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

[Tony S Yu]

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.

<snip>

> 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.

Thanks,
-Tony