I think the rationale is to allow selection of whole rows / columns. If you want to choose a single element from each row/column, then, yes, you have to pass np.arange(...). There is also np.choose function, but not recommended to use for such cases as far as I understand. I'm not an expert, though. Nikolay.
> From: misno...@gmail.com > Date: Tue, 7 Apr 2015 00:49:34 +0100 > To: numpy-discussion@scipy.org > Subject: [Numpy-discussion] Multidimensional Indexing > > With the indexing example from the documentation: > > y = np.arange(35).reshape(5,7) > > Why does selecting an item from explicitly every row work as I’d expect: > >>> y[np.array([0,1,2,3,4]),np.array([0,0,0,0,0])] > array([ 0, 7, 14, 21, 28]) > > But doing so from a full slice (which, I would naively expect to mean “Every > Row”) has some…other… behaviour: > > >>> y[:,np.array([0,0,0,0,0])] > array([[ 0, 0, 0, 0, 0], > [ 7, 7, 7, 7, 7], > [14, 14, 14, 14, 14], > [21, 21, 21, 21, 21], > [28, 28, 28, 28, 28]]) > > What is going on in this example, and how do I get what I expect? By > explicitly passing in an extra array with value===index? What is the > rationale for this difference in behaviour? > > Thanks, > > Nick > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion
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