Sturla Molden wrote: > >>> x = numpy.arange(100).reshape((1,10,10)) > > >>> x[0,:,numpy.arange(5)].shape > (5, 10) > > >>> x[:,:,numpy.arange(5)].shape > (1, 10, 5) > > > It looks like a bug that needs to be squashed. >
These are both correct. See my previous posts about the rule. The first case is exactly the example we saw before: we start with a (1,10,10)-shaped array and replace the first and last-dimension (1,10)-shaped array with a (5,)-shaped array. Not having a clear place to put the extracted (5,)-shaped subspace, it is tacked on to the front. In the second example, the last-dimension (10,)-shaped sub-space is replaced with a (5,)-shaped sub-space. There is no ambiguity in this case and the result is a (1,10,5)-shaped array. There is no bug here. Perhaps unexpected behavior with "advanced indexing" combined with single-integer indexing in separated dimensions but no bug. The result, does follow an understandable and generalizable rule. In addition, you can get what you seem to want very easily using x[0][:,numpy.arange(5)] -Travis _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
