Source: python-xarray Version: 0.21.0-1 X-Debbugs-CC: [email protected], [email protected] Severity: serious User: [email protected] Usertags: regression
Hi Maintainer python-xarray's autopkgtests are failing on the big-endian s390x architecture [1]. I've copied what I hope is the relevant part of the log below. Regards Graham [1] https://ci.debian.net/packages/p/python-xarray/unstable/s390x/ =================================== FAILURES =================================== _______________________ test_calendar_cftime_2D[365_day] _______________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[0.25602205, 0.47375523, 0.88418655, ..., 0.19579452, ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: -259805407763208-03-07 00:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime _______________________ test_calendar_cftime_2D[360_day] _______________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[0.3348676 , 0.8813548 , 0.07158625, ..., 0.12469613, ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 768533895196513-09-16 16:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime _______________________ test_calendar_cftime_2D[julian] ________________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[0.05513783, 0.72362925, 0.78967474, ..., 0.8560986 , ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 904522921033531-11-08 08:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime ______________________ test_calendar_cftime_2D[all_leap] _______________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[0.02927022, 0.10328084, 0.12428704, ..., 0.83960594, ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: -77577995854656-10-03 16:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime _______________________ test_calendar_cftime_2D[366_day] _______________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[0.32570151, 0.71143133, 0.43459037, ..., 0.14784034, ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 391106800438843-10-05 00:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime ______________________ test_calendar_cftime_2D[gregorian] ______________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[0.91161183, 0.42436822, 0.53522578, ..., 0.36468928, ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: -690921531052547-07-02 08:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime _________________ test_calendar_cftime_2D[proleptic_gregorian] _________________ data = <xarray.DataArray 'data' (lon: 10, lat: 10, time: 100)> array([[[8.84930980e-01, 9.76547499e-01, 4.34131057e-01, ..., ...0.0 2.222 4.444 6.667 ... 13.33 15.56 17.78 20.0 * time (time) object 2000-01-01 00:00:00 ... 2000-01-05 03:00:00 @requires_cftime def test_calendar_cftime_2D(data) -> None: # 2D np datetime: > data = xr.DataArray( np.random.randint(1, 1000000, size=(4, 5)).astype("<M8[h]"), dims=("x", "y") ) /usr/lib/python3/dist-packages/xarray/tests/test_accessor_dt.py:426: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:400: in __init__ data = as_compatible_data(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:232: in as_compatible_data data = _possibly_convert_objects(data) /usr/lib/python3/dist-packages/xarray/core/variable.py:176: in _possibly_convert_objects return np.asarray(pd.Series(values.ravel())).reshape(values.shape) /usr/lib/python3/dist-packages/pandas/core/series.py:439: in __init__ data = sanitize_array(data, index, dtype, copy) /usr/lib/python3/dist-packages/pandas/core/construction.py:545: in sanitize_array subarr = _try_cast(data, dtype, copy, raise_cast_failure) /usr/lib/python3/dist-packages/pandas/core/construction.py:704: in _try_cast return sanitize_to_nanoseconds(arr, copy=copy) /usr/lib/python3/dist-packages/pandas/core/dtypes/cast.py:1740: in sanitize_to_nanoseconds values = conversion.ensure_datetime64ns(values) pandas/_libs/tslibs/conversion.pyx:256: in pandas._libs.tslibs.conversion.ensure_datetime64ns ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: -67784665697082-12-03 00:00:00 pandas/_libs/tslibs/np_datetime.pyx:120: OutOfBoundsDatetime
