Test vana norm and bkg subtraction

Author: jl-wynen

tests/dream/geant4_reduction_test.py

@@ -30,6 +30,7 @@
     DspacingData,
     EmptyCanSubtractedIofDspacing,
     Filename,
+    FocussedDataDspacing,
     IofDspacing,
     IofDspacingTwoTheta,
     IofTof,
@@ -55,9 +56,9 @@
 from ess.reduce import time_of_flight
 from ess.reduce import workflow as reduce_workflow
 
-sample = sc.vector([0.0, 0.0, 0.0], unit='mm')
-source = sc.vector([-3.478, 0.0, -76550], unit='mm')
-charge = sc.scalar(1.0, unit='µAh')
+sample_position = sc.vector([0.0, 0.0, 0.0], unit='mm')
+source_position = sc.vector([-3.478, 0.0, -76550], unit='mm')
+proton_charge = sc.scalar(1.0, unit='µAh')
 dream_source_position = sc.vector(value=[0, 0, -76.55], unit="m")
 
 params = {
@@ -73,12 +74,12 @@
     DspacingBins: sc.linspace('dspacing', 0.0, 2.3434, 201, unit='angstrom'),
     TofMask: lambda x: (x < sc.scalar(0.0, unit='us').to(unit=elem_unit(x)))
     | (x > sc.scalar(86e3, unit='us').to(unit=elem_unit(x))),
-    Position[snx.NXsample, SampleRun]: sample,
-    Position[snx.NXsample, VanadiumRun]: sample,
-    Position[snx.NXsource, SampleRun]: source,
-    Position[snx.NXsource, VanadiumRun]: source,
-    AccumulatedProtonCharge[SampleRun]: charge,
-    AccumulatedProtonCharge[VanadiumRun]: charge,
+    Position[snx.NXsample, SampleRun]: sample_position,
+    Position[snx.NXsample, VanadiumRun]: sample_position,
+    Position[snx.NXsource, SampleRun]: source_position,
+    Position[snx.NXsource, VanadiumRun]: source_position,
+    AccumulatedProtonCharge[SampleRun]: proton_charge,
+    AccumulatedProtonCharge[VanadiumRun]: proton_charge,
     TwoThetaMask: None,
     WavelengthMask: None,
     CaveMonitorPosition: sc.vector([0.0, 0.0, -4220.0], unit='mm'),
@@ -187,6 +188,31 @@ def test_pipeline_can_compute_dspacing_result_with_integrated_monitor_norm(
     assert sc.identical(result.coords['dspacing'], params[DspacingBins])
 
 
+def test_pipeline_normalizes_and_subtracts_empty_can_as_expected(
+    workflow: sciline.Pipeline,
+) -> None:
+    workflow[UncertaintyBroadcastMode] = UncertaintyBroadcastMode.drop
+    workflow = powder.with_pixel_mask_filenames(workflow, [])
+    results = workflow.compute(
+        [
+            EmptyCanSubtractedIofDspacing[SampleRun],
+            FocussedDataDspacing[SampleRun],
+            FocussedDataDspacing[VanadiumRun],
+            FocussedDataDspacing[BackgroundRun],
+        ]
+    )
+    result = results[EmptyCanSubtractedIofDspacing[SampleRun]]
+
+    sample = results[FocussedDataDspacing[SampleRun]]
+    empty_can = results[FocussedDataDspacing[BackgroundRun]]
+    vanadium = results[FocussedDataDspacing[VanadiumRun]]
+
+    expected = powder.correction.normalize_by_vanadium_dspacing(
+        sample.bins.concatenate(-empty_can), vanadium, UncertaintyBroadcastMode.drop
+    )
+    sc.testing.assert_allclose(result, expected)
+
+
 def test_workflow_is_deterministic(workflow):
     workflow = powder.with_pixel_mask_filenames(workflow, [])
     # This is Sciline's default scheduler, but we want to be explicit here