DMSC Integration Testing

Test: nexusfiles-scipp|tbl|tbl_read_detector_everything|ngem_detector

2026-02-03 00:18:05: success

None

2026-02-02 00:16:57: success

None

2026-02-01 00:18:10: success

None

2026-01-31 00:17:18: success

None

2026-01-30 00:17:11: success

None

2026-01-29 00:17:33: success

None

2026-01-28 00:17:16: success

None

2026-01-27 00:17:30: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00016198.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-26 00:16:43: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00016058.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-25 00:18:29: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00015918.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-24 00:16:23: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00015785.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-23 00:17:36: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00015645.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-22 00:17:08: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00015505.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-21 00:16:15: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00014925.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-20 00:16:07: failed

2026-01-19 00:16:21: failed

2026-01-18 01:43:40: failed

2026-01-17 00:16:14: failed

2026-01-16 00:16:33: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00014817.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-14 00:17:06: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00014537.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-13 00:17:09: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00014396.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-12 00:16:45: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00014249.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-11 00:17:45: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00014109.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-10 00:16:34: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00013969.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-09 00:16:53: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00013829.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-08 00:16:20: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00013684.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-07 00:16:33: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00013551.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-06 00:16:10: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/coda_tbl_999999_00013411.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-05 00:15:21: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/tbl_999999_00011149.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2026-01-04 00:15:23: failed

2026-01-03 00:15:30: failed

2026-01-02 00:15:28: failed

2026-01-01 00:15:32: failed

2025-12-31 00:15:23: failed

2025-12-30 00:15:28: failed

2025-12-29 00:15:23: failed

2025-12-28 00:15:31: failed

2025-12-27 00:15:17: failed

2025-12-26 00:15:26: failed

2025-12-25 00:15:13: failed

2025-12-24 00:15:45: failed

2025-12-23 00:16:11: failed

2025-12-22 00:15:46: failed

2025-12-21 00:15:32: failed

2025-12-20 00:15:55: failed

2025-12-19 00:16:19: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/tbl_999999_00011072.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2025-12-18 00:16:17: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/tbl_999999_00010932.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2025-12-17 00:16:32: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/tbl_999999_00010806.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2025-12-16 00:16:14: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/tbl_999999_00010673.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError

2025-12-15 00:16:41: failed

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/999999/raw/tbl_999999_00010533.hdf')
detector_name = 'ngem_detector'
check_everything_events =

@pytest.mark.parametrize(
"detector_name",
[
"he3_detector_bank0",
"he3_detector_bank1",
"multiblade_detector",
"ngem_detector",
"timepix3_detector",
],
)
def test_tbl_read_detector_everything(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_everything_events: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

# Read the event data
> result = workflow.compute(RawDetector[SampleRun])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

tests/nexusfiles-scipp/tbl/tbl_load_nexus_test.py:130:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/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-tbl/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-tbl/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-tbl/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:423: in assemble_detector_data
neutron_data = 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-tbl/lib/python3.12/site-packages/ess/reduce/nexus/_nexus_loader.py:544: IndexError