fix issue with mismatched peaklists at assessment time

Author: walshmm

src/snapred/backend/dao/request/CalibrationAssessmentRequest.py

@@ -37,6 +37,7 @@ class CalibrationAssessmentRequest(BaseModel):
         default_factory=lambda: Pair.model_validate(Config["calibration.parameters.default.FWHMMultiplier"])
     )
     maxChiSq: float = Field(default_factory=lambda: Config["constants.GroupDiffractionCalibration.MaxChiSq"])
+    combinedPixelMask: WorkspaceName | None = None
 
     @field_validator("fwhmMultipliers", mode="before")
     @classmethod

src/snapred/backend/recipe/algorithm/FitMultiplePeaksAlgorithm.py

@@ -78,6 +78,11 @@ def PyExec(self):
         )
         self.chopIngredients(reducedPeakList)
         self.unbagGroceries()
+        
+        numHisto = self.mantidSnapper.mtd[self.inputWorkspaceName].getNumberHistograms()
+        if numHisto < len(self.groupIDs):
+            raise ValueError(f"Number of histograms and number of GroupPeakLists do not match: {numHisto} vs {len(self.groupIDs)}")
+        
 
         for index, groupID in enumerate(self.groupIDs):
             spectrumInfo = self.mantidSnapper.mtd[self.inputWorkspaceName].spectrumInfo()
@@ -86,9 +91,7 @@ def PyExec(self):
                 raise ValueError(
                     f"Spectrum with NO DETECTORS encountered on {self.inputWorkspaceName} at index {index}"
                 )
-            if index >= numHisto or spectrumInfo.isMasked(index):
-                continue
-
+                
             tmpSpecName = mtd.unique_name(prefix=f"__tmp_fitspec_{index}_")
             outputNameTmp = mtd.unique_name(prefix=f"__tmp_fitdiag_{index}_")
             outputNamesTmp = {x: f"{outputNameTmp}{self.outputSuffix[x]}_{index}" for x in FitOutputEnum}

src/snapred/backend/service/CalibrationService.py

@@ -688,8 +688,8 @@ def assessQuality(self, request: CalibrationAssessmentRequest):
             maxChiSq=request.maxChiSq,
             state=state,
         )
-        pixelGroup = self.sousChef.prepPixelGroup(farmFresh)
-        detectorPeaks = self.sousChef.prepDetectorPeaks(farmFresh)
+        pixelGroup = self.sousChef.prepPixelGroup(farmFresh, pixelMask=request.combinedPixelMask)
+        detectorPeaks = self.sousChef.prepDetectorPeaks(farmFresh, pixelMask=request.combinedPixelMask)
 
         # TODO: We Need to Fit the Data
         fitResults = FitMultiplePeaksRecipe().executeRecipe(

src/snapred/backend/service/SousChef.py

@@ -337,11 +337,12 @@ def prepDiffractionCalibrationIngredients(
         self, ingredients: FarmFreshIngredients, combinedPixelMask: Optional[WorkspaceName] = None
     ) -> DiffractionCalibrationIngredients:
         self.verifyCalibrationExists(ingredients.runNumber, ingredients.useLiteMode)
-
+        pixelGroup=self.prepPixelGroup(ingredients, pixelMask=combinedPixelMask)
+        groupedPeakLists=self.prepDetectorPeaks(ingredients, pixelMask=combinedPixelMask)
         return DiffractionCalibrationIngredients(
             runConfig=self.prepRunConfig(ingredients.runNumber),
-            pixelGroup=self.prepPixelGroup(ingredients, pixelMask=combinedPixelMask),
-            groupedPeakLists=self.prepDetectorPeaks(ingredients, pixelMask=combinedPixelMask),
+            pixelGroup=pixelGroup,
+            groupedPeakLists=groupedPeakLists,
             peakFunction=ingredients.peakFunction,
             convergenceThreshold=ingredients.convergenceThreshold,
             maxOffset=ingredients.maxOffset,

src/snapred/ui/workflow/DiffCalWorkflow.py

@@ -540,6 +540,8 @@ def _renewFocus(self, groupingIndex):
         return response
 
     def _renewFitPeaks(self, peakFunction):
+        logger.info(f"there are {len(self.ingredients.pixelGroup.groupIDs)} groups, and {len(self.ingredients.groupedPeakLists)} peak lists")
+
         payload = FitMultiplePeaksRequest(
             inputWorkspace=self.focusedWorkspace,
             outputWorkspaceGroup=self.fitPeaksDiagnostic,
@@ -655,6 +657,7 @@ def _triggerDiffractionCalibration(self, workflowPresenter):
             nBinsAcrossPeakWidth=self.nBinsAcrossPeakWidth,
             fwhmMultipliers=self.prevFWHM,
             maxChiSq=self.maxChiSq,
+            combinedPixelMask=self.combinedPixelMaskName,
         )
 
         response = self.request(path="calibration/assessment", payload=payload)