On Do, 2015-06-04 at 18:04 -0700, Nathaniel Smith wrote:
> On Thu, Jun 4, 2015 at 5:57 PM, Nathaniel Smith <n...@pobox.com> wrote:
> > So specifically the question is -- if you have an array with five
> items, and
> > a Boolean array with three items, then currently you can use the
> later to
> > index the former:
> >
> > arr = np.arange(5)
> > mask = np.asarray([True, False, True])
> > arr[mask] # returns array([0, 2])
> >
> > This is justified by the rule that indexing with a Boolean array
> should be
> > the same as indexing with the same array that's been passed to
> np.nonzero().
> > Empirically, though, this causes constant confusion and does not
> seen very
> > useful, so the question is whether we should deprecate it.
> 
> One place where the current behavior is particularly baffling and
> annoying is when you have multiple boolean masks in the same indexing
> operation. I think everyone would expect this to index separately on
> each axis ("outer product indexing" style, like slices do), and that's
> really the only useful interpretation, but that's not what it does...:


This is not being deprecated in there for the moment, it is a different
discussion. Though maybe we can improve the error message to mention
that the array was originally boolean, has always been bugging me a bit
(it used to mention for some cases it is not anymore).

- Sebastian


> In [3]: a = np.arange(9).reshape((3, 3))
> 
> In [4]: a
> Out[4]:
> array([[0, 1, 2],
>        [3, 4, 5],
>        [6, 7, 8]])
> 
> In [6]: a[np.asarray([True, False, True]), np.asarray([False, True,
> True])]
> Out[6]: array([1, 8])
> 
> In [7]: a[np.asarray([True, False, True]), np.asarray([False, False,
> True])]
> Out[7]: array([2, 8])
> 
> In [8]: a[np.asarray([True, False, True]), np.asarray([True, True,
> True])]
> ---------------------------------------------------------------------------
> IndexError                                Traceback (most recent call
> last)
> <ipython-input-8-30b3427bec2a> in <module>()
> ----> 1 a[np.asarray([True, False, True]), np.asarray([True, True,
> True])]
> 
> IndexError: shape mismatch: indexing arrays could not be broadcast
> together with shapes (2,) (3,)
> 
> 
> -n
> 
> -- 
> Nathaniel J. Smith -- http://vorpus.org
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion

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