rcond in polyfit
A. M. Archibald
peridot.faceted at gmail.com
Fri Oct 13 16:07:55 CDT 2006
On 13/10/06, Charles R Harris <charlesr.harris at gmail.com> wrote:
> On 10/13/06, A. M. Archibald <peridot.faceted at gmail.com> wrote:
> > On 12/10/06, Charles R Harris <charlesr.harris at gmail.com> wrote:
> > > Hi all,
> > >
> > > I note that polyfit looks like it should work for single and double,
> > > and complex, polynomials. On the otherhand, the default rcond needs to
> > > depend on the underlying precision. On the other, other hand, all the
> > > computations are done with dgelsd or zgelsd, i.e., double precision.
> Even so
> > > problems can arise from inherent errors of the input data if it is
> > > precision to start with. I also think the final degree of the fit should
> > > available somewhere if wanted, as it is an indication of what is going
> > > Sooo, any suggestions as to what to do? My initial impulse would be to
> > > rcond=1e-6 for single, 1e-14 for double, make rcond a keyword, and kick
> > > can down the road on returning the actual degree of the fit.
> > I'd also be inclined to output a warning (which the user can ignore,
> > read or trap as necessary) if the condition number is too bad or they
> > supplied an rcond that is too small for the precision of their data.
> That sounds good, but how to do it? Should I raise an exception? I would
> also have to modify lstsq so it returns the degree of the fit which would
> mess up the current interface.
Python's warnings module is a decent solution for providing this
information. Goodness-of-fit worries me less than ill-conditioning -
users are going to expect the curve to deviate from their function
(and an easy reliable way to get goodness of fit is
sqrt(sum(abs(f(xs)-polynomial(xs))**2)); this is certain to take into
account any roundoff errors introduced anywhere). But they may well
have no idea they should be worried about the condition number of some
matrix they've never heard of.
A. M. Archibald
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