Why do these belong in NumPy? What is the broad field of application of these functions? And, does a more general concept underpin them? Thanks, Alan Isaac
On Tue, Jan 23, 2024 at 5:17 PM Marten van Kerkwijk <m...@astro.utoronto.ca> 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). > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: alan.is...@gmail.com >
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