Add PTC to linearity and BFK header provenance

python/lsst/cp/pipe/linearity.py

@@ -31,7 +31,8 @@
 from lsstDebug import getDebugFrame
 from lsst.ip.isr import (Linearizer, IsrProvenance)
 
-from .utils import funcPolynomial, irlsFit, AstierSplineLinearityFitter
+from .utils import (funcPolynomial, irlsFit, AstierSplineLinearityFitter,
+                    extractCalibDate)
 
 
 def ptcLookup(datasetType, registry, quantumDataId, collections):
@@ -265,7 +266,28 @@ def runQuantum(self, butlerQC, inputRefs, outputRefs):
         # Use the dimensions to set calib/provenance information.
         inputs['inputDims'] = dict(inputRefs.inputPtc.dataId.required)
 
+        # Add calibration provenance info to header.
+        kwargs = dict()
+        reference = getattr(inputRefs, "inputPtc", None)
+
+        if reference is not None and hasattr(reference, "run"):
+            runKey = "PTC_RUN"
+            runValue = reference.run
+            idKey = "PTC_UUID"
+            idValue = str(reference.id)
+            dateKey = "PTC_DATE"
+            calib = inputs.get("inputPtc", None)
+            dateValue = extractCalibDate(calib)
+
+            kwargs[runKey] = runValue
+            kwargs[idKey] = idValue
+            kwargs[dateKey] = dateValue
+
+            self.log.info("Using " + str(reference.run))
+
         outputs = self.run(**inputs)
+        outputs.outputLinearizer.updateMetadata(setDate=False, **kwargs)
+
         butlerQC.put(outputs, outputRefs)
 
     def run(self, inputPtc, dummy, camera, inputDims,

python/lsst/cp/pipe/makeBrighterFatterKernel.py

@@ -32,7 +32,7 @@
 import lsst.pipe.base.connectionTypes as cT
 
 from lsst.ip.isr import (BrighterFatterKernel)
-from .utils import (funcPolynomial, irlsFit)
+from .utils import (funcPolynomial, irlsFit, extractCalibDate)
 
 
 class BrighterFatterKernelSolveConnections(pipeBase.PipelineTaskConnections,
@@ -175,7 +175,28 @@ def runQuantum(self, butlerQC, inputRefs, outputRefs):
         # Use the dimensions to set calib/provenance information.
         inputs['inputDims'] = dict(inputRefs.inputPtc.dataId.required)
 
+        # Add calibration provenance info to header.
+        kwargs = dict()
+        reference = getattr(inputRefs, "inputPtc", None)
+
+        if reference is not None and hasattr(reference, "run"):
+            runKey = "PTC_RUN"
+            runValue = reference.run
+            idKey = "PTC_UUID"
+            idValue = str(reference.id)
+            dateKey = "PTC_DATE"
+            calib = inputs.get("inputPtc", None)
+            dateValue = extractCalibDate(calib)
+
+            kwargs[runKey] = runValue
+            kwargs[idKey] = idValue
+            kwargs[dateKey] = dateValue
+
+            self.log.info("Using " + str(reference.run))
+
         outputs = self.run(**inputs)
+        outputs.outputBFK.updateMetadata(setDate=False, **kwargs)
+
         butlerQC.put(outputs, outputRefs)
 
     def run(self, inputPtc, dummy, camera, inputDims):

python/lsst/cp/pipe/utils.py

@@ -573,6 +573,31 @@ def arrangeFlatsByExpId(exposureList, exposureIdList):
     return flatsAtExpId
 
 
+def extractCalibDate(calib):
+    """Extract common calibration metadata values that will be written to
+    output header.
+
+    Parameters
+    ----------
+    calib : `lsst.afw.image.Exposure` or `lsst.ip.isr.IsrCalib`
+        Calibration to pull date information from.
+
+    Returns
+    -------
+    dateString : `str`
+        Calibration creation date string to add to header.
+    """
+    if hasattr(calib, "getMetadata"):
+        if 'CALIB_CREATION_DATE' in calib.getMetadata():
+            return " ".join((calib.getMetadata().get("CALIB_CREATION_DATE", "Unknown"),
+                             calib.getMetadata().get("CALIB_CREATION_TIME", "Unknown")))
+        else:
+            return " ".join((calib.getMetadata().get("CALIB_CREATE_DATE", "Unknown"),
+                             calib.getMetadata().get("CALIB_CREATE_TIME", "Unknown")))
+    else:
+        return "Unknown Unknown"
+
+
 class CovFastFourierTransform:
     """A class to compute (via FFT) the nearby pixels correlation function.