DMSC Integration Testing

Test: nexusfiles-scipp|odin|can_compute_tof|timepix3

2025-11-01 00:16:50: success

None

2025-10-31 00:16:02: success

None

2025-10-30 00:17:07: success

None

2025-10-29 00:16:49: success

None

2025-10-28 00:17:11: success

None

2025-10-27 00:16:43: success

None

2025-10-26 00:16:45: success

None

2025-10-25 00:16:32: success

None

2025-10-24 00:17:18: success

None

2025-10-23 00:16:34: success

None

2025-10-22 00:17:38: success

None

2025-10-21 00:16:49: success

None

2025-10-20 00:16:39: success

None

2025-10-19 00:17:21: success

None

2025-10-18 00:16:54: success

None

2025-10-17 00:16:42: success

None

2025-10-16 00:16:34: success

None

2025-10-15 00:16:18: success

None

2025-10-14 00:16:00: success

None

2025-10-13 11:45:08: success

None

2025-10-09 00:16:04: success

None

2025-10-08 00:15:55: success

None

2025-10-07 00:16:13: success

None

2025-10-06 11:14:15: success

None

2025-10-06 10:46:35: success

None

2025-10-03 00:15:48: success

None

2025-10-02 00:16:21: success

None

2025-10-01 00:16:11: success

None

2025-09-30 00:17:51: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/977695/raw/odin_977695_00086385.hdf')

def test_can_compute_tof__timepix3(
workflow: sciline.Pipeline, coda_nexus_file_path: Path
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = "event_mode_detectors/timepix3"

> result = workflow.compute(DetectorTofData[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/odin/odin_reduction_test.py:33:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/task_graph.py:122: in compute
return self._scheduler.get(self._graph, [targets], reporter=reporter)[0]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/scheduler.py:119: in get
return self._dask_get(dsk, list(map(_to_dask_key, keys)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:455: in assemble_detector_data
grouped = nexus.group_event_data(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

def group_event_data(
*, event_data: sc.DataArray, detector_number: sc.Variable
) -> sc.DataArray:
"""Group event data by detector number.

The detector_number variable also defines the output shape and dimension names.

Parameters
----------
event_data:
Data array with events to group, as returned from :py:func:`load_event_data`.
detector_number:
Variable with detector numbers matching the `event_id` field of the event data.

Returns
-------
:
Data array with events grouped by detector number.
"""
event_id = detector_number.flatten(to='event_id').copy()
constituents = event_data.bins.constituents
begin = constituents['begin']
end = constituents['end']
data = constituents['data'].copy(deep=False)
if 'event_time_zero' in event_data.coords:
data.coords['event_time_zero'] = sc.bins_like(
event_data, fill_value=event_data.coords['event_time_zero']
).bins.constituents['data']
# After loading raw NXevent_data it is guaranteed that the event table
# is contiguous and that there is no masking. We can therefore use the
# more efficient approach of binning from scratch instead of erasing the
# 'event_time_zero' binning defined by NXevent_data. This sanity check should
# therefore always pass unless some unusual modifications were performed.
if (
event_data.masks
> or begin[0] != sc.index(0)
^^^^^^^^
or end[-1] != sc.index(data.sizes[data.dim])
or (begin[1:] != end[:-1]).any()
):
E IndexError: The requested index 0 is out of range. Dimension size is 0 and the allowed range is [0:-1].

.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:414: IndexError

2025-09-29 00:16:39: success

None

2025-09-28 00:16:30: success

None

2025-09-27 00:16:22: success

None

2025-09-26 00:16:43: success

None

2025-09-25 00:16:31: success

None

2025-09-24 00:17:04: success

None

2025-09-23 00:16:56: success

None

2025-09-22 00:16:19: success

None

2025-09-21 00:16:57: success

None

2025-09-20 00:16:16: success

None

2025-09-19 00:15:56: success

None

2025-09-18 00:16:48: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00084827.hdf')

def test_can_compute_tof__timepix3(
workflow: sciline.Pipeline, coda_nexus_file_path: Path
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = "event_mode_detectors/timepix3"

> result = workflow.compute(DetectorTofData[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/odin/odin_reduction_test.py:33:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/task_graph.py:122: in compute
return self._scheduler.get(self._graph, [targets], reporter=reporter)[0]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/scheduler.py:119: in get
return self._dask_get(dsk, list(map(_to_dask_key, keys)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/utils.py:78: in apply
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:392: in get_calibrated_detector
offsets = snx.zip_pixel_offsets(da.coords).transpose(da.dims).copy()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/scipp/core/shape.py:389: in transpose
return _call_cpp_func(_cpp.transpose, x, dims if dims is not None else []) # type: ignore[return-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

func =
args = ( (dim_0: 4096) vector3 [m] [(-0.00703828, -0.00703828, 0), (-0.00703484, -0.00703484, 0), ..., (0.00703484, 0.00703484, 0), (0.00703828, 0.00703828, 0)], ('dim_0', 'dim_1'))
kwargs = {}, out = None

def call_func(
func: Callable[_P, _R],
*args: _P.args,
**kwargs: _P.kwargs,
) -> _R | DataGroup[Any]:
out = kwargs.pop('out', None)
if any(isinstance(x, DataGroup) for x in itertools.chain(args, kwargs.values())):
if out is not None:
raise ValueError(
"`out` argument is not supported for DataGroup operations."
)
return data_group_nary(func, *args, **kwargs)
if out is None:
> return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
E scipp._scipp.core.DimensionError: Cannot transpose: Requested new dimension order contains different number of labels.

.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/scipp/core/_cpp_wrapper_util.py:27: DimensionError

2025-09-17 00:16:26: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00084691.hdf')

def test_can_compute_tof__timepix3(
workflow: sciline.Pipeline, coda_nexus_file_path: Path
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = "event_mode_detectors/timepix3"

> result = workflow.compute(DetectorTofData[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/odin/odin_reduction_test.py:33:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/task_graph.py:122: in compute
return self._scheduler.get(self._graph, [targets], reporter=reporter)[0]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/scheduler.py:119: in get
return self._dask_get(dsk, list(map(_to_dask_key, keys)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/utils.py:78: in apply
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:392: in get_calibrated_detector
offsets = snx.zip_pixel_offsets(da.coords).transpose(da.dims).copy()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/scipp/core/shape.py:389: in transpose
return _call_cpp_func(_cpp.transpose, x, dims if dims is not None else []) # type: ignore[return-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

func =
args = ( (dim_0: 4096) vector3 [m] [(-0.00703828, -0.00703828, 0), (-0.00703484, -0.00703484, 0), ..., (0.00703484, 0.00703484, 0), (0.00703828, 0.00703828, 0)], ('dim_0', 'dim_1'))
kwargs = {}, out = None

def call_func(
func: Callable[_P, _R],
*args: _P.args,
**kwargs: _P.kwargs,
) -> _R | DataGroup[Any]:
out = kwargs.pop('out', None)
if any(isinstance(x, DataGroup) for x in itertools.chain(args, kwargs.values())):
if out is not None:
raise ValueError(
"`out` argument is not supported for DataGroup operations."
)
return data_group_nary(func, *args, **kwargs)
if out is None:
> return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
E scipp._scipp.core.DimensionError: Cannot transpose: Requested new dimension order contains different number of labels.

.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/scipp/core/_cpp_wrapper_util.py:27: DimensionError

2025-09-16 00:16:58: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00084551.hdf')

def test_can_compute_tof__timepix3(
workflow: sciline.Pipeline, coda_nexus_file_path: Path
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = "event_mode_detectors/timepix3"

> result = workflow.compute(DetectorTofData[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/odin/odin_reduction_test.py:33:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/task_graph.py:122: in compute
return self._scheduler.get(self._graph, [targets], reporter=reporter)[0]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/sciline/scheduler.py:119: in get
return self._dask_get(dsk, list(map(_to_dask_key, keys)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/dask/utils.py:78: in apply
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:392: in get_calibrated_detector
offsets = snx.zip_pixel_offsets(da.coords).transpose(da.dims).copy()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/scipp/core/shape.py:389: in transpose
return _call_cpp_func(_cpp.transpose, x, dims if dims is not None else []) # type: ignore[return-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

func =
args = ( (dim_0: 4096) vector3 [m] [(-0.00703828, -0.00703828, 0), (-0.00703484, -0.00703484, 0), ..., (0.00703484, 0.00703484, 0), (0.00703828, 0.00703828, 0)], ('dim_0', 'dim_1'))
kwargs = {}, out = None

def call_func(
func: Callable[_P, _R],
*args: _P.args,
**kwargs: _P.kwargs,
) -> _R | DataGroup[Any]:
out = kwargs.pop('out', None)
if any(isinstance(x, DataGroup) for x in itertools.chain(args, kwargs.values())):
if out is not None:
raise ValueError(
"`out` argument is not supported for DataGroup operations."
)
return data_group_nary(func, *args, **kwargs)
if out is None:
> return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
E scipp._scipp.core.DimensionError: Cannot transpose: Requested new dimension order contains different number of labels.

.tox/nexusfiles-scipp-odin/lib/python3.12/site-packages/scipp/core/_cpp_wrapper_util.py:27: DimensionError

2025-09-15 00:16:36: success

None

2025-09-14 00:16:23: success

None

2025-09-13 00:16:33: success

None