write correct calibrant to norm record and then use it in reduction (#448)

* write correct calibrant to norm record and then use it in reduction

* update tests

Author: walshmm

src/snapred/backend/dao/normalization/NormalizationRecord.py

@@ -28,6 +28,7 @@ class NormalizationRecord(BaseModel):
     workspaceNames: List[WorkspaceName] = []
     version: int = Config["instrument.startingVersionNumber"]
     crystalDBounds: Limit[float]
+    normalizationCalibrantSamplePath: str
 
     @field_validator("runNumber", "backgroundRunNumber", mode="before")
     @classmethod

src/snapred/backend/service/NormalizationService.py

@@ -169,6 +169,7 @@ def normalizationAssessment(self, request: NormalizationRequest):
             peakIntensityThreshold=request.peakIntensityThreshold,
             backgroundRunNumber=request.backgroundRunNumber,
             smoothingParameter=request.smoothingParameter,
+            normalizationCalibrantSamplePath=request.calibrantSamplePath,
             calibration=calibration,
             crystalDBounds=request.crystalDBounds,
         )

src/snapred/backend/service/SousChef.py

@@ -194,7 +194,7 @@ def prepReductionIngredients(
             )
         # grab information from records
         ingredients_ = ingredients.model_copy()
-        ingredients_.calibrantSamplePath = calibrationRecord.calibrationFittingIngredients.calibrantSamplePath
+        ingredients_.calibrantSamplePath = normalizationRecord.normalizationCalibrantSamplePath
         ingredients_.cifPath = self.dataFactoryService.getCifFilePath(Path(ingredients_.calibrantSamplePath).stem)
         ingredients_.peakIntensityThreshold = normalizationRecord.peakIntensityThreshold
         return ReductionIngredients(

tests/resources/inputs/normalization/NormalizationRecord.json

@@ -4,6 +4,7 @@
     "backgroundRunNumber": 58813,
     "smoothingParameter": 0.5,
     "peakIntensityThreshold": 0.05,
+    "normalizationCalibrantSamplePath": "/path/to/sample",
     "calibration":{
         "instrumentState": {
             "id": "ab8704b0bc2a2342",

tests/unit/backend/service/test_SousChef.py

@@ -324,17 +324,18 @@ def test_prepDetectorPeaks_cache(self, DetectorPeakPredictorRecipe):
 
     @mock.patch(thisService + "ReductionIngredients")
     def test_prepReductionIngredients(self, ReductionIngredients):
-        record = mock.Mock(
-            smoothingParamter=1.0,
-            calibrationFittingIngredients=mock.Mock(calibrantSamplePath="a/b.x"),
+        calibrationRecord = mock.Mock()
+        normalizationRecord = mock.Mock(
+            smoothingParameter=1.0,
+            normalizationCalibrantSamplePath="a/b.x",
         )
         self.instance.prepRunConfig = mock.Mock()
         self.instance.prepManyPixelGroups = mock.Mock()
         self.instance.prepManyDetectorPeaks = mock.Mock()
         self.instance.dataFactoryService.getCifFilePath = mock.Mock()
         self.instance.dataFactoryService.getReductionState = mock.Mock()
-        self.instance.dataFactoryService.getNormalizationRecord = mock.Mock(return_value=record)
-        self.instance.dataFactoryService.getCalibrationRecord = mock.Mock(return_value=record)
+        self.instance.dataFactoryService.getNormalizationRecord = mock.Mock(return_value=normalizationRecord)
+        self.instance.dataFactoryService.getCalibrationRecord = mock.Mock(return_value=calibrationRecord)
 
         res = self.instance.prepReductionIngredients(self.ingredients)
 
@@ -343,7 +344,7 @@ def test_prepReductionIngredients(self, ReductionIngredients):
         assert ReductionIngredients.called_once_with(
             maskList=[],
             pixelGroups=self.instance.prepManyPixelGroups.return_value,
-            smoothingParameter=record.smoothingParameter,
+            smoothingParameter=normalizationRecord.smoothingParameter,
             detectorPeaksMany=self.instance.prepManyDetectorPeaks.return_value,
         )
         assert res == ReductionIngredients.return_value