[Numpy-discussion] Adding .abs() method to the array object

Todd toddrjen@gmail....
Tue Feb 26 04:16:47 CST 2013


On Tue, Feb 26, 2013 at 10:58 AM, Sebastian Berg <sebastian@sipsolutions.net
> wrote:

> On Mon, 2013-02-25 at 22:04 -0500, josef.pktd@gmail.com wrote:
> > On Mon, Feb 25, 2013 at 9:58 PM,  <josef.pktd@gmail.com> wrote:
> > > On Mon, Feb 25, 2013 at 9:20 PM, Sebastian Berg
> > > <sebastian@sipsolutions.net> wrote:
> > >> On Mon, 2013-02-25 at 10:50 -0500, Skipper Seabold wrote:
> > >>> On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki <mail.till@gmx.de>
> > >>> wrote:
> > >>> >
> > >>> > First, sorry that i didnt search for an old thread, but because i
> > >>> disagree with
> > >>> > conclusion i would at least address my reason:
> > >>> >
> <snip>
> > >> Two small things (not sure if it matters much). But first almost all
> of
> > >> these methods are related to the container and not the elements.
> Second
> > >> actually using a method arr.abs() has a tiny pitfall, since abs would
> > >> work on numpy types, but not on python types. This means that:
> > >>
> > >> np.array([1, 2, 3]).max().abs()
> > >>
> > >> works, but
> > >>
> > >> np.array([1, 2, 3], dtype=object).max().abs()
> > >>
> > >> breaks. Python has a safe name for abs already...
> > >
> > >>>> (np.array([1, 2, 3], dtype=object)).max()
> > > 3
> > >>>> (np.array([1, 2, 3], dtype=object)).__abs__().max()
> > > 3
> > >>>> (np.array([1, 2, '3'], dtype=object)).__abs__()
> > > Traceback (most recent call last):
> > >   File "<stdin>", line 1, in <module>
> > > TypeError: bad operand type for abs(): 'str'
> > >
> > >>>> map(abs, [1, 2, 3])
> > > [1, 2, 3]
> > >>>> map(abs, [1, 2, '3'])
> > > Traceback (most recent call last):
> > >   File "<stdin>", line 1, in <module>
> > > TypeError: bad operand type for abs(): 'str'
> >
> > or maybe more useful
> >
> > >>> from decimal import Decimal
> > >>> d = [Decimal(str(k)) for k in np.linspace(-1, 1, 5)]
> > >>> map(abs, d)
> > [Decimal('1.0'), Decimal('0.5'), Decimal('0.0'), Decimal('0.5'),
> Decimal('1.0')]
> >
> > >>> np.asarray(d).__abs__()
> > array([1.0, 0.5, 0.0, 0.5, 1.0], dtype=object)
> > >>> np.asarray(d).__abs__()[0]
> > Decimal('1.0')
> >
> > Josef
> >
> > >
> > > I don't see a difference.
> > >
> > > (I don't expect to use max abs on anything else than numbers.)
> > >
>
> The difference is about scalars only. And of course __abs__ is fine, but
> if numpy adds an abs method, its scalars would logically have it too.
> But then you diverge from python scalars. That has exactly the downside
> that you may write code that suddenly stops working for python scalars
> without noticing.
>
> I turned around the abs and max order here, so that the abs works on the
> scalar, not useful but just as an example.
>

But doesn't this also apply to many existing methods?
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