Prune unused domain types in dream workflows

pyproject.toml

@@ -31,7 +31,7 @@ requires-python = ">=3.10"
 # Make sure to list one dependency per line.
 dependencies = [
   "dask",
-  "essreduce>=24.11.3",
+  "essreduce>=24.12.0",
   "graphviz",
   "numpy",
   "plopp",

src/ess/dream/io/geant4.py

@@ -22,9 +22,12 @@
     NeXusDetectorName,
     Position,
     RunType,
+    SampleRun,
+    VanadiumRun,
 )
 from ess.reduce.nexus.types import CalibratedBeamline
 from ess.reduce.nexus.workflow import GenericNeXusWorkflow
+from ess.reduce.workflow import prune_nexus_domain_types
 
 MANTLE_DETECTOR_ID = sc.index(7)
 HIGH_RES_DETECTOR_ID = sc.index(8)
@@ -281,4 +284,13 @@ def LoadGeant4Workflow() -> sciline.Pipeline:
     wf.insert(dummy_assemble_monitor_data)
     wf.insert(dummy_source_position)
     wf.insert(dummy_sample_position)
+
+    wf = prune_nexus_domain_types(
+        wf,
+        targets=(CalibrationData,),
+        targets_per_run=(DetectorData,),
+        targets_per_run_and_monitor=(MonitorData,),
+        run_types=(SampleRun, VanadiumRun),
+        monitor_types=(CaveMonitor,),
+    )
     return wf

src/ess/dream/workflow.py

@@ -18,16 +18,18 @@
 from ess.powder.types import (
     AccumulatedProtonCharge,
     CaveMonitorPosition,  # Should this be a DREAM-only parameter?
+    IofDspacingTwoTheta,
     PixelMaskFilename,
     Position,
+    ReducedTofCIF,
     SampleRun,
     TofMask,
     TwoThetaMask,
     VanadiumRun,
     WavelengthMask,
 )
 from ess.reduce.parameter import parameter_mappers
-from ess.reduce.workflow import register_workflow
+from ess.reduce.workflow import prune_nexus_domain_types, register_workflow
 
 from .io.cif import CIFAuthors, prepare_reduced_tof_cif
 from .io.geant4 import LoadGeant4Workflow
@@ -66,6 +68,9 @@ def DreamGeant4Workflow(*, run_norm: RunNormalization) -> sciline.Pipeline:
     for provider in itertools.chain(powder_providers, _dream_providers):
         wf.insert(provider)
     insert_run_normalization(wf, run_norm)
+
+    wf = prune_nexus_domain_types(wf, targets=(ReducedTofCIF, IofDspacingTwoTheta))
+
     for key, value in default_parameters().items():
         wf[key] = value
     wf.typical_outputs = typical_outputs