[Numpy-discussion] polyfit with fixed points
Tue Mar 5 09:50:34 CST 2013
If you are going to work on this, you should also take a look at the recent
which is about the weighting function, which is in a confused state in the
current version of polyfit. By the way, Numerical Recipes has a nice
discussion both about fixing parameters and about weighting the data in
different ways in polynomial least squares fitting.
On Mon, Mar 4, 2013 at 7:23 PM, Jaime Fernández del Río <
> 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?
> ( O.o)
> ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes
> de dominación mundial.
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