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xref: #12330 (comment)
The docs state that nan == nan in assert_array_equal
https://docs.scipy.org/doc/numpy-1.15.0/reference/generated/numpy.testing.assert_array_equal.html
Failer
import numpy as np
from numpy.testing import assert_array_equal
a = np.zeros(1, dtype='f8,f8')
a[0] = (np.nan, 0)
assert_array_equal(a, a)---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-6-96868a4fad08> in <module>
----> 1 assert_array_equal(a, a)
/home/mark/git/numpy/numpy/testing/_private/utils.py in assert_array_equal(x, y, err_msg, verbose)
871 __tracebackhide__ = True # Hide traceback for py.test
872 assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
--> 873 verbose=verbose, header='Arrays are not equal')
874
875
/home/mark/git/numpy/numpy/testing/_private/utils.py in assert_array_compare(comparison, x, y, err_msg, verbose, header, precision, equal_nan, equal_inf)
795 verbose=verbose, header=header,
796 names=('x', 'y'), precision=precision)
--> 797 raise AssertionError(msg)
798 except ValueError:
799 import traceback
AssertionError:
Arrays are not equal
(mismatch 100.0%)
x: array([(nan, 0.)], dtype=[('f0', '<f8'), ('f1', '<f8')])
y: array([(nan, 0.)], dtype=[('f0', '<f8'), ('f1', '<f8')])Workaround: don't use nan in structured array tests
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