issues: 200908727

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
200908727 MDU6SXNzdWUyMDA5MDg3Mjc= 1208 Test failures on Debian if built with bottleneck 1964655 closed 0     14 2017-01-16T00:21:38Z 2017-01-29T23:56:04Z 2017-01-29T23:31:29Z CONTRIBUTOR      

On my attempt to package xarray for Debian, I encountered the following issue whereby the package build process (which sequentially runs build, test, install for all supported Python versions) would succeed if the bottleneck build dependency is omitted, but fail at the test stage otherwise. The version of bottleneck currently available in Debian is 1.2.0. The log from pytest is pasted below:

``` =================================== FAILURES =================================== ___ TestDataArray.test_groupby_apply_center ______

self = <xarray.test.test_dataarray.TestDataArray testMethod=test_groupby_apply_center>

def test_groupby_apply_center(self):
    def center(x):
        return x - np.mean(x)

    array = self.make_groupby_example_array()
    grouped = array.groupby('abc')

    expected_ds = array.to_dataset()
    exp_data = np.hstack([center(self.x[:, :9]),
                          center(self.x[:, 9:10]),
                          center(self.x[:, 10:])])
    expected_ds['foo'] = (['x', 'y'], exp_data)
    expected_centered = expected_ds['foo']

  self.assertDataArrayAllClose(expected_centered, grouped.apply(center))

xarray/test/test_dataarray.py:1481:

xarray/test/init.py:197: in assertDataArrayAllClose assert_xarray_allclose(ar1, ar2, rtol=rtol, atol=atol) xarray/test/init.py:235: in assert_xarray_allclose assert_xarray_allclose(a.variable, b.variable)

a = <xarray.Variable (x: 10, y: 20)> array([[ 0.09890759, 0.25838611, -0.45524894...108, -0.4202902 , -0.3395864 , -0.15065542, -0.03596724, -0.44654371]]) b = <xarray.Variable (x: 10, y: 20)> array([[ 0.09890759, 0.25838611, -0.45524894...108, -0.4202902 , -0.3395864 , -0.15065542, -0.03596724, -0.44654371]]) rtol = 1e-05, atol = 1e-08

def assert_xarray_allclose(a, b, rtol=1e-05, atol=1e-08):
    import xarray as xr
    ___tracebackhide__ = True  # noqa: F841
    assert type(a) == type(b)
    if isinstance(a, xr.Variable):
        assert a.dims == b.dims
        allclose = data_allclose_or_equiv(
            a.values, b.values, rtol=rtol, atol=atol)

      assert allclose, '{}\n{}'.format(a.values, b.values)

E AssertionError: [[ 0.09890759 0.25838611 -0.45524894 0.19438977 0.33283847 -0.43268996 E -0.48217406 0.19246675 -0.35439804 0.11269385 -0.41444651 -0.48431908 E -0.39910098 0.49254261 -0.30480298 -0.32417743 -0.07204188 0.2693067 E 0.26276671 0.33348262] E [-0.34499113 0.46303903 -0.35713035 0.15563781 -0.01807461 0.08631493 E -0.17055826 0.12467856 0.02713384 -0.3631607 -0.37158371 0.30343557 E -0.19175157 0.19976175 -0.36999787 -0.30401142 -0.48258481 -0.34936509 E 0.19736374 -0.09867697] E [ 0.09397107 0.20609742 -0.0663552 -0.19143598 0.01839407 0.34196996 E -0.14854474 0.31282176 0.00777962 0.10738644 0.37057503 -0.15718542 E 0.04364944 -0.06578303 -0.23842453 0.34648799 0.49288676 0.41277933 E 0.50145361 -0.3835484 ] E [-0.21291174 -0.45514573 0.12111804 -0.28319255 0.32380163 -0.3474909 E 0.23764942 -0.39402155 0.08587823 0.40455906 0.21993109 -0.48659786 E 0.34223771 -0.46998904 0.3689656 0.27974461 -0.00213432 -0.29371619 E 0.39490332 0.2572515 ] E [ 0.0058088 -0.10393215 0.39392373 0.26350055 -0.49707502 -0.23407721 E 0.06441153 0.09532245 0.26361004 0.24034371 -0.46882038 0.49472167 E -0.31433938 0.26932964 -0.00890849 -0.40142042 0.03952812 0.17389542 E -0.25081914 0.45069667] E [ 0.21532826 -0.05997302 0.02021198 0.48875992 -0.0297901 -0.17712176 E -0.44359239 0.2964151 -0.30089817 -0.22969758 0.03411299 0.280227 E -0.24713806 -0.10428751 0.23407841 0.39648906 -0.10151348 0.50768613 E 0.44325196 -0.10753505] E [-0.25493908 0.12975219 -0.24043256 0.15334854 0.44570823 0.12942852 E -0.25521364 0.07838812 -0.3195924 0.08087772 -0.27026464 0.31757927 E 0.00234494 0.23580586 0.47520352 -0.43470572 -0.37470029 0.31202043 E -0.09424153 -0.17970934] E [ 0.37067661 0.38608375 0.38549098 -0.33920416 0.35198984 0.16994992 E 0.22551435 0.32186772 0.19998808 -0.01718303 0.42852689 -0.31499095 E -0.42404301 -0.16993069 0.44848428 -0.24842595 0.45198088 0.04095394 E -0.42434055 0.08295308] E [-0.062468 -0.31612011 0.46015728 0.01154732 0.07488519 0.18989284 E -0.27148594 0.26888518 -0.35489493 -0.02320481 0.23154296 0.3228651 E 0.21833924 0.32340958 -0.12142829 -0.08212185 0.00699867 -0.10949993 E -0.07059468 -0.0616217 ] E [ 0.33549783 -0.42434389 -0.45991471 0.09982218 0.32355871 -0.36587924 E -0.12447734 -0.23565156 -0.31755871 -0.31261466 -0.4069172 0.42464878 E -0.42271043 -0.25510055 0.39021108 -0.4202902 -0.3395864 -0.15065542 E -0.03596724 -0.44654371]] E [[ 0.09890759 0.25838611 -0.45524894 0.19438977 0.33283847 -0.43268996 E -0.48217406 0.19246675 -0.35439804 0.47884013 -0.41444651 -0.48431908 E -0.39910098 0.49254261 -0.30480298 -0.32417743 -0.07204188 0.2693067 E 0.26276671 0.33348262] E [-0.34499113 0.46303903 -0.35713035 0.15563781 -0.01807461 0.08631493 E -0.17055826 0.12467856 0.02713384 0.00298558 -0.37158371 0.30343557 E -0.19175157 0.19976175 -0.36999787 -0.30401142 -0.48258481 -0.34936509 E 0.19736374 -0.09867697] E [ 0.09397107 0.20609742 -0.0663552 -0.19143598 0.01839407 0.34196996 E -0.14854474 0.31282176 0.00777962 0.47353272 0.37057503 -0.15718542 E 0.04364944 -0.06578303 -0.23842453 0.34648799 0.49288676 0.41277933 E 0.50145361 -0.3835484 ] E [-0.21291174 -0.45514573 0.12111804 -0.28319255 0.32380163 -0.3474909 E 0.23764942 -0.39402155 0.08587823 0.77070534 0.21993109 -0.48659786 E 0.34223771 -0.46998904 0.3689656 0.27974461 -0.00213432 -0.29371619 E 0.39490332 0.2572515 ] E [ 0.0058088 -0.10393215 0.39392373 0.26350055 -0.49707502 -0.23407721 E 0.06441153 0.09532245 0.26361004 0.60649 -0.46882038 0.49472167 E -0.31433938 0.26932964 -0.00890849 -0.40142042 0.03952812 0.17389542 E -0.25081914 0.45069667] E [ 0.21532826 -0.05997302 0.02021198 0.48875992 -0.0297901 -0.17712176 E -0.44359239 0.2964151 -0.30089817 0.13644871 0.03411299 0.280227 E -0.24713806 -0.10428751 0.23407841 0.39648906 -0.10151348 0.50768613 E 0.44325196 -0.10753505] E [-0.25493908 0.12975219 -0.24043256 0.15334854 0.44570823 0.12942852 E -0.25521364 0.07838812 -0.3195924 0.447024 -0.27026464 0.31757927 E 0.00234494 0.23580586 0.47520352 -0.43470572 -0.37470029 0.31202043 E -0.09424153 -0.17970934] E [ 0.37067661 0.38608375 0.38549098 -0.33920416 0.35198984 0.16994992 E 0.22551435 0.32186772 0.19998808 0.34896325 0.42852689 -0.31499095 E -0.42404301 -0.16993069 0.44848428 -0.24842595 0.45198088 0.04095394 E -0.42434055 0.08295308] E [-0.062468 -0.31612011 0.46015728 0.01154732 0.07488519 0.18989284 E -0.27148594 0.26888518 -0.35489493 0.34294147 0.23154296 0.3228651 E 0.21833924 0.32340958 -0.12142829 -0.08212185 0.00699867 -0.10949993 E -0.07059468 -0.0616217 ] E [ 0.33549783 -0.42434389 -0.45991471 0.09982218 0.32355871 -0.36587924 E -0.12447734 -0.23565156 -0.31755871 0.05353162 -0.4069172 0.42464878 E -0.42271043 -0.25510055 0.39021108 -0.4202902 -0.3395864 -0.15065542 E -0.03596724 -0.44654371]]

xarray/test/init.py:233: AssertionError _____ TestDataArray.test_groupby_math ______

self = <xarray.test.test_dataarray.TestDataArray testMethod=test_groupby_math>

def test_groupby_math(self):
    array = self.make_groupby_example_array()
    for squeeze in [True, False]:
        grouped = array.groupby('x', squeeze=squeeze)

        expected = array + array.coords['x']
        actual = grouped + array.coords['x']
        self.assertDataArrayIdentical(expected, actual)

        actual = array.coords['x'] + grouped
        self.assertDataArrayIdentical(expected, actual)

        ds = array.coords['x'].to_dataset('X')
        expected = array + ds
        actual = grouped + ds
        self.assertDatasetIdentical(expected, actual)

        actual = ds + grouped
        self.assertDatasetIdentical(expected, actual)

    grouped = array.groupby('abc')
    expected_agg = (grouped.mean() - np.arange(3)).rename(None)
    actual = grouped - DataArray(range(3), [('abc', ['a', 'b', 'c'])])
    actual_agg = actual.groupby('abc').mean()

  self.assertDataArrayAllClose(expected_agg, actual_agg)

xarray/test/test_dataarray.py:1527:

xarray/test/init.py:197: in assertDataArrayAllClose assert_xarray_allclose(ar1, ar2, rtol=rtol, atol=atol) xarray/test/init.py:235: in assert_xarray_allclose assert_xarray_allclose(a.variable, b.variable)

a = <xarray.Variable (abc: 3)> array([ 4.66319277e-001, -4.76053212e-001, 1.49956297e+247]) b = <xarray.Variable (abc: 3)> array([ 4.66319277e-01, -4.76053212e-01, -9.90547784e+75]) rtol = 1e-05, atol = 1e-08

def assert_xarray_allclose(a, b, rtol=1e-05, atol=1e-08):
    import xarray as xr
    ___tracebackhide__ = True  # noqa: F841
    assert type(a) == type(b)
    if isinstance(a, xr.Variable):
        assert a.dims == b.dims
        allclose = data_allclose_or_equiv(
            a.values, b.values, rtol=rtol, atol=atol)

      assert allclose, '{}\n{}'.format(a.values, b.values)

E AssertionError: [ 4.66319277e-001 -4.76053212e-001 1.49956297e+247] E [ 4.66319277e-01 -4.76053212e-01 -9.90547784e+75]

xarray/test/init.py:233: AssertionError ----------------------------- Captured stderr call ----------------------------- /<<PKGBUILDDIR>>/.pybuild/pythonX.Y_2.7/build/xarray/test/test_dataarray.py:1515: FutureWarning: the order of the arguments on DataArray.to_dataset has changed; you now need to supply name as a keyword argument ds = array.coords['x'].to_dataset('X') ___ TestDataArray.testgroupby_sum ____

self = <xarray.test.test_dataarray.TestDataArray testMethod=test_groupby_sum>

def test_groupby_sum(self):
    array = self.make_groupby_example_array()
    grouped = array.groupby('abc')

    expected_sum_all = Dataset(
        {'foo': Variable(['abc'], np.array([self.x[:, :9].sum(),
                                            self.x[:, 10:].sum(),
                                            self.x[:, 9:10].sum()]).T),
         'abc': Variable(['abc'], np.array(['a', 'b', 'c']))})['foo']
    self.assertDataArrayAllClose(expected_sum_all, grouped.reduce(np.sum))

  self.assertDataArrayAllClose(expected_sum_all, grouped.sum())

xarray/test/test_dataarray.py:1426:

xarray/test/init.py:197: in assertDataArrayAllClose assert_xarray_allclose(ar1, ar2, rtol=rtol, atol=atol) xarray/test/init.py:235: in assert_xarray_allclose assert_xarray_allclose(a.variable, b.variable)

a = <xarray.Variable (abc: 3)> array([ 45.64328315, 47.37700685, 5.99867891]) b = <xarray.Variable (abc: 3)> array([ 4.56432831e+001, 4.73770068e+001, 1.49956297e+248]) rtol = 1e-05, atol = 1e-08

def assert_xarray_allclose(a, b, rtol=1e-05, atol=1e-08):
    import xarray as xr
    ___tracebackhide__ = True  # noqa: F841
    assert type(a) == type(b)
    if isinstance(a, xr.Variable):
        assert a.dims == b.dims
        allclose = data_allclose_or_equiv(
            a.values, b.values, rtol=rtol, atol=atol)

      assert allclose, '{}\n{}'.format(a.values, b.values)

E AssertionError: [ 45.64328315 47.37700685 5.99867891] E [ 4.56432831e+001 4.73770068e+001 1.49956297e+248]

xarray/test/init.py:233: AssertionError ============= 3 failed, 1149 passed, 340 skipped in 39.32 seconds ============== ```

 
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