[SciPy-Dev] SciPy Goal
Mon Jan 9 05:37:02 CST 2012
05.01.2012 04:16, Zachary Pincus kirjoitti:
> Just one point here: one of the current shortcomings in scipy
> from my perspective is interpolation, which is spread between
> interpolate, signal, and ndimage, each package with strengths
> and inexplicable (to a new user) weaknesses.
Interpolation and splines are indeed a weak point currently.
What's missing is:
- interface for interpolating gridded data (unifying ndimage,
RectBivariateSpline, and scipy.spline routines)
- the interface for `griddata` could be simplified a bit
(-> allow variable number of arguments). Also, no natural neighbor
interpolation so far.
- FITPACK is a quirky beast, especially its 2D-routines (apart from
RectBivariateSpline) which very often don't work for real data.
I'm also not fully sure how far it and its smoothing can be trusted
in 1D (see stackoverflow)
- There are two sets of incompatible spline routines in
scipy.interpolate, which should be cleaned up.
The *Spline class interfaces are also not very pretty, as there is
__class__ changing magic going on.
The interp2d interface is somewhat confusing, and IMO would be best
- There is also a problem with large 1D data sets: FITPACK is slow, and
the other set of spline routines try to invert a dense matrix,
rather than e.g. using the band matrix routines.
- RBF sort of works, but uses dense matrices and is not suitable for
large data sets. IDW interpolation could be an useful addition here.
And probably more: making a laundry list of what to fix could be helpful.
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