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: misnomer@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