[Numpy-discussion] Consider improving numpy.outer's behavior with zero-dimensional vectors

[Neil Girdhar]

Okay, but by the same token, why do we have cumsum?  Isn't it identical to

np.add.accumulate

— or if you're passing in multidimensional data —

np.add.accumulate(a.flatten())

?

add.accumulate feels more generic, would make the other ufunc things more
discoverable, and is self-documenting.

Similarly, cumprod is just np.multiply.accumulate.

Best,

Neil


On Sat, Apr 11, 2015 at 12:49 PM, Nathaniel Smith <njs at pobox.com> wrote:

> Documentation and a call to warnings.warn(DeprecationWarning(...)), I
> guess.
>
> On Sat, Apr 11, 2015 at 12:39 PM, Neil Girdhar <mistersheik at gmail.com>
> wrote:
> > 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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> >> NumPy-Discussion at scipy.org
> >> http://mail.scipy.org/mailman/listinfo/numpy-discussion
> >
> >
> >
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>
>
>
> --
> Nathaniel J. Smith -- http://vorpus.org
> _______________________________________________
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