On 08.02.2012 15:11, Olivier Delalleau wrote: > From a user perspective, I would definitely prefer cross-product > semantics for fancy indexing. In fact, I had never used fancy indexing > with more than one array index, so the behavior described in this thread > totally baffled me. If for instance x is a matrix, I think it's > intuitive to expect x[0:2, 0:2] and x[[0, 1], [0, 1]] to return the same > data.
I think most would prefer cross-product semantics. We might be copying a bad feature of Matlab. Maybe we should just disallow fancy indexing with more than one dimension, e.g. array[X,Y] with X and Y from meshgrid. It might be that the kind of result x[[0, 1],[0, 1]] produces today is better left to a function, e.g. np.meshselect(x, *indices). Then we could just require that all arguments passed to *indices have the same shape. Sturla _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion