2009/3/12 Robert Kern <robert.k...@gmail.com>: >> idx = np.array([0,1]) >> e = x[0,:,idx] >> print e.shape >> >> #-----> return (2,3). I think the right answer should be (3,2). Is >> # it a bug here? my numpy version is 1.2.1. > > It's certainly weird, but it's working as designed. Fancy indexing via > arrays is a separate subsystem from indexing via slices. Basically, > fancy indexing decides the outermost shape of the result (e.g. the > leftmost items in the shape tuple). If there are any sliced axes, they > are *appended* to the end of that shape tuple.
This was my understanding, but now I see: In [31]: x = np.random.random([4,5,6,7]) In [32]: idx = np.array([1,2]) In [33]: x[:, idx, idx, :].shape Out[33]: (4, 2, 7) Cheers Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
