DMSC Integration Testing

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00084401.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00084261.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00084128.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083992.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083866.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083740.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083607.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083474.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083341.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083215.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError

workflow =
coda_nexus_file_path = PosixPath('/ess/data/coda/2025/999999/raw/999999_00083082.hdf')
detector_name = 'detector_panel_1'
check_detector_positions =

@pytest.mark.parametrize("detector_name", [f"detector_panel_{i}" for i in range(3)])
def test_nmx_read_detector_geometry(
workflow: sciline.Pipeline,
coda_nexus_file_path: Path,
detector_name: str,
check_detector_positions: Callable,
) -> None:
workflow[Filename[SampleRun]] = coda_nexus_file_path
workflow[NeXusDetectorName] = detector_name

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

tests/nexusfiles-scipp/nmx/nmx_load_nexus_test.py:37:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/sciline/pipeline.py:191: in compute
return self.get(tp, **kwargs).compute(reporter=reporter)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/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-nmx/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-nmx/lib/python3.12/site-packages/dask/threaded.py:91: in get
results = get_async(
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:549: in get_async
raise_exception(exc, tb)
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:353: in reraise
raise exc
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/local.py:258: in execute_task
result = task(data)
^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/_task_spec.py:759: in __call__
return self.func(*new_argspec)
^^^^^^^^^^^^^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/dask/utils.py:80: in apply
return func(*args)
^^^^^^^^^^^
.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:340: in to_transformation
t.value = _time_filter(t.value['time', interval.value])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

transform =
Dimensions: Sizes[time:0, ]
Coordinates:
* average_value float64 [deg] () 0... datetime64 [ns] (time) []
Data:
float64 [deg] (time) []



def _time_filter(transform: sc.DataArray) -> sc.Variable:
if transform.ndim == 0 or transform.sizes == {'time': 1}:
return transform.data.squeeze()
> raise ValueError(
f"Transform is time-dependent: {transform}, but no filter is provided."
)
E ValueError: Transform is time-dependent:
E Dimensions: Sizes[time:0, ]
E Coordinates:
E * average_value float64 [deg] () 0
E * maximum_value float64 [deg] () 0
E * minimum_value float64 [deg] () 0
E * time datetime64 [ns] (time) []
E Data:
E float64 [deg] (time) []
E
E , but no filter is provided.

.tox/nexusfiles-scipp-nmx/lib/python3.12/site-packages/ess/reduce/nexus/workflow.py:294: ValueError