[Numpy-discussion] Sign of NaN

[josef.pktd at gmail.com]

On Tue, Sep 29, 2015 at 2:16 PM, Nathaniel Smith <njs at pobox.com> wrote:

> On Sep 29, 2015 8:25 AM, "Anne Archibald" <archibald at astron.nl> wrote:
> >
> > IEEE 754 has signum(NaN)->NaN. So does np.sign on floating-point arrays.
> Why should it be different for object arrays?
>
> The argument for doing it this way would be that arbitrary python objects
> don't have a sign, and the natural way to implement something like
> np.sign's semantics using only the "object" interface is
>
> if obj < 0:
>     return -1
> elif obj > 0:
>     return 1
> elif obj == 0:
>     return 0
> else:
>     raise
>
> In general I'm not a big fan of trying to do all kinds of guessing about
> how to handle random objects in object arrays, the kind that ends up with a
> big chain of type checks and fallback behaviors. Pretty soon we find
> ourselves trying to extend the language with our own generic dispatch
> system for arbitrary python types, just for object arrays. (The current
> hack where for object arrays np.log will try calling obj.log() is
> particularly horrible. There is no rule in python that "log" is a reserved
> method name for "logarithm" on arbitrary objects. Ditto for the other
> ufuncs that implement this hack.)
>
> Plus we hope that many use cases for object arrays will soon be supplanted
> by better dtype support, so now may not be the best time to invest heavily
> in making object arrays complicated and powerful.
>
> OTOH sometimes practicality beats purity, and at least object arrays are
> already kinda cordoned off from the rest of the system, so I don't feel as
> strongly as if we were talking about core functionality.
>
> ...is there a compelling reason to even support np.sign on object arrays?
> This seems pretty far into the weeds, and that tends to lead to poor
> intuition and decision making.
>

One of the usecases that has sneaked in during the last few numpy versions
is that object arrays contain numerical arrays where the shapes don't add
up to a rectangular array.
In those cases being able to apply numerical operations might be useful.

But I'm +0 since I don't work with object arrays.

Josef



> -n
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20150929/95c21ec2/attachment.html>