I believe this line is the reason: https://github.com/numpy/numpy/blob/c0e48cfbbdef9cca954b0c4edd0052e1ec8a30aa/numpy/core/src/multiarray/item_selection.c#L2110
On Thu, Dec 17, 2015 at 11:52 AM, Raghav R V <rag...@gmail.com> wrote: > I was just playing with `count_nonzero` and found it to be significantly > faster for boolean arrays compared to integer arrays > > > >>> a = np.random.randint(0, 2, (100, 5)) > >>> a_bool = a.astype(bool) > > >>> %timeit np.sum(a) > 100000 loops, best of 3: 5.64 µs per loop > > >>> %timeit np.count_nonzero(a) > 1000000 loops, best of 3: 1.42 us per loop > > >>> %timeit np.count_nonzero(a_bool) > 1000000 loops, best of 3: 279 ns per loop (but why?) > > I tried looking into the code and dug my way through to this line > <https://github.com/numpy/numpy/blob/c0e48cfbbdef9cca954b0c4edd0052e1ec8a30aa/numpy/core/src/multiarray/item_selection.c#L2172>. > I am unable to dig further. > > I know this is probably a trivial question, but was wondering if anyone > could provide insight on why this is so? > > Thanks > > R > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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