NaT tests need to be fixed on master

[dcherian]

=================================== FAILURES ===================================
____________________ TestVariable.test_index_0d_not_a_time _____________________
self = <xarray.tests.test_variable.TestVariable object at 0x7f0dd7b6bda0>
    def test_index_0d_not_a_time(self):
        d = np.datetime64('NaT', 'ns')
        x = self.cls(['x'], [d])
>       self._assertIndexedLikeNDArray(x, d)
xarray/tests/test_variable.py:197: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
self = <xarray.tests.test_variable.TestVariable object at 0x7f0dd7b6bda0>
variable = <xarray.Variable (x: 1)>
array(['NaT'], dtype='datetime64[ns]')
expected_value0 = numpy.datetime64('NaT'), expected_dtype = None
    def _assertIndexedLikeNDArray(self, variable, expected_value0,
                                  expected_dtype=None):
        """Given a 1-dimensional variable, verify that the variable is indexed
        like a numpy.ndarray.
        """
        assert variable[0].shape == ()
        assert variable[0].ndim == 0
        assert variable[0].size == 1
        # test identity
        assert variable.equals(variable.copy())
        assert variable.identical(variable.copy())
        # check value is equal for both ndarray and Variable
        with warnings.catch_warnings():
            warnings.filterwarnings('ignore', "In the future, 'NAT == x'")
>           assert variable.values[0] == expected_value0
E           AssertionError: assert numpy.datetime64('NaT') == numpy.datetime64('NaT')
E             -numpy.datetime64('NaT')
E             +numpy.datetime64('NaT')
xarray/tests/test_variable.py:143: AssertionError



________________ TestVariableWithDask.test_index_0d_not_a_time _________________
self = <xarray.tests.test_variable.TestVariableWithDask object at 0x7f0e00bc5978>
    def test_index_0d_not_a_time(self):
        d = np.datetime64('NaT', 'ns')
        x = self.cls(['x'], [d])
>       self._assertIndexedLikeNDArray(x, d)
xarray/tests/test_variable.py:197: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
self = <xarray.tests.test_variable.TestVariableWithDask object at 0x7f0e00bc5978>
variable = <xarray.Variable (x: 1)>
dask.array<shape=(1,), dtype=datetime64[ns], chunksize=(1,)>
expected_value0 = numpy.datetime64('NaT'), expected_dtype = None
    def _assertIndexedLikeNDArray(self, variable, expected_value0,
                                  expected_dtype=None):
        """Given a 1-dimensional variable, verify that the variable is indexed
        like a numpy.ndarray.
        """
        assert variable[0].shape == ()
        assert variable[0].ndim == 0
        assert variable[0].size == 1
        # test identity
        assert variable.equals(variable.copy())
        assert variable.identical(variable.copy())
        # check value is equal for both ndarray and Variable
        with warnings.catch_warnings():
            warnings.filterwarnings('ignore', "In the future, 'NAT == x'")
>           assert variable.values[0] == expected_value0
E           AssertionError: assert numpy.datetime64('NaT') == numpy.datetime64('NaT')
E             -numpy.datetime64('NaT')
E             +numpy.datetime64('NaT')
xarray/tests/test_variable.py:143: AssertionError



__________________ TestIndexVariable.test_index_0d_not_a_time __________________
self = <xarray.tests.test_variable.TestIndexVariable object at 0x7f0e01063390>
    def test_index_0d_not_a_time(self):
        d = np.datetime64('NaT', 'ns')
        x = self.cls(['x'], [d])
>       self._assertIndexedLikeNDArray(x, d)
xarray/tests/test_variable.py:197: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
self = <xarray.tests.test_variable.TestIndexVariable object at 0x7f0e01063390>
variable = <xarray.IndexVariable 'x' (x: 1)>
array(['NaT'], dtype='datetime64[ns]')
expected_value0 = numpy.datetime64('NaT'), expected_dtype = None
    def _assertIndexedLikeNDArray(self, variable, expected_value0,
                                  expected_dtype=None):
        """Given a 1-dimensional variable, verify that the variable is indexed
        like a numpy.ndarray.
        """
        assert variable[0].shape == ()
        assert variable[0].ndim == 0
        assert variable[0].size == 1
        # test identity
        assert variable.equals(variable.copy())
        assert variable.identical(variable.copy())
        # check value is equal for both ndarray and Variable
        with warnings.catch_warnings():
            warnings.filterwarnings('ignore', "In the future, 'NAT == x'")
>           assert variable.values[0] == expected_value0
E           AssertionError: assert numpy.datetime64('NaT') == numpy.datetime64('NaT')
E             -numpy.datetime64('NaT')
E             +numpy.datetime64('NaT')
xarray/tests/test_variable.py:143: AssertionError

[shoyer]

We might just be able to switch these to use np.testing.assert_equal() (though I'm not sure if it handles NaT properly yet).

[dcherian]

Can we remove the warnings filter in the line above your change? Seems like it filtered the warning about this particular issue!

[shoyer]

Well, we might as well keep the filter so we don't see the warning with old NumPy versions. Though I agree, we clearly should not have ignored it!

…

On Tue, Jan 15, 2019 at 6:16 PM Deepak Cherian ***@***.***> wrote: Can we remove the warnings filter in the line above your change? Seems like it filtered the warning about this particular issue! — You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub <#2673 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABKS1sq8rZpjZs3FzLmYVwf_Ok5I86TDks5vDf7EgaJpZM4Z_m2a> .