Support partial outputs for detection on the preconvolved diffim

Author: isullivan

python/lsst/ip/diffim/detectAndMeasure.py

@@ -1368,7 +1368,7 @@ class DetectAndMeasureScoreTask(DetectAndMeasureTask):
 
     @timeMethod
     def run(self, science, matchedTemplate, difference, scoreExposure, kernelSources,
-            idFactory=None):
+            idFactory=None, measurementResults=None):
         """Detect and measure sources on a score image.
 
         Parameters
@@ -1388,6 +1388,10 @@ def run(self, science, matchedTemplate, difference, scoreExposure, kernelSources
             Generator object used to assign ids to detected sources in the
             difference image. Ids from this generator are not set until after
             deblending and merging positive/negative peaks.
+        measurementResults : `lsst.pipe.base.Struct`, optional
+            Result struct that is modified to allow saving of partial outputs
+            for some failure conditions. If the task completes successfully,
+            this is also returned.
 
         Returns
         -------
@@ -1398,6 +1402,8 @@ def run(self, science, matchedTemplate, difference, scoreExposure, kernelSources
             ``diaSources``  : `lsst.afw.table.SourceCatalog`
                 The catalog of detected sources.
         """
+        if measurementResults is None:
+            measurementResults = pipeBase.Struct()
         if idFactory is None:
             idFactory = lsst.meas.base.IdGenerator().make_table_id_factory()
 
@@ -1420,17 +1426,20 @@ def run(self, science, matchedTemplate, difference, scoreExposure, kernelSources
                                                           results.positive,
                                                           results.negative)
 
-            return self.processResults(science, matchedTemplate, difference,
-                                       sources, idFactory, kernelSources,
-                                       positives=positives,
-                                       negatives=negatives)
+            self.processResults(science, matchedTemplate, difference,
+                                sources, idFactory, kernelSources,
+                                positives=positives,
+                                negatives=negatives,
+                                measurementResults=measurementResults)
 
         else:
             positives = afwTable.SourceCatalog(self.schema)
             results.positive.makeSources(positives)
             negatives = afwTable.SourceCatalog(self.schema)
             results.negative.makeSources(negatives)
-            return self.processResults(science, matchedTemplate, difference,
-                                       results.sources, idFactory, kernelSources,
-                                       positives=positives,
-                                       negatives=negatives)
+            self.processResults(science, matchedTemplate, difference,
+                                results.sources, idFactory, kernelSources,
+                                positives=positives,
+                                negatives=negatives,
+                                measurementResults=measurementResults)
+        return measurementResults