On 15/2/22 09:53, Stefan van der Walt wrote:
On Mon, Feb 14, 2022, at 12:45, Sebastian Berg wrote:
But this is currently *not* consistently the case. I wish to make this
consistent. The confusion is around object arrays, though:
value = np.array(None, dtype=object)
arr[0] = value
Stores `value` without unpacking it currently.
arr.fill(value)
Stores the `None` (unpacking `value`) if and only if `value` is 0-D.
That last behavior doesn't look right to me. An object array should be thought
of as a collection of pointers, and if you happen to want to point to a NumPy
array, so be it.
I think we should strive for consistency and code simplicity. In the
non-object case, it is clear that assignment will try to unpack an
ndarray. So we should do the same thing with object arrays, and document
the change in behaviour. Could we suggest a backward compatible
alternative (would using a record dtype fit better with Stefan's mental
model)?
Matti
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