[Numpy-discussion] proposal: min, max of complex should give warning

Ralf Gommers ralf.gommers at gmail.com
Tue Dec 31 11:24:05 EST 2013


On Tue, Dec 31, 2013 at 4:52 PM, Neal Becker <ndbecker2 at gmail.com> wrote:

> Cera, Tim wrote:
>
> > I don't work with complex numbers, but just sampling what others do:
> >
> >
> > Python: no ordering, results in TypeError
> >
> > Matlab: sorts by magnitude
> > http://www.mathworks.com/help/matlab/ref/sort.html
> >
> > R: sorts first by real, then by imaginary
> > http://stat.ethz.ch/R-manual/R-patched/library/base/html/sort.html
> >
> > Numpy: sorts first by real, then by imaginary (the documentation link
> > below calls this sort 'lexicographical' which I don't think is
> > correct)
> > http://docs.scipy.org/doc/numpy/reference/generated/numpy.sort.html
> >
> >
> > I would think that the Matlab sort might be more useful, but easy
> > enough by using the absolute value.
> >
> > I think what Numpy does is normal enough to not justify a warning, but
> > leave this to others because as I pointed out in the beginning I don't
> > work with complex numbers.
> >
> > Kindest regards,
> > Tim
>
> But I'm not proposing to change numpy's result, which I'm sure would raise
> many
> objections.  I'm just asking to give a warning, because I think in most
> cases
> this is actually a mistake on the user's part.  Just like the warning
> currently
> given when complex data are truncated to real part.
>

Keep in mind that warnings can be highly annoying. If you're a user who
uses this functionality regularly (and you know what you're doing), then
you're going to be very unhappy to have to wrap each function call in:
    olderr = np.seterr(all='ignore')
    max(...)
    np.seterr(**olderr)
or in:
    with warnings.catch_warnings():
        warnings.filterwarnings('ignore', ...)
        max(...)

The actual behavior isn't documented now it looks like, so that should be
done. In the Notes section of max/min probably.

As for your proposal, it would be good to know if adding a warning would
actually catch any bugs. For the truncation warning it caught several in
scipy and other libs IIRC.

Ralf
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