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https://github.com/pydata/xarray/pull/3596#issuecomment-563311262 https://api.github.com/repos/pydata/xarray/issues/3596 563311262 MDEyOklzc3VlQ29tbWVudDU2MzMxMTI2Mg== 2448579 2019-12-09T16:11:46Z 2019-12-09T16:11:46Z MEMBER

It seems like we have some value mismatches on dask==1.2. @fujiisoup is this the error you found?

``` =================================== FAILURES =================================== _ TestVariableWithDask.testpad[xr_arg0-np_arg0-linear_ramp] __

self = <xarray.tests.test_variable.TestVariableWithDask object at 0x7fb69b629b00> mode = 'linear_ramp', xr_arg = {'x': (2, 1)}, np_arg = ((2, 1), (0, 0), (0, 0))

@pytest.mark.parametrize(
    "mode",
    [
        pytest.param("mean", marks=pytest.mark.xfail),
        pytest.param("median", marks=pytest.mark.xfail),
        pytest.param("reflect", marks=pytest.mark.xfail),
        "edge",
        "linear_ramp",
        "maximum",
        "minimum",
        "symmetric",
        "wrap",
    ],
)
@pytest.mark.parametrize(
    "xr_arg, np_arg",
    [
        [{"x": (2, 1)}, ((2, 1), (0, 0), (0, 0))],
        [{"y": (0, 3)}, ((0, 0), (0, 3), (0, 0))],
        [{"x": (3, 1), "z": (2, 0)}, ((3, 1), (0, 0), (2, 0))],
    ],
)
def test_pad(self, mode, xr_arg, np_arg):
    data = np.arange(4 * 3 * 2).reshape(4, 3, 2)
    v = self.cls(["x", "y", "z"], data)

    actual = v.pad(mode=mode, **xr_arg)
    expected = np.pad(data, np_arg, mode=mode,)

  assert_array_equal(actual, expected)

E AssertionError: E Arrays are not equal E
E (mismatch 2.3809523809523796%) E x: array([[[ 0, 0], E [ 0, 0], E [ 0, 0]],... E y: array([[[ 0, 0], E [ 0, 0], E [ 0, 0]],...

xarray/tests/test_variable.py:821: AssertionError _ TestVariableWithDask.testpad[xr_arg1-np_arg1-linear_ramp] __

self = <xarray.tests.test_variable.TestVariableWithDask object at 0x7fb69df9eb00> mode = 'linear_ramp', xr_arg = {'y': (0, 3)}, np_arg = ((0, 0), (0, 3), (0, 0))

@pytest.mark.parametrize(
    "mode",
    [
        pytest.param("mean", marks=pytest.mark.xfail),
        pytest.param("median", marks=pytest.mark.xfail),
        pytest.param("reflect", marks=pytest.mark.xfail),
        "edge",
        "linear_ramp",
        "maximum",
        "minimum",
        "symmetric",
        "wrap",
    ],
)
@pytest.mark.parametrize(
    "xr_arg, np_arg",
    [
        [{"x": (2, 1)}, ((2, 1), (0, 0), (0, 0))],
        [{"y": (0, 3)}, ((0, 0), (0, 3), (0, 0))],
        [{"x": (3, 1), "z": (2, 0)}, ((3, 1), (0, 0), (2, 0))],
    ],
)
def test_pad(self, mode, xr_arg, np_arg):
    data = np.arange(4 * 3 * 2).reshape(4, 3, 2)
    v = self.cls(["x", "y", "z"], data)

    actual = v.pad(mode=mode, **xr_arg)
    expected = np.pad(data, np_arg, mode=mode,)

  assert_array_equal(actual, expected)

E AssertionError: E Arrays are not equal E
E (mismatch 16.66666666666667%) E x: array([[[ 0, 1], E [ 2, 3], E [ 4, 5],... E y: array([[[ 0, 1], E [ 2, 3], E [ 4, 5],...

xarray/tests/test_variable.py:821: AssertionError _ TestVariableWithDask.testpad[xr_arg2-np_arg2-linear_ramp] __

self = <xarray.tests.test_variable.TestVariableWithDask object at 0x7fb69c609860> mode = 'linear_ramp', xr_arg = {'x': (3, 1), 'z': (2, 0)} np_arg = ((3, 1), (0, 0), (2, 0))

@pytest.mark.parametrize(
    "mode",
    [
        pytest.param("mean", marks=pytest.mark.xfail),
        pytest.param("median", marks=pytest.mark.xfail),
        pytest.param("reflect", marks=pytest.mark.xfail),
        "edge",
        "linear_ramp",
        "maximum",
        "minimum",
        "symmetric",
        "wrap",
    ],
)
@pytest.mark.parametrize(
    "xr_arg, np_arg",
    [
        [{"x": (2, 1)}, ((2, 1), (0, 0), (0, 0))],
        [{"y": (0, 3)}, ((0, 0), (0, 3), (0, 0))],
        [{"x": (3, 1), "z": (2, 0)}, ((3, 1), (0, 0), (2, 0))],
    ],
)
def test_pad(self, mode, xr_arg, np_arg):
    data = np.arange(4 * 3 * 2).reshape(4, 3, 2)
    v = self.cls(["x", "y", "z"], data)

    actual = v.pad(mode=mode, **xr_arg)
    expected = np.pad(data, np_arg, mode=mode,)

  assert_array_equal(actual, expected)

E AssertionError: E Arrays are not equal E
E (mismatch 5.208333333333329%) E x: array([[[ 0, 0, 0, 0], E [ 0, 0, 0, 0], E [ 0, 0, 0, 0]],... E y: array([[[ 0, 0, 0, 0], E [ 0, 0, 0, 0], E [ 0, 0, 0, 0]],... ```

 
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