On Tue, Feb 7, 2012 at 10:41 AM, Sturla Molden <stu...@molden.no> wrote: > It's the combination of a single index and fancy indexing that does > this, not the slicing.
There are some quirks in the broadcasting machinery that makes it almost impossible to guess what the outcome of mixed indexing is going to be. The safest is to stick either to slicing or to fancy indexing, e.g. In [64]: idx1 = np.arange(x.shape[1])[:, None] In [65]: idx2 = np.array([False, True, False, True]) In [66]: idx1.shape, idx2.shape Out[66]: ((3, 1), (4,)) In [67]: np.broadcast_arrays(idx1, idx2)[0].shape Out[67]: (3, 4) The output will be (.., 3, 4), except that idx2 only has two True elements, so (..., 3, 2). In [68]: x[0, idx1, idx2].shape Out[68]: (3, 2) Regards Stéfan _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
