[Numpy-discussion] Scipy 2017 NumPy sprint

Ben Rowland bennyrowland at mac.com
Thu Jul 6 07:42:59 EDT 2017


> On 5 Jul 2017, at 19:05, Stephan Hoyer <shoyer at gmail.com> wrote:
> 
> On Wed, Jul 5, 2017 at 10:40 AM, Chris Barker <chris.barker at noaa.gov <mailto:chris.barker at noaa.gov>> wrote:
> Along those lines, there was some discussion of having a set of utilities (or maybe eve3n an ABC?) that would make it easier to create a ndarray-like object.
> 
> That is, the boilerplate needed for multi-dimensional indexing and slicing, etc...
> 
> That could be a nice little sprint-able project.
> 
> Indeed. Let me highlight a few mixins <https://github.com/pydata/xarray/blob/6a20f917041abf53bcb35e210d59f5b331211012/xarray/core/utils.py#L381-L425> that I wrote for xarray that might be more broadly useful. The challenge here is that there are quite a few different meanings to "ndarray-like", so mixins really need to be mix-and-match-able. But at least defining a base list of methods to implement/override would be useful.
> 
> In NumPy, this could go along with NDArrayOperatorsMixins in numpy/lib/mixins.py <https://github.com/numpy/numpy/blob/14cd918c651d72f4c2a8681093e114f01d5bdc36/numpy/lib/mixins.py>
Slightly off topic, but as someone who has just spent a fair amount of time implementing various
subclasses of nd-array, I am interested (and a little concerned), that the consensus is not to use
them. Is there anything available which explains why this is the case and what the alternatives
are?

Ben
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