Pass PSF sigma in to fallback source detector.

This is necessary in rare cases when convolving the template if building the kernel fails, and the fallback source detector attempts to calculate the template PSF at a chip gap.
lsst · Nov 28, 2024 · d50a149 · d50a149
1 parent 32906f2
commit d50a149
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Showing 2 changed files with 9 additions and 3 deletions.
diff --git a/python/lsst/ip/diffim/makeKernel.py b/python/lsst/ip/diffim/makeKernel.py
@@ -276,7 +276,7 @@ def getSelectSources(self, exposure, sigma=None, doSmooth=True, idFactory=None):
         return selectSources
 
     def makeCandidateList(self, convolved, reference, kernelSize,
-                          candidateList, preconvolved=False):
+                          candidateList, preconvolved=False, sigma=None):
         """Make a list of acceptable KernelCandidates.
 
         Generate a list of candidate sources for Psf-matching, remove sources
@@ -309,7 +309,7 @@ def makeCandidateList(self, convolved, reference, kernelSize,
             If ``candidateList`` is empty after sub-selection.
         """
         if candidateList is None:
-            candidateList = self.getSelectSources(reference, doSmooth=not preconvolved)
+            candidateList = self.getSelectSources(reference, doSmooth=not preconvolved, sigma=sigma)
             if len(candidateList) < 1:
                 raise RuntimeError("No kernel candidates after detection and measurement.")
 

diff --git a/python/lsst/ip/diffim/subtractImages.py b/python/lsst/ip/diffim/subtractImages.py
@@ -505,8 +505,14 @@ def runConvolveTemplate(self, template, science, selectSources):
             if self.config.allowKernelSourceDetection:
                 self.log.warning("Error encountered trying to construct the matching kernel"
                                  f" Running source detection and retrying. {e}")
+                kernelSize = self.makeKernel.makeKernelBasisList(
+                    self.templatePsfSize, self.sciencePsfSize)[0].getWidth()
+                sigmaToFwhm = 2*np.log(2*np.sqrt(2))
+                candidateList = self.makeKernel.makeCandidateList(template, science, kernelSize,
+                                                                  candidateList=None,
+                                                                  sigma=self.sciencePsfSize/sigmaToFwhm)
                 kernelSources = self.makeKernel.selectKernelSources(template, science,
-                                                                    candidateList=None,
+                                                                    candidateList=candidateList,
                                                                     preconvolved=False)
                 kernelResult = self.makeKernel.run(template, science, kernelSources,
                                                    preconvolved=False)