Sure. I didn’t originally, because I thought it would require an entire custom
array container, but the following trivial example actually shows the behavior
in question:
import numpy
class MyThing(object):
def __array__(self, dtype=None, copy=None):
print(f"MyThing.__array__(dtype={dtype}, copy={copy})")
return numpy.ones((5, 5))
u = numpy.zeros((5, 5))
v = MyThing()
u[...] = v
If you run this code, as part of the final assignment statement, the __array__
method is called for ‘v’ with copy=True. Why?
—
Daniel Israel
XCP-4: Continuum Models and Numerical Algorithms
d...@lanl.gov
On Dec 25, 2024, at 3:23 PM, Steven Ellis <stevenalonzoel...@gmail.com> wrote:
Hi David,
New to the listserv, but, maybe you can provide a reproducible example?
Steven
On Wed, Dec 25, 2024, 2:19 PM Israel, Daniel M via NumPy-Discussion
<numpy-discussion@python.org<mailto:numpy-discussion@python.org>> wrote:
I was updating some code that uses a custom array container built with the
mixin library. Specifically, I was trying to eliminate some warnings due to
the change to the __array__ interface to add a copy argument. In doing so, I
discovered that, for two objects u, v in my container class, the code:
u[…] = v
performs a copy on v. Specifically, it calls __array__() with copy=True. This
seems unnecessary and wasteful of memory. Can someone explain to me what is
happening here?
Thanks.
—
Daniel Israel
XCP-4: Continuum Models and Numerical Algorithms
d...@lanl.gov<mailto:d...@lanl.gov>
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