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@davidtrem davidtrem commented Sep 13, 2018

Test for issue #2414

closes #2414


def test_indexing_1d_object_array():
testarray = DataArray(np.array((np.arange(3), np.arange(6))))
testarray[0]
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Maybe add:

expected_array = np.empty((), dtype=object)
expected_array[()] = np.arange(3)
expected = DataArray(expected_array)
assert_identical(expected, testarray[0])

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@davidtrem davidtrem Sep 13, 2018

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Well...
I guess you mean:

expected_array = np.arange(3)
expected = DataArray(expected_array)
assert_identical(expected, testarray[0])

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expected_array = np.arange(3) gives you an array with shape (3,) and int dtype. You want a scalar NumPy with shape () and object dtype.

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OK, I get you point :-)
Main issue I still have then is that I'm not able to get the 'np.arange(3) array'
from the 'expected'...
because 'expected.data' is king of empty :-(
expected.data.shape == () therefore expected.data[0] raise an IndexError
How would you access the content of 'expected' ?

@shoyer
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shoyer commented Sep 14, 2018 via email

@keewis
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keewis commented Apr 3, 2021

if we still want this test, it should be ready for review / merging

@max-sixty
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Let's do it! Thanks for resuscitating @keewis

@dcherian
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dcherian commented Apr 5, 2021

Thanks @keewis

@dcherian dcherian merged commit 27ecf2d into pydata:master Apr 5, 2021
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Indexing not properly working with object dtype element ?

6 participants