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

Charles R Harris charlesr.harris at gmail.com
Mon Oct 19 22:40:15 EDT 2015

On Mon, Oct 19, 2015 at 8:28 PM, Nathan Goldbaum <nathan12343 at gmail.com>

> 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.

The problem with github searches is that there are a ton of numpy forks.
ISTR once finding a method to avoid them, but can't remember what is was.
If anyone knows how to do that, I'd appreciate learning.

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