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io.fits and Lomb-Scargle test failures on ppc64le
See original GitHub issueI noticed the following test failures on ppc64le:
__________________ TestChecksumFunctions.test_groups_hdu_data __________________
self = <astropy.io.fits.tests.test_checksum.TestChecksumFunctions object at 0x4111f63668>
def test_groups_hdu_data(self):
imdata = np.arange(100.0)
imdata.shape = (10, 1, 1, 2, 5)
pdata1 = np.arange(10) + 0.1
pdata2 = 42
x = fits.hdu.groups.GroupData(imdata, parnames=['abc', 'xyz'],
pardata=[pdata1, pdata2], bitpix=-32)
hdu = fits.GroupsHDU(x)
hdu.writeto(self.temp('tmp.fits'), overwrite=True, checksum=True)
with fits.open(self.temp('tmp.fits'), checksum=True) as hdul:
assert comparerecords(hdul[0].data, hdu.data)
assert 'CHECKSUM' in hdul[0].header
> assert hdul[0].header['CHECKSUM'] == '3eDQAZDO4dDOAZDO'
E AssertionError: assert 'AAGND29NA8GNA89N' == '3eDQAZDO4dDOAZDO'
E - 3eDQAZDO4dDOAZDO
E + AAGND29NA8GNA89N
../../.tox/py37-test/lib/python3.7/site-packages/astropy/io/fits/tests/test_checksum.py:145: AssertionError
______________________ TestDiff.test_different_table_data ______________________
self = <astropy.io.fits.tests.test_diff.TestDiff object at 0x41129ea048>
def test_different_table_data(self):
"""
Test diffing table data on columns of several different data formats
and dimensions.
"""
ca1 = Column('A', format='L', array=[True, False])
ca2 = Column('B', format='X', array=[[0], [1]])
ca3 = Column('C', format='4I', dim='(2, 2)',
array=[[0, 1, 2, 3], [4, 5, 6, 7]])
ca4 = Column('D', format='J', bscale=2.0, array=[0.0, 2.0])
ca5 = Column('E', format='A3', array=['abc', 'def'])
ca6 = Column('F', format='E', unit='m', array=[0.0, 1.0])
ca7 = Column('G', format='D', bzero=-0.1, array=[0.0, 1.0])
ca8 = Column('H', format='C', array=[0.0+1.0j, 2.0+3.0j])
ca9 = Column('I', format='M', array=[4.0+5.0j, 6.0+7.0j])
ca10 = Column('J', format='PI(2)', array=[[0, 1], [2, 3]])
cb1 = Column('A', format='L', array=[False, False])
cb2 = Column('B', format='X', array=[[0], [0]])
cb3 = Column('C', format='4I', dim='(2, 2)',
array=[[0, 1, 2, 3], [5, 6, 7, 8]])
cb4 = Column('D', format='J', bscale=2.0, array=[2.0, 2.0])
cb5 = Column('E', format='A3', array=['abc', 'ghi'])
cb6 = Column('F', format='E', unit='m', array=[1.0, 2.0])
cb7 = Column('G', format='D', bzero=-0.1, array=[2.0, 3.0])
cb8 = Column('H', format='C', array=[1.0+1.0j, 2.0+3.0j])
cb9 = Column('I', format='M', array=[5.0+5.0j, 6.0+7.0j])
cb10 = Column('J', format='PI(2)', array=[[1, 2], [3, 4]])
ta = BinTableHDU.from_columns([ca1, ca2, ca3, ca4, ca5, ca6, ca7,
ca8, ca9, ca10])
tb = BinTableHDU.from_columns([cb1, cb2, cb3, cb4, cb5, cb6, cb7,
cb8, cb9, cb10])
diff = TableDataDiff(ta.data, tb.data, numdiffs=20)
assert not diff.identical
# The column definitions are the same, but not the column values
assert diff.diff_columns == ()
assert diff.diff_values[0] == (('A', 0), (True, False))
assert diff.diff_values[1] == (('B', 1), ([1], [0]))
assert diff.diff_values[2][0] == ('C', 1)
assert (diff.diff_values[2][1][0] == [[4, 5], [6, 7]]).all()
assert (diff.diff_values[2][1][1] == [[5, 6], [7, 8]]).all()
assert diff.diff_values[3] == (('D', 0), (0, 2.0))
assert diff.diff_values[4] == (('E', 1), ('def', 'ghi'))
assert diff.diff_values[5] == (('F', 0), (0.0, 1.0))
assert diff.diff_values[6] == (('F', 1), (1.0, 2.0))
assert diff.diff_values[7] == (('G', 0), (0.0, 2.0))
assert diff.diff_values[8] == (('G', 1), (1.0, 3.0))
> assert diff.diff_values[9] == (('H', 0), (0.0+1.0j, 1.0+1.0j))
E AssertionError: assert (('I', 0), ((4+5j), (5+5j))) == (('H', 0), (1j, (1+1j)))
E At index 0 diff: ('I', 0) != ('H', 0)
E Use -v to get the full diff
../../.tox/py37-test/lib/python3.7/site-packages/astropy/io/fits/tests/test_diff.py:556: AssertionError
__________________ TestGroupsFunctions.test_create_groupdata ___________________
self = <astropy.io.fits.tests.test_groups.TestGroupsFunctions object at 0x4111dcb9b0>
def test_create_groupdata(self):
"""
Basic test for creating GroupData from scratch.
"""
imdata = np.arange(100.0)
imdata.shape = (10, 1, 1, 2, 5)
pdata1 = np.arange(10, dtype=np.float32) + 0.1
pdata2 = 42.0
x = fits.hdu.groups.GroupData(imdata, parnames=['abc', 'xyz'],
pardata=[pdata1, pdata2], bitpix=-32)
assert x.parnames == ['abc', 'xyz']
assert (x.par('abc') == pdata1).all()
assert (x.par('xyz') == ([pdata2] * len(x))).all()
> assert (x.data == imdata).all()
E assert False
E + where False = <built-in method all of numpy.ndarray object at 0x410ff49f30>()
E + where <built-in method all of numpy.ndarray object at 0x410ff49f30> = array([[[[[ 0...dtype=float32) == array([[[[[ 0...98., 99.]]]]])
E Use -v to get the full diff.all
../../.tox/py37-test/lib/python3.7/site-packages/astropy/io/fits/tests/test_groups.py:151: AssertionError
______________ TestImageFunctions.test_scale_bzero_with_int_data _______________
self = <astropy.io.fits.tests.test_image.TestImageFunctions object at 0x4111f51a90>
def test_scale_bzero_with_int_data(self):
"""
Regression test for https://github.com/astropy/astropy/issues/4600
"""
a = np.arange(100, 200, dtype=np.int16)
hdu1 = fits.PrimaryHDU(data=a.copy())
hdu2 = fits.PrimaryHDU(data=a.copy())
# Previously the following line would throw a TypeError,
# now it should be identical to the integer bzero case
hdu1.scale('int16', bzero=99.0)
hdu2.scale('int16', bzero=99)
> assert np.allclose(hdu1.data, hdu2.data)
E assert False
E + where False = <function allclose at 0x400327b510>(array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0,... 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 97, 98, 99, 100], dtype=int16), array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,\n 14, 15, 16, 17, 18, 19, 20, 21,...81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,\n 92, 93, 94, 95, 96, 97, 98, 99, 100], dtype=int16))
E + where <function allclose at 0x400327b510> = np.allclose
E + and array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0,... 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 97, 98, 99, 100], dtype=int16) = <astropy.io.fits.hdu.image.PrimaryHDU object at 0x4111f516a0>.data
E + and array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,\n 14, 15, 16, 17, 18, 19, 20, 21,...81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,\n 92, 93, 94, 95, 96, 97, 98, 99, 100], dtype=int16) = <astropy.io.fits.hdu.image.PrimaryHDU object at 0x4111f51780>.data
../../.tox/py37-test/lib/python3.7/site-packages/astropy/io/fits/tests/test_image.py:1059: AssertionError
____________ TestCompressedImage.test_compression_with_gzip_column _____________
self = <astropy.io.fits.tests.test_image.TestCompressedImage object at 0x401b64cba8>
def test_compression_with_gzip_column(self):
"""
Regression test for https://github.com/spacetelescope/PyFITS/issues/71
"""
arr = np.zeros((2, 7000), dtype='float32')
# The first row (which will be the first compressed tile) has a very
# wide range of values that will be difficult to quantize, and should
# result in use of a GZIP_COMPRESSED_DATA column
arr[0] = np.linspace(0, 1, 7000)
arr[1] = np.random.normal(size=7000)
hdu = fits.CompImageHDU(data=arr)
hdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as hdul:
comp_hdu = hdul[1]
# GZIP-compressed tile should compare exactly
> assert np.all(comp_hdu.data[0] == arr[0])
E assert False
E + where False = <function all at 0x4003260378>(array([ 0.000...dtype=float32) == array([ 0.000...dtype=float32)
E + where <function all at 0x4003260378> = np.all
E Use -v to get the full diff)
../../.tox/py37-test/lib/python3.7/site-packages/astropy/io/fits/tests/test_image.py:1659: AssertionError
________ TestCompressedImage.test_scale_bzero_with_compressed_int_data _________
self = <astropy.io.fits.tests.test_image.TestCompressedImage object at 0x41129da2e8>
def test_scale_bzero_with_compressed_int_data(self):
"""
Regression test for https://github.com/astropy/astropy/issues/4600
and https://github.com/astropy/astropy/issues/4588
Identical to test_scale_bzero_with_int_data() but uses a compressed
image.
"""
a = np.arange(100, 200, dtype=np.int16)
hdu1 = fits.CompImageHDU(data=a.copy())
hdu2 = fits.CompImageHDU(data=a.copy())
# Previously the following line would throw a TypeError,
# now it should be identical to the integer bzero case
hdu1.scale('int16', bzero=99.0)
hdu2.scale('int16', bzero=99)
> assert np.allclose(hdu1.data, hdu2.data)
E assert False
E + where False = <function allclose at 0x400327b510>(array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0,... 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 97, 98, 99, 100], dtype=int16), array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,\n 14, 15, 16, 17, 18, 19, 20, 21,...81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,\n 92, 93, 94, 95, 96, 97, 98, 99, 100], dtype=int16))
E + where <function allclose at 0x400327b510> = np.allclose
E + and array([ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0,... 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 97, 98, 99, 100], dtype=int16) = <astropy.io.fits.hdu.compressed.CompImageHDU object at 0x41129da5c0>.data
E + and array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,\n 14, 15, 16, 17, 18, 19, 20, 21,...81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,\n 92, 93, 94, 95, 96, 97, 98, 99, 100], dtype=int16) = <astropy.io.fits.hdu.compressed.CompImageHDU object at 0x4113000400>.data
../../.tox/py37-test/lib/python3.7/site-packages/astropy/io/fits/tests/test_image.py:1704: AssertionError
@olebole - have you seen these before in Debian testing?
Issue Analytics
- State:
- Created 3 years ago
- Comments:6 (6 by maintainers)
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We only have arm and s390x not PPC. But I can add all three to the GitHub Actions config 😺
Wow, this one is quite surprising. It has nothing to do with compression, cfitsio etc., just some basic arithmetic. https://github.com/astropy/astropy/runs/1949615134?check_suite_focus=true