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]).
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
--
"And it's much the same thing with knowledge, for whenever you learn
something new, the whole world becomes that much richer."
-- The Princess of Pure Reason, as told by Norton Juster in The Phantom
Tollbooth
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