On Mo, 2016-08-08 at 15:11 +0200, Anakim Border wrote: > Dear List, > > I'm experimenting with views and array indexing. I have written two > code blocks that I was expecting to produce the same result. > > First try: > > >>> a = np.arange(10) > >>> b = a[np.array([1,6,5])] > >>> b += 1 > >>> a > array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) > > > Alternative version: > > >>> a = np.arange(10) > >>> a[np.array([1,6,5])] += 1 > >>> a > array([0, 2, 2, 3, 4, 6, 7, 7, 8, 9]) > > > I understand what is happening in the first case. In fact, the > documentation is quite clear on the subject: > > For all cases of index arrays, what is returned is a copy of the > original data, not a view as one gets for slices. > > What about the second case? There, I'm not keeping a reference to the > intermediate copy (b, in the first example). Still, I don't see why > the update (to the copy) is propagating to the original array. Is > there any implementation detail that I'm missing? >
The second case translates to: tmp = a[np.array([1,6,5])] + 1 a[np.array([1,6,5])] = tmp this is done by python, without any interplay of numpy at all. Which is different from `arr += 1`, which is specifically defined and translates to `np.add(arr, 1, out=arr)`. - Sebastian > Best, > ab > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion
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