[Numpy-discussion] Consider improving numpy.outer's behavior with zero-dimensional vectors
Neil Girdhar
mistersheik at gmail.com
Sat Apr 11 12:39:44 EDT 2015
I would be happy to, but I'm not sure what that involves? It's just a
documentation changelist?
On Sat, Apr 11, 2015 at 12:29 PM, Nathaniel Smith <njs at pobox.com> wrote:
> On Sat, Apr 11, 2015 at 12:06 PM, Neil Girdhar <mistersheik at gmail.com>
> wrote:
> >> On Wed, Apr 8, 2015 at 7:34 PM, Neil Girdhar <mistersheik at gmail.com>
> >> wrote:
> >> > Numpy's outer product works fine with vectors. However, I seem to
> always
> >> > want len(outer(a, b).shape) to be equal to len(a.shape) +
> len(b.shape).
> >> > Wolfram-alpha seems to agree
> >> > https://reference.wolfram.com/language/ref/Outer.html with respect to
> >> > matrix
> >> > outer products.
> >> You're probably right that this is the correct definition of the outer
> >> product in an n-dimensional world. But this seems to go beyond being
> >> just a bug in handling 0-d arrays (which is the kind of corner case
> >> we've fixed in the past); np.outer is documented to always ravel its
> >> inputs to 1d.
> >> In fact the implementation is literally just:
> >> a = asarray(a)
> >> b = asarray(b)
> >> return multiply(a.ravel()[:, newaxis], b.ravel()[newaxis,:], out)
> >> Sebastian's np.multiply.outer is much more generic and effective.
> >> Maybe we should just deprecate np.outer? I don't see what use it
> >> serves. (When and whether it actually got removed after being
> >> deprecated would depend on how much use it actually gets in real code,
> >> which I certainly don't know while typing a quick email. But we could
> >> start telling people not to use it any time.)
> >
> >
> > +1 with everything you said.
>
> Want to write a PR? :-)
>
> --
> Nathaniel J. Smith -- http://vorpus.org
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