[Numpy-discussion] Allowing broadcasting of code dimensions in generalized ufuncs

[Marten van Kerkwijk]

Hi All,

The discussion on the gufunc signature enhancements seems to have stalled a
bit, but while it was going I've tried to update the NEP correspondingly.
The NEP is now merged, so can viewed more easily, at
http://www.numpy.org/neps/nep-0020-gufunc-signature-enhancement.html

My own quite possibly biased summary of the discussion so far is that:

1) Frozen dimensions are generally seen as a good idea; other
implementations may be possible, but are not as clear.

2) Flexible dimensions have little use beyond matmul; the main discussion
is whether there is a better way. In my opinion, the main benefit of the
current proposal is that it allows operator overrides to all work the same
way (via __array_ufunc__), independent of any assumptions about the object
that does the override (such as that it has a shape).

3) Broadcastable dimensions had less support, but mostly for lack of
examples; there now is one beyond all_equal, for which a gufunc is more
clearly the proper route: a weighted average (which has obvious extensions).

A general benefit of course is that there is actual code for all three; it
would certainly be nice if we could fully support `matmul` and `@` in 1.16.

So, the question would seem whether the NEP should be accepted or rejected
(with part acceptance of course being possible, though I note that flexible
and broadcastable share a lot of implementation, so in my opinion it is
somewhat pointless to do just one of them).

All the best,

Marten
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