Merge pull request #275 from lsst/tickets/DM-44246

DM-44246: Add functionality to use an external footprint set for NoiseReplacer in SingleFrameMeasurementTask.

python/lsst/meas/base/baseMeasurement.py

@@ -485,3 +485,21 @@ def doMeasurementN(self, plugin, measCat, *args, **kwds):
                 self.log.getChild(plugin.name).warning(
                     "Exception in %s.measureN on records %s-%s: %s",
                     plugin.name, measCat[0].getId(), measCat[-1].getId(), error)
+
+    @staticmethod
+    def getFootprintsFromCatalog(catalog):
+        """Get a set of footprints from a catalog, keyed by id.
+
+        Parameters
+        ----------
+        catalog : `lsst.afw.table.SourceCatalog`
+            Catalog with `lsst.afw.detection.Footprint`s attached.
+
+        Returns
+        -------
+        footprints : `dict` [`int`: (`int`, `lsst.afw.detection.Footprint`)]
+            Dictionary of footprint, keyed by id number, with a tuple of
+            the parent id and footprint.
+        """
+        return {measRecord.getId(): (measRecord.getParent(), measRecord.getFootprint())
+                for measRecord in catalog}

python/lsst/meas/base/sfm.py

@@ -206,7 +206,16 @@ def __init__(self, schema, algMetadata=None, **kwds):
             self.doBlendedness = False
 
     @timeMethod
-    def run(self, measCat, exposure, noiseImage=None, exposureId=None, beginOrder=None, endOrder=None):
+    def run(
+        self,
+        measCat,
+        exposure,
+        noiseImage=None,
+        exposureId=None,
+        beginOrder=None,
+        endOrder=None,
+        footprints=None,
+    ):
         r"""Run single frame measurement over an exposure and source catalog.
 
         Parameters
@@ -233,10 +242,13 @@ def run(self, measCat, exposure, noiseImage=None, exposureId=None, beginOrder=No
             Final execution order (exclusive): measurements with
             ``executionOrder >= endOrder`` are not executed. `None` for no
             limit.
+        footprints : `dict` {`int`: `lsst.afw.detection.Footprint`}, optional
+            List of footprints to use for noise replacement. If this is not
+            supplied then the footprints from the measCat are used.
         """
         assert measCat.getSchema().contains(self.schema)
-        footprints = {measRecord.getId(): (measRecord.getParent(), measRecord.getFootprint())
-                      for measRecord in measCat}
+        if footprints is None:
+            footprints = self.getFootprintsFromCatalog(measCat)
 
         # noiseReplacer is used to fill the footprints with noise and save
         # heavy footprints of the source pixels so that they can be restored

tests/test_NoiseReplacer.py

@@ -104,6 +104,29 @@ def testNoiseReplacer(self, noiseSource, variance):
             # fail (indeed, 67% should)
             self.assertLess(record.get("test_NoiseReplacer_outside"), np.sqrt(sumVariance))
 
+    @methodParameters(noiseSource=['measure', 'variance', 'meta', 'variance_median'],
+                      variance=[1.0, 1.0, 2.0, 1.0])
+    def testNoiseReplacerExternalFootprints(self, noiseSource, variance):
+        # We choose a random seed which causes the test to pass.
+        task = self.makeSingleFrameMeasurementTask("test_NoiseReplacer")
+        task.config.noiseReplacer.noiseSource = noiseSource
+        exposure, catalog = self.dataset.realize(variance, task.schema, randomSeed=0)
+        if noiseSource == 'meta':
+            md = PropertyList()
+            md['BGMEAN'] = variance
+            exposure.setMetadata(md)
+        footprints = task.getFootprintsFromCatalog(catalog)
+        task.run(catalog, exposure, footprints=footprints)
+        sumVariance = exposure.variance.array.sum()
+        for record in catalog:
+            self.assertFloatsAlmostEqual(record.get("test_NoiseReplacer_inside"),
+                                         record.get("truth_instFlux"), rtol=1E-3)
+
+            # N.B. Next line checks that a random value is correct to a
+            # statistical 1-sigma prediction; some RNG seeds may cause it to
+            # fail (indeed, 67% should)
+            self.assertLess(record.get("test_NoiseReplacer_outside"), np.sqrt(sumVariance))
+
     def tearDown(self):
         del self.bbox
         del self.dataset