Depends on how big your array is. Numpy C code is 150x+ faster than python overhead. Fancy indexing can be expensive in my experience. Without trying I'd guess arr[:, argmax(arr, axis=1)] does what you want, but even if it is, try profiling the two and see. I highly doubt such would be even 1% of your run time, but it depends on what your doing. Part of python with numpy is slightly not caring about big O because trying to be clever is rarely worth it in my experience.
On Thu, Oct 31, 2019 at 12:35 AM Daniele Nicolodi <dani...@grinta.net> wrote: > On 30/10/2019 22:42, Elliot Hallmark wrote: > > I wouldn't be surprised at all if calling max in addition to argmax > > wasn't as fast or faster than indexing the array using argmax. > > Regardless, just use that then profile when you're done with the > > whole thing and see if there's any gains to be made. Very likely not > here. > > Hi Elliot, > > how do you arrive at this conclusion? np.argmax() and np.max() are O(N) > while indexing is O(1) thus I don't see how you can conclude that > running both np.argmax() and np.max() on the input array is going to > incur in a small penalty compared to running np.argmax() and then indexing. > > Cheers, > Dan > > > > > > -elliot > > > > On Wed, Oct 30, 2019, 10:32 PM Daniele Nicolodi <dani...@grinta.net > > <mailto:dani...@grinta.net>> wrote: > > > > On 30/10/2019 19:10, Neal Becker wrote: > > > max(axis=1)? > > > > Hi Neal, > > > > I should have been more precise in stating the problem. Getting the > > values in the array for which I'm looking at the maxima is only one > step > > in a more complex piece of code for which I need the indexes along > the > > second axis of the array. I would like to avoid to have to iterate > the > > array more than once. > > > > Thank you! > > > > Cheers, > > Dan > > > > > > > On Wed, Oct 30, 2019, 7:33 PM Daniele Nicolodi <dani...@grinta.net > > <mailto:dani...@grinta.net> > > > <mailto:dani...@grinta.net <mailto:dani...@grinta.net>>> wrote: > > > > > > Hello, > > > > > > this is a very basic question, but I cannot find a satisfying > > answer. > > > Assume a is a 2D array and that I get the index of the maximum > > value > > > along the second dimension: > > > > > > i = a.argmax(axis=1) > > > > > > Is there a better way to get the value of the maximum array > > entries > > > along the second axis other than: > > > > > > v = a[np.arange(len(a)), i] > > > > > > ?? > > > > > > Thank you. > > > > > > Cheers, > > > Daniele > > > _______________________________________________ > > > NumPy-Discussion mailing list > > > NumPy-Discussion@python.org > > <mailto:NumPy-Discussion@python.org> > > <mailto:NumPy-Discussion@python.org > > <mailto:NumPy-Discussion@python.org>> > > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > > > > > > _______________________________________________ > > > NumPy-Discussion mailing list > > > NumPy-Discussion@python.org <mailto:NumPy-Discussion@python.org> > > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org <mailto: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 > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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