https://github.com/numpy/numpy/issues/8708 is a proposal to add such a function, with an implementation in https://github.com/numpy/numpy/pull/8714
Eric On Mon, 26 Mar 2018 at 11:35 Benjamin Root <ben.v.r...@gmail.com> wrote: > Ah, yes, I should have thought about that. Kind of seems like something > that we could make `np.take()` do, somehow, for something that is easier to > read. > > Thank you! > Ben Root > > > On Mon, Mar 26, 2018 at 2:28 PM, Robert Kern <robert.k...@gmail.com> > wrote: > >> On Mon, Mar 26, 2018 at 11:24 AM, Benjamin Root <ben.v.r...@gmail.com> >> wrote: >> > >> > I seem to be losing my mind... I can't seem to get this to work right. >> > >> > I have a (N, k) array `distances` (along with a bunch of other arrays >> of the same shape). I need to resort the rows, so I do: >> > >> > indexs = np.argsort(distances, axis=1) >> > >> > How do I use this index array correctly to get back distances sorted >> along rows? Note, telling me to use `np.sort()` isn't going to work because >> I need to apply the same indexing to a couple of other arrays. >> > >> > new_dists = distances[indexs] >> > >> > gives me a (N, k, k) array, while >> > >> > new_dists = np.take(indexs, axis=1) >> > >> > gives me a (N, N, k) array. >> > >> > What am I missing? >> >> Broadcasting! >> >> new_dists = distances[np.arange(N)[:, np.newaxis], indexs] >> >> -- >> Robert Kern >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@python.org >> https://mail.python.org/mailman/listinfo/numpy-discussion >> >> > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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