[NumPy-Tickets] [NumPy] #1651: Inconsistency with __index__() for rank-1 arrays?

[NumPy Trac]

#1651: Inconsistency with __index__() for rank-1 arrays?
--------------------+-------------------------------------------------------
 Reporter:  faltet  |       Owner:  somebody
     Type:  defect  |      Status:  new     
 Priority:  normal  |   Milestone:  2.0.0   
Component:  Other   |     Version:  1.5.0   
 Keywords:          |  
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 I find this a bit misleading:

 {{{
 >>> a = np.arange(10)

 >>> a[np.array(0)]
 0

 >>> a[np.array([0])]
 array([0])

 >>> a[[0]]
 array([0])
 }}}

 But, for regular python lists we have:

 {{{
 >>> l = a.tolist()

 >>> l[np.array(0)]
 0

 >>> l[np.array([0])]
 0
 }}}

 i.e. indexing with a rank-0 array and a rank-1 array with one single
 element return the same result, which I find inconsistent with the
 expected behaviour for this case, i.e.:

 {{{
 >>> l[[0]]
 ---------------------------------------------------------------------------
 TypeError                                 Traceback (most recent call
 last)

 /tmp/tables-2.2/<ipython console> in <module>()

 TypeError: list indices must be integers, not list
 }}}

 The ultimate reason for all of this is:

 {{{
 >>> np.array(0).__index__()
 0

 >>> np.array([0]).__index__()
 0
 }}}

 But I wonder why !NumPy needs the latter behaviour, instead of the more
 logical:

 {{{
 >>> np.array([0]).__index__()
 ---------------------------------------------------------------------------
 TypeError                                 Traceback (most recent call
 last)

 /tmp/tables-2.2/<ipython console> in <module>()

 TypeError: only rank-0 integer arrays can be converted to an index
 }}}

 This inconsistency has indeed introduced a bug in my application and for
 solving this I'd need something like:

 {{{
 def is_idx(index):
     """Check if an object can work as an index or not."""

     if hasattr(index, "__index__"):  # Only works on Python 2.5 on
         if (hasattr(index, "shape") and index.shape == (1,)):
             return False
         try:
             idx = index.__index__()
             return True
         except TypeError:
             return False

     return False
 }}}

 i.e. for determining if an object can be an index or not, I need to
 explicitly check for a shape different from (1,), which is unnecessarily
 complicated.

 So I find the current behaviour prone to introduce errors in apps and I'm
 wondering why exactly {{{np.array([1])}}} should work as an index at all.
 It would not be better if {{{np.array([1]).__index__()}}} would raise a
 `TypeError`?

 Thanks

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1651>
NumPy <http://projects.scipy.org/numpy>
My example project