xarray/tests/test_dataarray.py::TestDataArray::test_curvefit_helpers: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[365_day]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[360_day]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[julian]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[all_leap]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[366_day]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[gregorian]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_cftimeindex.py::test_distant_cftime_datetime_sub_cftimeindex[proleptic_gregorian]: Failed: DID NOT RAISE <class 'ValueError'>
xarray/tests/test_groupby.py::test_groupby_bins_datetime_mean: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.DataArray 'time' (index_bins: 148)> Size: 1kB\narray(['2020-01-01T03:00:00.000000', '2020-01-01T08:00:00.000000... dtype='datetime64[us]')\nCoordinates:\n * index_bins (index_bins) interval[int64, right] 2kB (0, 5] ... (735, 740].dtype
+ where <xarray.DataArray 'time' (index_bins: 148)> Size: 1kB\narray(['2020-01-01T03:00:00.000000', '2020-01-01T08:00:00.000000... dtype='datetime64[us]')\nCoordinates:\n * index_bins (index_bins) interval[int64, right] 2kB (0, 5] ... (735, 740] = <xarray.Dataset> Size: 5kB\nDimensions: (index_bins: 148)\nCoordinates:\n * index_bins (index_bins) interval[int64,...64[us] 1kB 2020-01-01T03:00:00 ... 2020-...\n float (index_bins) float64 1kB 0.004032 0.01075 ... 0.9852 0.9919.time
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_groupby.py::test_groupby_bins_mean_time_series: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.DataArray 'time' (trial_bins: 5)> Size: 40B\narray(['2024-01-01T15:00:03.333333', '2024-01-01T15:00:16.666666',..., dtype='datetime64[us]')\nCoordinates:\n * trial_bins (trial_bins) interval[float64, right] 80B (-0.009, 1.8] ... (....dtype
+ where <xarray.DataArray 'time' (trial_bins: 5)> Size: 40B\narray(['2024-01-01T15:00:03.333333', '2024-01-01T15:00:16.666666',..., dtype='datetime64[us]')\nCoordinates:\n * trial_bins (trial_bins) interval[float64, right] 80B (-0.009, 1.8] ... (... = <xarray.Dataset> Size: 160B\nDimensions: (trial_bins: 5)\nCoordinates:\n * trial_bins (trial_bins) interval[float...s) float64 40B 5.0 25.0 45.0 65.0 85.0\n time (trial_bins) datetime64[us] 40B 2024-01-01T15:00:03.333333 .....time
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_interp.py::test_datetime[x_new2-expected2]: AssertionError: Left and right DataArray objects are not close
Differing values:
L
array([nan, nan])
R
array([0.5, 1.5])
xarray/tests/test_interp.py::test_datetime[x_new3-expected3]: AssertionError: Left and right DataArray objects are not close
Differing values:
L
array([nan, nan, nan])
R
array([0.5, 1.5, nan])
xarray/tests/test_interp.py::test_datetime[x_new4-0.5]: AssertionError: Left and right DataArray objects are not close
Differing values:
L
array([nan])
R
array([0.5])
xarray/tests/test_interp.py::test_datetime_single_string: AssertionError: Left and right DataArray objects are not close
Differing values:
L
array(nan)
R
array(0.5)
xarray/tests/test_variable.py::test_as_compatible_data_writeable[data0]: pandas.errors.Pandas4Warning: Copy-on-Write can no longer be disabled, setting to False has no impact. This option will be removed in pandas 4.0.
xarray/tests/test_variable.py::test_as_compatible_data_writeable[data1]: pandas.errors.Pandas4Warning: Copy-on-Write can no longer be disabled, setting to False has no impact. This option will be removed in pandas 4.0.
xarray/tests/test_variable.py::TestVariable::test_index_0d_timedelta64: AssertionError: assert dtype('<m8[us]') == 'timedelta64[ns]'
+ where dtype('<m8[us]') = np.timedelta64(3600000000,'us').dtype
xarray/tests/test_variable.py::TestVariable::test_datetime64_conversion[values0-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.Variable (t: 3)> Size: 24B\narray(['1970-01-01T00:00:00.000000', '1970-01-02T00:00:00.000000',\n '1970-01-03T00:00:00.000000'], dtype='datetime64[us]').dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestVariable::test_datetime64_conversion[values1-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.Variable (t: 3)> Size: 24B\narray(['1970-01-01T00:00:00.000000', '1970-01-02T00:00:00.000000',\n '1970-01-03T00:00:00.000000'], dtype='datetime64[us]').dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestVariable::test_timedelta64_conversion[values5-ns]: AssertionError: assert dtype('<m8[us]') == dtype('<m8[ns]')
+ where dtype('<m8[us]') = <xarray.Variable (t: 3)> Size: 24B\narray([ 0, 86400000000, 172800000000], dtype='timedelta64[us]').dtype
+ and dtype('<m8[ns]') = <class 'numpy.dtype'>('timedelta64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestVariable::test_timedelta64_conversion_scalar[values4-ns]: AssertionError: assert dtype('<m8[us]') == dtype('<m8[ns]')
+ where dtype('<m8[us]') = <xarray.Variable ()> Size: 8B\narray(86400000000, dtype='timedelta64[us]').dtype
+ and dtype('<m8[ns]') = <class 'numpy.dtype'>('timedelta64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestVariableWithDask::test_index_0d_timedelta64: AssertionError: assert dtype('<m8[us]') == 'timedelta64[ns]'
+ where dtype('<m8[us]') = np.timedelta64(3600000000,'us').dtype
xarray/tests/test_variable.py::TestVariableWithDask::test_datetime64_conversion[values0-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.Variable (t: 3)> Size: 24B\ndask.array<array, shape=(3,), dtype=datetime64[us], chunksize=(3,), chunktype=numpy.ndarray>.dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestVariableWithDask::test_datetime64_conversion[values1-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.Variable (t: 3)> Size: 24B\ndask.array<array, shape=(3,), dtype=datetime64[us], chunksize=(3,), chunktype=numpy.ndarray>.dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestVariableWithDask::test_timedelta64_conversion[values5-ns]: AssertionError: assert dtype('<m8[us]') == dtype('<m8[ns]')
+ where dtype('<m8[us]') = <xarray.Variable (t: 3)> Size: 24B\ndask.array<array, shape=(3,), dtype=timedelta64[us], chunksize=(3,), chunktype=numpy.ndarray>.dtype
+ and dtype('<m8[ns]') = <class 'numpy.dtype'>('timedelta64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestIndexVariable::test_timedelta64_conversion[values5-ns]: AssertionError: assert dtype('<m8[us]') == dtype('<m8[ns]')
+ where dtype('<m8[us]') = <xarray.IndexVariable 't' (t: 3)> Size: 24B\narray([ 0, 86400000000, 172800000000], dtype='timedelta64[us]').dtype
+ and dtype('<m8[ns]') = <class 'numpy.dtype'>('timedelta64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestIndexVariable::test_concat_periods: ValueError: Could not convert <xarray.IndexVariable 't' (t: 5)> Size: 40B
<PeriodArray>
['2000-01-01', '2000-01-02', '2000-01-03', '2000-01-04', '2000-01-05']
Length: 5, dtype: period[D] to a NumPy dtype (via `.dtype` value period[D]).
xarray/tests/test_variable.py::test_datetime_conversion[DatetimeIndex(['2000-01-01'], dtype='datetime64[us]', freq='D')-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.Variable (time: 1)> Size: 8B\narray(['2000-01-01T00:00:00.000000'], dtype='datetime64[us]').dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::test_datetime_conversion[DatetimeIndex(['2000-01-01 00:00:00-05:00'], dtype='datetime64[us, America/New_York]', freq='D')-ns]: AssertionError: assert datetime64[us, America/New_York] == datetime64[ns, America/New_York]
+ where datetime64[us, America/New_York] = DatetimeIndex(['2000-01-01 00:00:00-05:00'], dtype='datetime64[us, America/New_York]', freq='D').dtype
+ where DatetimeIndex(['2000-01-01 00:00:00-05:00'], dtype='datetime64[us, America/New_York]', freq='D') = PandasIndexingAdapter(array=DatetimeIndex(['2000-01-01 00:00:00-05:00'], dtype='datetime64[us, America/New_York]', freq='D'), dtype=datetime64[us, America/New_York]).array
+ where PandasIndexingAdapter(array=DatetimeIndex(['2000-01-01 00:00:00-05:00'], dtype='datetime64[us, America/New_York]', freq='D'), dtype=datetime64[us, America/New_York]) = <xarray.Variable (time: 1)> Size: 8B\n<DatetimeArray>\n['2000-01-01 00:00:00-05:00']\nLength: 1, dtype: datetime64[us, America/New_York]._data
+ and datetime64[ns, America/New_York] = <class 'pandas.DatetimeTZDtype'>('ns', <DstTzInfo 'America/New_York' LMT-1 day, 19:04:00 STD>)
+ where <class 'pandas.DatetimeTZDtype'> = pd.DatetimeTZDtype
+ and <DstTzInfo 'America/New_York' LMT-1 day, 19:04:00 STD> = <function timezone at 0x7f69f68bfe20>('America/New_York')
+ where <function timezone at 0x7f69f68bfe20> = pytz.timezone
xarray/tests/test_variable.py::test_datetime_conversion[0 2000-01-01 00:00:00-05:00\ndtype: datetime64[us, America/New_York]-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.Variable (time: 1)> Size: 8B\narray(['2000-01-01T05:00:00.000000'], dtype='datetime64[us]').dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::test_timedelta_conversion[1 day, 0:00:00-ns]: AssertionError: assert dtype('<m8[us]') == dtype('<m8[ns]')
+ where dtype('<m8[us]') = <xarray.Variable ()> Size: 8B\narray(86400000000, dtype='timedelta64[us]').dtype
+ and dtype('<m8[ns]') = <class 'numpy.dtype'>('timedelta64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::test_timedelta_conversion[[datetime.timedelta(days=1)]-ns]: AssertionError: assert dtype('<m8[us]') == dtype('<m8[ns]')
+ where dtype('<m8[us]') = <xarray.Variable (time: 1)> Size: 8B\narray([86400000000], dtype='timedelta64[us]').dtype
+ and dtype('<m8[ns]') = <class 'numpy.dtype'>('timedelta64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestIndexVariable::test_index_0d_timedelta64: AssertionError: assert dtype('<m8[us]') == 'timedelta64[ns]'
+ where dtype('<m8[us]') = np.timedelta64(3600000000,'us').dtype
xarray/tests/test_variable.py::TestIndexVariable::test_datetime64_conversion[values0-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.IndexVariable 't' (t: 3)> Size: 24B\narray(['1970-01-01T00:00:00.000000', '1970-01-02T00:00:00.000000',\n '1970-01-03T00:00:00.000000'], dtype='datetime64[us]').dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
xarray/tests/test_variable.py::TestIndexVariable::test_datetime64_conversion[values1-ns]: AssertionError: assert dtype('<M8[us]') == dtype('<M8[ns]')
+ where dtype('<M8[us]') = <xarray.IndexVariable 't' (t: 3)> Size: 24B\narray(['1970-01-01T00:00:00.000000', '1970-01-02T00:00:00.000000',\n '1970-01-03T00:00:00.000000'], dtype='datetime64[us]').dtype
+ and dtype('<M8[ns]') = <class 'numpy.dtype'>('datetime64[ns]')
+ where <class 'numpy.dtype'> = np.dtype
