TST: TestQuantityReshapeFuncs.test_flat_attributes failed with AssertionError on s390x (big-endian)
See original GitHub issueExample log: https://github.com/astropy/astropy/runs/2708622607?check_suite_focus=true
Last week’s run was successful (https://github.com/astropy/astropy/runs/2653579480?check_suite_focus=true) on 2021-05-24.
________________ TestQuantityReshapeFuncs.test_flat_attributes _________________
self = <astropy.units.tests.test_quantity_array_methods.TestQuantityReshapeFuncs object at 0x42b00b16a0>
def test_flat_attributes(self):
"""While ``flat`` doesn't make a copy, it changes the shape."""
q = np.arange(6.).reshape(3, 1, 2) * u.m
qf = q.flat
# see TestQuantityArrayCopy.test_flat for tests of iteration
# and slicing and setting. Here we test the properties and methods to
# match `numpy.ndarray.flatiter`
assert qf.base is q
# testing the indices -- flat and full -- into the array
assert qf.coords == (0, 0, 0) # to start
assert qf.index == 0
# now consume the iterator
endindices = [(qf.index, qf.coords) for x in qf][-2] # next() oversteps
> assert endindices[0] == 5
E assert 0 == 5
astropy/units/tests/test_quantity_array_methods.py:138: AssertionError
Issue Analytics
- State:
- Created 2 years ago
- Comments:12 (12 by maintainers)
Top Results From Across the Web
test_can_restrict_endianness fails on big-endian s390x #1164
Hi! test_can_restrict_endianness fails on s390x, the only big-endian architecture being tested in Ubuntu. ... Is this by design? The test fails ...
Read more >Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start FreeTop Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
Top GitHub Comments
Yes, hopefully, things will just work with numpy-dev!
Looks like numpy/numpy#19153 is marked as a bug and slated to be fixed in Numpy 1.22. So, for now, perhaps we can xfail this test for
numpy<=1.21
in thes390x
job only?