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

[Neil Girdhar]

Would it be possible to deprecate np.outer's usage on non one-dimensional
vectors for a few versions, and then reintroduce it with definition
np.outer == np.multiply.outer?

On Wed, Apr 15, 2015 at 8:02 PM, <josef.pktd at gmail.com> wrote:

> On Wed, Apr 15, 2015 at 6:40 PM, Nathaniel Smith <njs at pobox.com> wrote:
> > On Wed, Apr 15, 2015 at 6:08 PM,  <josef.pktd at gmail.com> wrote:
> >> On Wed, Apr 15, 2015 at 5:31 PM, Neil Girdhar <mistersheik at gmail.com>
> wrote:
> >>> Does it work for you to set
> >>>
> >>> outer = np.multiply.outer
> >>>
> >>> ?
> >>>
> >>> It's actually faster on my machine.
> >>
> >> I assume it does because np.corrcoeff uses it, and it's the same type
> >> of use cases.
> >> However, I'm not using it very often (I prefer broadcasting), but I've
> >> seen it often enough when reviewing code.
> >>
> >> This is mainly to point out that it could be a popular function (that
> >> maybe shouldn't be deprecated)
> >>
> >> https://github.com/search?utf8=%E2%9C%93&q=np.outer
> >> 416914
> >
> > For future reference, that's not the number -- you have to click
> > through to "Code" and then look at a single-language result to get
> > anything remotely meaningful. In this case b/c they're different by an
> > order of magnitude, and in general because sometimes the "top line"
> > number is completely made up (like it has no relation to the
> > per-language numbers on the left and then changes around randomly if
> > you simply reload the page).
> >
> > (So 29,397 is what you want in this case.)
> >
> > Also that count then tends to have tons of duplicates (e.g. b/c there
> > are hundreds of copies of numpy itself on github), so you need a big
> > grain of salt when looking at the absolute number, but it can be
> > useful, esp. for relative comparisons.
>
> My mistake, rushing too much.
> github show only 25 code references in numpy itself.
>
> in quotes, python only  (namespace conscious packages on github)
> (I think github counts modules not instances)
>
> "np.cumsum" 11,022
> "np.cumprod" 1,290
> "np.outer" 6,838
>
> statsmodels
> "np.cumsum" 21
> "np.cumprod"  2
> "np.outer" 15
>
> Josef
>
> >
> > -n
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