[Numpy-discussion] Behavior of numpy.copy with sub-classes

[Nathan Goldbaum]

On Mon, Oct 19, 2015 at 7:23 PM, Jonathan Helmus <jjhelmus at gmail.com> wrote:

> In GitHub issue #3474, a number of us have started a conversation on how
> NumPy's copy function should behave when passed an instance which is a
> sub-class of the array class.  Specifically, the issue began by noting that
> when a MaskedArray is passed to np.copy, the sub-class is not passed
> through but rather a ndarray is returned.
>
> I suggested adding a "subok" parameter which controls how sub-classes are
> handled and others suggested having the function call a copy method on duck
> arrays.  The "subok" parameter is implemented in PR #6509 as an example.
> Both of these options would change the API of numpy.copy and possibly break
> backwards compatibility.  Do others have an opinion of how np.copy should
> handle sub-classes?
>
> For a concrete example of this behavior and possible changes, what type
> should copy_x be in the following snippet:
>
> import numpy as np
> x = np.ma.array([1,2,3])
> copy_x = np.copy(x)
>

FWIW, it looks like np.copy() is never used in our code to work with the
ndarray subclass we maintain in yt. Instead we use the copy() method much
more often, and that returns the appropriate type. I guess it makes sense
to have the type of the return value of np.copy() agree with the type of
the copy() member function.

That said, breaking backwards compatibility here before numpy 2.0 might
very well break real code. It might be worth it search e.g. github for all
instances of np.copy() to see if they're dealing with subclasses.


>
>
> Cheers,
>
>     - Jonathan Helmus
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