On Mon, Jun 25, 2018 at 11:29 PM Andrew Nelson wrote:
> On Tue, 26 Jun 2018 at 16:24, Juan Nunez-Iglesias
> wrote:
>
>> > Plain indexing arr[...] should return an error for ambiguous cases.
>> [...] This includes every use of vectorized indexing with multiple integer
>> arrays.
>>
>> This line c
On Tue, 26 Jun 2018 at 16:24, Juan Nunez-Iglesias
wrote:
> > Plain indexing arr[...] should return an error for ambiguous cases.
> [...] This includes every use of vectorized indexing with multiple integer
> arrays.
>
> This line concerns me. In scikit-image, we often do:
>
> rr, cc = coords.T #
> Plain indexing arr[...] should return an error for ambiguous cases.
> [...] This includes every use of vectorized indexing with multiple
> integer arrays.
This line concerns me. In scikit-image, we often do:
rr, cc = coords.T # coords is an (n, 2) array of integer coordinates
values = image[rr,
Generally +1 on this, but I don’t think we need
To ensure that existing subclasses of ndarray that override indexing
do not inadvertently revert to default behavior for indexing attributes,
these attribute should have explicit checks that disable them if
__getitem__ or __setitem__ has been overrid
Sebastian and I have revised a Numpy Enhancement Proposal that he started
three years ago for overhauling NumPy's advanced indexing. We'd now like to
present it for official consideration.
Minor inline comments (e.g., typos) can be added to the latest pull request
(https://github.com/numpy/numpy/p
