[SciPy-user] Does scipy have a function to...?
Clinton Allen
clintonwallen at gmail.com
Mon Sep 25 17:57:44 CDT 2006
You might look at Chebyshev polynomials. They have a "min-max of the error"
property. One place to start is
http://mathworld.wolfram.com/ChebyshevApproximationFormula.html
Don't know if there's any python code for using these.
--Clinton
On 9/25/06, Robert Kern <robert.kern at gmail.com> wrote:
>
> Bill Dandreta wrote:
> > What I want is a smooth curve that serves as an upper limit for a data
> > plot. I would like it to be close to the data at the local maxima.
> >
> > Does such a function exist?
>
> No, not really. It would be quite tricky to construct such a beast. At the
> one
> end would be a complete interpolating curve that goes through every point;
> however, this will almost certainly not be as "smooth" as you want it. You
> would
> need to choose the length scale at which variations in the data are
> ignored.
> E.g. you need to find some means of determining why the curve should skip
> over A
> but try to get close to B.
>
> ________
> /* *\
> / A \
> * \_______
> *B
>
> Possibly limiting the order of an interpolating polynomial or spline will
> be
> sufficient.
>
> You might be able to formulate this as a constrained minimization problem
> using
> scipy.optimize.fmin_cobyla(). Take some curve f(x), minimize (f(x) - y)
> under
> the constraint (f(x) - y >= 0).
>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma
> that is made terrible by our own mad attempt to interpret it as though
> it had
> an underlying truth."
> -- Umberto Eco
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