoothing spline: may not.
> So after all that, a menu for splines:
> - interpolating / smoothing
> - local / various global
> - work on Nxk reals / work on anything numpy
> - 1d as above, 2d image processing
> - derivatives
> - Bezier curves with control points
Thanks Denis! Reading through this explanation has helped a lot (although I'll need to spend more time understanding everything in it).
I'm still a bit confused on what seems to be subclasses of smoothing splines: 1) those with points or knots at the x-values (but not necessarily the y-values) of original data points and 2) those with fewer points than the original data (which is what scipy.interpolate provides). Is there a term for these subclasses? I'm having a difficult time distinguishing the two in the literature.
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