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 > >
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