[SciPy-User] Cubic splines - MATLAB vs Scipy.interpolate
Tue Sep 27 18:50:45 CDT 2011
On Tue, Sep 27, 2011 at 7:27 PM, Charles R Harris
> On Tue, Sep 27, 2011 at 2:27 PM, Zachary Pincus <email@example.com>
>> scipy.signal has some cubic and quadratic spline functions:
>> (and replace the c with q for the quadratic versions).
>> I have no idea how fast they are, or if they're at all drop-in
>> replacements for the matlab ones. The stuff in scipy.interpolate is
>> powerful, but the fitpack spline-fitting operations can be a bit
>> input-sensitive and prone to strange ringing.
>> On Sep 27, 2011, at 3:32 PM, Charles R Harris wrote:
>> > On Tue, Sep 27, 2011 at 1:04 PM, Jaidev Deshpande
>> > <firstname.lastname@example.org> wrote:
>> > Hi
>> > The big question: Why does the MATLAB function spline operate faster
>> > than the cubic spline alternatives in Scipy, especially splrep and splev ?
>> > ------
>> > The context: I'm working on an algorithm that bottlenecks on spline
>> > interpolation.
>> > Some functions in Scipy return an interpolation object function
>> > depending on the input data which needs to be evaluated independently over
>> > the whole range.
>> > So I used 'lower order' functions like splrep and splev. Even that was
>> > too slow.
>> > Then I tried to write my own code for cubic splines, generating and
>> > solving a system of 4N simultaneous equations for interpolation between N+1
>> > points.
>> > No matter what I do, the code is quite slow. How come the MATLAB
>> > function spline operate so fast? What am I missing? What can I do to speed
>> > it up?
>> > I suspect it is because the scipy routines you reference are based on
>> > b-splines, which are needed for least squares fits. Simple cubic spline
>> > interpolation through a give set of points tends to be faster and I believe
>> > that is what the Matlab spline function does. To get b-splines in Matlab you
>> > need one of the toolboxes, it doesn't come with the core. I don't think
>> > scipy has a simple cubic spline interpolation, but I may be wrong.
> I believe the splines in signal are periodic and the boundary conditions
> aren't flexible. The documentation is, um..., well, they are effectively
> undocumented. We really need better spline support in scipy.
I thought the main difference of the signal compared to interpolate
splines is that they work only on a regular grid.
They have a smoothing coefficient lambda, so they don't seem to be
pure interpolating splines.
(I never looked at them because of the regular grid restriction.)
matlab's spline has x and Y, but all the examples in the help have regular grid.
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