On Mo, 2015-11-30 at 18:42 +0100, Lluís Vilanova wrote: > Hi, > > TL;DR: There's a pending pull request deprecating some behaviour I find > unexpected. Does anyone object? > > Some time ago I noticed that numpy yields unexpected results in some very > specific cases. An array can be used to index multiple elements of a single > dimension: > > >>> a = np.arange(8).reshape((2,2,2)) > >>> a[ np.array([[0], [0]]) ] > array([[[[0, 1], > [2, 3]]], > [[[0, 1], > [2, 3]]]]) > > Nonetheless, if a list is used instead, it is (unexpectedly) transformed into > a > tuple, resulting in indexing across multiple dimensions: > > >>> a[ [[0], [0]] ] > array([[0, 1]]) > > I.e., it is interpeted as: > > >>> a[ [0], [0] ] > array([[0, 1]]) > > Or what is the same: > > >>> a[( [0], [0] )] > array([[0, 1]]) > > > I've been informed that there's a pending pull request that deprecates this > behaviour [1], which could in the future be reverted to what is expected (at > least what I expect) from the documents (except for an obscure note in [2]). >
Obviously, I am not against this ;). I have to admit it worries me a bit, because there is quite a bit of code doing things like: >>> slice_object = [slice(None)] * 5 >>> slice_object[2] = 3 >>> arr[slice_object] and all of this code (numpy also has a lot of it), will probably have to change the last line to be: >>> arr[tuple(slice_object)] So the implication of this might actually be more farther reaching then one might think at first; or at least require quite a lot of code to be touched (inside numpy that is no problem, but outside). - Sebastian > The discussion leading to this mail can be found here [3]. > > [1] https://github.com/numpy/numpy/pull/4434 > [2] > http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#advanced-indexing > [3] https://github.com/numpy/numpy/issues/6564 > > > Thanks, > Lluis >
signature.asc
Description: This is a digitally signed message part
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
