DM-51360: also use template mask plane for kernel candidate selection

python/lsst/ip/diffim/makeKernel.py

@@ -335,6 +335,11 @@ def makeCandidateList(self, convolved, reference, kernelSize,
             if (reference.subset(bbox).mask.array & bitmask).any():
                 good[i] = False
                 continue
+
+            # Reject footprints with any bad mask bits set.
+            if (convolved.subset(bbox).mask.array & bitmask).any():
+                good[i] = False
+                continue
         candidates = candidateList[good].copy(deep=True)
 
         self.log.info("Selected %d / %d sources as kernel candidates.", good.sum(), len(candidateList))

python/lsst/ip/diffim/subtractImages.py

@@ -858,7 +858,6 @@ def _sourceSelector(self, sources, mask):
 
         selected = self.sourceSelector.selectSources(sources).selected
         nInitialSelected = np.count_nonzero(selected)
-        selected *= self._checkMask(mask, sources, self.config.excludeMaskPlanes)
         nSelected = np.count_nonzero(selected)
         self.log.info("Rejecting %i candidate sources: an excluded template mask plane is set.",
                       nInitialSelected - nSelected)
@@ -885,47 +884,6 @@ def _sourceSelector(self, sources, mask):
 
         return selectSources
 
-    @staticmethod
-    def _checkMask(mask, sources, excludeMaskPlanes, checkAdjacent=True):
-        """Exclude sources that are located on or adjacent to masked pixels.
-
-        Parameters
-        ----------
-        mask : `lsst.afw.image.Mask`
-            The image mask plane to use to reject sources
-            based on the location of their centroid on the ccd.
-        sources : `lsst.afw.table.SourceCatalog`
-            The source catalog to evaluate.
-        excludeMaskPlanes : `list` of `str`
-            List of the names of the mask planes to exclude.
-
-        Returns
-        -------
-        flags : `numpy.ndarray` of `bool`
-            Array indicating whether each source in the catalog should be
-            kept (True) or rejected (False) based on the value of the
-            mask plane at its location.
-        """
-        setExcludeMaskPlanes = [
-            maskPlane for maskPlane in excludeMaskPlanes if maskPlane in mask.getMaskPlaneDict()
-        ]
-
-        excludePixelMask = mask.getPlaneBitMask(setExcludeMaskPlanes)
-
-        xv = (np.rint(sources.getX() - mask.getX0())).astype(int)
-        yv = (np.rint(sources.getY() - mask.getY0())).astype(int)
-
-        flags = np.ones(len(sources), dtype=bool)
-        if checkAdjacent:
-            pixRange = (0, -1, 1)
-        else:
-            pixRange = (0,)
-        for j in pixRange:
-            for i in pixRange:
-                mv = mask.array[yv + j, xv + i]
-                flags *= np.bitwise_and(mv, excludePixelMask) == 0
-        return flags
-
     def _prepareInputs(self, template, science, visitSummary=None):
         """Perform preparatory calculations common to all Alard&Lupton Tasks.
 

tests/test_detectAndMeasure.py

@@ -32,7 +32,7 @@
 import lsst.utils.tests
 import lsst.meas.base.tests
 
-from utils import makeTestImage
+from utils import makeTestImage, checkMask
 
 
 class DetectAndMeasureTestBase:
@@ -505,7 +505,6 @@ def test_exclude_mask_detections(self):
         science, sources = makeTestImage(noiseLevel=noiseLevel, noiseSeed=6, **kwargs)
         matchedTemplate, _ = makeTestImage(noiseLevel=noiseLevel/4, noiseSeed=7, **kwargs)
 
-        _checkMask = subtractImages.AlardLuptonSubtractTask._checkMask
         # Configure the detection Task
         detectionTask = self._setup_detection()
         excludeMaskPlanes = detectionTask.config.detection.excludeMaskPlanes
@@ -530,7 +529,7 @@ def _detection_wrapper(setFlags=True):
                     difference[srcBbox].mask.array |= lsst.afw.image.Mask.getPlaneBitMask(badMask)
             output = detectionTask.run(science, matchedTemplate, difference)
             refIds = []
-            goodSrcFlags = _checkMask(difference.mask, transientSources, excludeMaskPlanes)
+            goodSrcFlags = checkMask(difference.mask, transientSources, excludeMaskPlanes)
             if setFlags:
                 self.assertEqual(np.sum(~goodSrcFlags), nBad)
                 self.assertFalse(hasattr(output, "diaSources"))
@@ -965,7 +964,7 @@ def _detection_wrapper(setFlags=True):
             score = subtractTask._convolveExposure(difference, scienceKernel, subtractTask.convolutionControl)
             output = detectionTask.run(science, matchedTemplate, difference, score)
             refIds = []
-            goodSrcFlags = subtractTask._checkMask(difference.mask, transientSources, excludeMaskPlanes)
+            goodSrcFlags = checkMask(difference.mask, transientSources, excludeMaskPlanes)
             if setFlags:
                 self.assertEqual(np.sum(~goodSrcFlags), nBad)
                 self.assertFalse(hasattr(output, "diaSources"))

tests/utils.py

@@ -1219,3 +1219,44 @@ def generate_data_id(*,
 
     data_id = DataCoordinate.standardize(record_id, universe=universe)
     return data_id.expanded(record)
+
+
+def checkMask(mask, sources, excludeMaskPlanes, checkAdjacent=True):
+    """Exclude sources that are located on or adjacent to masked pixels.
+
+    Parameters
+    ----------
+    mask : `lsst.afw.image.Mask`
+        The image mask plane to use to reject sources
+        based on the location of their centroid on the ccd.
+    sources : `lsst.afw.table.SourceCatalog`
+        The source catalog to evaluate.
+    excludeMaskPlanes : `list` of `str`
+        List of the names of the mask planes to exclude.
+
+    Returns
+    -------
+    flags : `numpy.ndarray` of `bool`
+        Array indicating whether each source in the catalog should be
+        kept (True) or rejected (False) based on the value of the
+        mask plane at its location.
+    """
+    setExcludeMaskPlanes = [
+        maskPlane for maskPlane in excludeMaskPlanes if maskPlane in mask.getMaskPlaneDict()
+    ]
+
+    excludePixelMask = mask.getPlaneBitMask(setExcludeMaskPlanes)
+
+    xv = (np.rint(sources.getX() - mask.getX0())).astype(int)
+    yv = (np.rint(sources.getY() - mask.getY0())).astype(int)
+
+    flags = np.ones(len(sources), dtype=bool)
+    if checkAdjacent:
+        pixRange = (0, -1, 1)
+    else:
+        pixRange = (0,)
+    for j in pixRange:
+        for i in pixRange:
+            mv = mask.array[yv + j, xv + i]
+            flags *= np.bitwise_and(mv, excludePixelMask) == 0
+    return flags