[Numpy-discussion] bug in deepcopy() of rank-zero arrays?

Richard Hattersley rhattersley@gmail....
Tue Apr 30 07:35:07 CDT 2013


+1 for getting rid of this inconsistency

We've hit this with Iris (a met/ocean analysis package - see github), and
have had to add several workarounds.


On 19 April 2013 16:55, Chris Barker - NOAA Federal
<chris.barker@noaa.gov>wrote:

> Hi folks,
>
> In [264]: np.__version__
> Out[264]: '1.7.0'
>
> I just noticed that deep copying a rank-zero array yields a scalar --
> probably not what we want.
>
> In [242]: a1 = np.array(3)
>
> In [243]: type(a1), a1
> Out[243]: (numpy.ndarray, array(3))
>
> In [244]: a2 = copy.deepcopy(a1)
>
> In [245]: type(a2), a2
> Out[245]: (numpy.int32, 3)
>
> regular copy.copy() seems to work fine:
>
> In [246]: a3 = copy.copy(a1)
>
> In [247]: type(a3), a3
> Out[247]: (numpy.ndarray, array(3))
>
> Higher-rank arrays seem to work fine:
>
> In [253]: a1 = np.array((3,4))
>
> In [254]: type(a1), a1
> Out[254]: (numpy.ndarray, array([3, 4]))
>
> In [255]: a2 = copy.deepcopy(a1)
>
> In [256]: type(a2), a2
> Out[256]: (numpy.ndarray, array([3, 4]))
>
> Array scalars seem to work fine as well:
>
> In [257]: s1 = np.float32(3)
>
> In [258]: s2 = copy.deepcopy(s1)
>
> In [261]: type(s1), s1
> Out[261]: (numpy.float32, 3.0)
>
> In [262]: type(s2), s2
> Out[262]: (numpy.float32, 3.0)
>
> There are other ways to copy arrays, but in this case, I had a dict
> with a bunch of arrays in it, and needed a deepcopy of the dict. I was
> surprised to find that my rank-0 array got turned into a scalar.
>
> -Chris
>
> --
>
> Christopher Barker, Ph.D.
> Oceanographer
>
> Emergency Response Division
> NOAA/NOS/OR&R            (206) 526-6959   voice
> 7600 Sand Point Way NE   (206) 526-6329   fax
> Seattle, WA  98115       (206) 526-6317   main reception
>
> Chris.Barker@noaa.gov
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