On Mon, Mar 4, 2013 at 4:53 PM, Aron Ahmadia <[email protected]> wrote:
> Interesting, that question would probably have gotten a different response > on scicomp, it is a pity we are not attracting more questions there! > > I know there are two polyfit modules in numpy, one in numpy.polyfit, the > other in numpy.polynomial, the functionality you are suggesting seems to > fit in either. > > What parameters/functionality are you considering adding? > Well, you need two more array-likes, x_fixed and y_fixed, which could probably be fed to polyfit as an optional tuple parameter: polyfit(x, y, deg, fixed_points=(x_fixed, y_fixed)) The standard return would still be the deg + 1 coefficients of the fitted polynomial, so the workings would be perfectly backwards compatible. An optional return, either when full=True, or by setting an additional lagrange_mult=True flag, could include the values of the Lagrange multipliers calculated during the fit. Jaime > A > > > On Mon, Mar 4, 2013 at 7:23 PM, Jaime Fernández del Río < > [email protected]> wrote: > >> A couple of days back, answering a question in StackExchange ( >> http://stackoverflow.com/a/15196628/110026), I found myself using >> Lagrange multipliers to fit a polynomial with least squares to data, making >> sure it went through some fixed points. This time it was relatively easy, >> because some 5 years ago I came across the same problem in real life, and >> spent the better part of a week banging my head against it. Even knowing >> what you are doing, it is far from simple, and in my own experience very >> useful: I think the only time ever I have fitted a polynomial to data with >> a definite purpose, it required that some points were fixed. >> >> Seeing that polyfit is entirely coded in python, it would be relatively >> straightforward to add support for fixed points. It is also something I >> feel capable, and willing, of doing. >> >> * Is such an additional feature something worthy of investigating, or >> will it never find its way into numpy.polyfit? >> * Any ideas on the best syntax for the extra parameters? >> >> Thanks, >> >> Jaime >> >> -- >> (\__/) >> ( O.o) >> ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes >> de dominación mundial. >> >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.
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