Hi all,

I would like to/lean to going ahead with adding these.  And in some
discussions I think that was basically the decision, so that is the
default currently.

But, I am not sure that nobody had serious disagreement about it (or
maybe the conjugation part, although I think it drops out of the
existing vecdot).

I am more seriously considering whether we should only add them to the
`numpy.linalg` namespace, while `matmul` and `vecdot` are in both
`numpy` and `numpy.linalg`.
(A bit tedious/surprising, but if not used much OK with the "See Also"
section)

- Sebastian 



On Tue, 2024-01-23 at 17:07 -0500, Marten van Kerkwijk wrote:
> Hi All,
> 
> I have a PR [1] that adds `np.matvec` and `np.vecmat` gufuncs for
> matrix-vector and vector-matrix calculations, to add to plain
> matrix-matrix multiplication with `np.matmul` and the inner vector
> product with `np.vecdot`.  They call BLAS where possible for speed.
> I'd like to hear whether these are good additions.
> 
> I also note that for complex numbers, `vecmat` is defined as `x†A`,
> i.e., the complex conjugate of the vector is taken. This seems to be
> the
> standard and is what we used for `vecdot` too (`x†x`). However, it is
> *not* what `matmul` does for vector-matrix or indeed vector-vector
> products (remember that those are possible only if the vector is
> one-dimensional, i.e., not with a stack of vectors). I think this is
> a
> bug in matmul, which I'm happy to fix. But I'm posting here in part
> to
> get feedback on that.
> 
> Thanks!
> 
> Marten
> 
> [1] https://github.com/numpy/numpy/pull/25675
> 
> p.s. Separately, with these functions available, in principle these
> could be used in `__matmul__` (and thus for `@`) and the
> specializations
> in `np.matmul` removed. But that can be a separate PR (if it is
> wanted
> at all).
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