[Numpy-discussion] Inconsistency with __index__() for rank-1 arrays?
Travis Oliphant
oliphant@enthought....
Thu Oct 28 23:34:52 CDT 2010
The __index__ method returns an integer from an array.
The current behavior follows the idea of "return an integer if there is 1-element in the array"
Your suggestion is to only return an integer if it is a rank-0 array, otherwise raise an error.
This could potentially be changed in NumPy 2.0. I'm +0 on the suggestion.
-Travis
On Oct 27, 2010, at 9:34 AM, Francesc Alted wrote:
> Hi,
>
> 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 this behaviour is this:
>
>>>> 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: # (as per PEP 357)
> 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 that would raise a ``TypeError``?
>
> Thanks,
>
> --
> Francesc Alted
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---
Travis Oliphant
Enthought, Inc.
oliphant@enthought.com
1-512-536-1057
http://www.enthought.com
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