Charles R Harris wrote:
>
>
> On 10/13/06, *A. M. Archibald* <[EMAIL PROTECTED]
> <mailto:[EMAIL PROTECTED]>> wrote:
>
> On 12/10/06, Charles R Harris <[EMAIL PROTECTED]
> <mailto:[EMAIL PROTECTED]>> wrote:
> > Hi all,
> >
> > I note that polyfit looks like it should work for single and
> double, real
> > and complex, polynomials. On the otherhand, the default rcond
> needs to
> > depend on the underlying precision. On the other, other hand,
> all the svd
> > 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 single
> > precision to start with. I also think the final degree of the
> fit should be
> > available somewhere if wanted, as it is an indication of what is
> going on.
> > Sooo, any suggestions as to what to do? My initial impulse would
> be to set
> > rcond=1e-6 for single, 1e-14 for double, make rcond a keyword,
> and kick the
> > 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?
Use the warnings framework:
>>> import warnings
>>> warnings.warn("condition number is BAD")
__main__:1: UserWarning: condition number is BAD
The user can turn warnings on or off or turned in exceptions based on a
variety of criteria. Look for the warnings filter in the docs.
Which brings up a question: do we want to have a FloatingPointWarning or
some such? Currently, if you use set the error handling to warn using
seterr a runtime warning is issued:
>>> np.seterr(all='warn')
{'over': 'ignore', 'divide': 'ignore', 'invalid': 'ignore', 'under':
'ignore'}
>>> np.arange(1) / 0
__main__:1: RuntimeWarning: divide by zero encountered in divide
On the other hand if error handling is set to 'raise', then a
FloatingPointError is issued. Is a FloatingPointWarning in order to
mirror the FloatingPointError? And if so, would it be appropriate to use
for condition number?
> I would also have to modify lstsq so it returns the degree of the fit
> which would mess up the current interface.
One approach would be to write lstsqcond (or a better name) that returns
both the fit and the condition number. listsq could then be just a
wrapper over that which dumped the condition number. IIRC, the
condition number is available, but we're not returning it.
-tim
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