def loadAndMatch(self, exposure, sourceCat):
"""!Fake loading and matching
Copy the source catalog to a reference catalog and producing a match list
"""
wcs = exposure.getWcs()
refSchema = LoadReferenceObjectsTask.makeMinimalSchema(
filterNameList = [FilterName],
addIsPhotometric = True,
)
refCat = afwTable.SimpleCatalog(refSchema)
refFluxKey = refSchema[FilterName + "_flux"].asKey()
refIsPhotoKey = refSchema["photometric"].asKey()
matches = lsst.afw.table.ReferenceMatchVector()
for src in sourceCat:
flux = 1e-3*src.getPsfFlux()*np.random.normal(1.0, 2e-2)
refObj = refCat.addNew()
refObj.set(refFluxKey, flux)
refObj.setCoord(wcs.pixelToSky(src.getCentroid()))
refObj.set(refIsPhotoKey, True)
match = lsst.afw.table.ReferenceMatch(refObj, src, 0)
matches.append(match)
return pipeBase.Struct(
refCat = refCat,
matches = matches,
matchMeta = createMatchMetadata(exposure),
)
def loadAndMatch(self, exposure, sourceCat):
"""!Fake loading and matching
Copy the source catalog to a reference catalog and producing a match list
"""
wcs = exposure.getWcs()
refSchema = LoadReferenceObjectsTask.makeMinimalSchema(
filterNameList=[FilterName],
addIsPhotometric=True,
)
refCat = afwTable.SimpleCatalog(refSchema)
refFluxKey = refSchema[FilterName + "_flux"].asKey()
refIsPhotoKey = refSchema["photometric"].asKey()
matches = lsst.afw.table.ReferenceMatchVector()
for src in sourceCat:
flux = 1e-3 * src.getPsfFlux() * np.random.normal(1.0, 2e-2)
refObj = refCat.addNew()
refObj.set(refFluxKey, flux)
refObj.setCoord(wcs.pixelToSky(src.getCentroid()))
refObj.set(refIsPhotoKey, True)
match = lsst.afw.table.ReferenceMatch(refObj, src, 0)
matches.append(match)
return pipeBase.Struct(
refCat=refCat,
matches=matches,
matchMeta=createMatchMetadata(exposure),
)
def execute(self, dataRef):
"""!Characterize a science image
@param dataRef: butler data reference
@return a pipeBase Struct containing the results
"""
self.log.info("Performing Super Calibrate on sensor data ID %s" % (dataRef.dataId,))
self.log.info("Reading input data using dataRef")
inputData = self.read_input_data(dataRef)
self.log.info("Running operations. The run() method should not take anything Butler")
if self.config.doWrite and self.config.doAstrometry:
self.matchMeta = createMatchMetadata(inputData.getDict()['exposure'], border=self.pixelMargin)
else:
self.matchMeta = None
result = CalibrateTask.calibrate(CalibrateTask(config=self.config, log=self.log, icSourceSchema=self.icSourceSchema),
**inputData.getDict())
self.log.info("Writing output data using dataRef")
self.write_output_data(dataRef, result)
return result
def run(self, dataRef, exposure=None, background=None, icSourceCat=None, doUnpersist=True):
"""!Calibrate an exposure, optionally unpersisting inputs and persisting outputs.
This is a wrapper around the `calibrate` method that unpersists inputs
(if `doUnpersist` true) and persists outputs (if `config.doWrite` true)
@param[in] dataRef butler data reference corresponding to a science image
@param[in,out] exposure characterized exposure (an lsst.afw.image.ExposureF or similar),
or None to unpersist existing icExp and icBackground.
See calibrate method for details of what is read and written.
@param[in,out] background initial model of background already subtracted from exposure
(an lsst.afw.math.BackgroundList). May be None if no background has been subtracted,
though that is unusual for calibration.
A refined background model is output.
Ignored if exposure is None.
@param[in] icSourceCat catalog from which to copy the fields specified by icSourceKeys, or None;
@param[in] doUnpersist unpersist data:
- if True, exposure, background and icSourceCat are read from dataRef and those three arguments
must all be None;
- if False the exposure must be provided; background and icSourceCat are optional.
True is intended for running as a command-line task, False for running as a subtask
@warning until detectAndMeasure can determine suitable sources for measuring aperture correction
by itself, you must provide icSourceCat and a suitable entry in config.icSourceFieldsToCopy
@return same data as the calibrate method
"""
self.log.info("Processing %s" % (dataRef.dataId))
if doUnpersist:
if any(item is not None for item in (exposure, background, icSourceCat)):
raise RuntimeError("doUnpersist true; exposure, background and icSourceCat must all be None")
exposure = dataRef.get("icExp", immediate=True)
background = dataRef.get("icExpBackground", immediate=True)
icSourceCat = dataRef.get("icSrc", immediate=True)
elif exposure is None:
raise RuntimeError("doUnpersist false; exposure must be provided")
if self.config.doWrite and self.config.doAstrometry:
matchMeta = createMatchMetadata(exposure, border=self.pixelMargin)
else:
matchMeta = None
exposureIdInfo = dataRef.get("expIdInfo")
calRes = self.calibrate(
exposure = exposure,
exposureIdInfo = exposureIdInfo,
background = background,
icSourceCat = icSourceCat,
)
if self.config.doWrite:
self.writeOutputs(
dataRef = dataRef,
exposure = calRes.exposure,
background = calRes.background,
sourceCat = calRes.sourceCat,
astromMatches = calRes.astromMatches,
matchMeta = matchMeta,
)
return calRes
def run(self,
dataRef,
exposure=None,
background=None,
icSourceCat=None,
doUnpersist=True):
"""!Calibrate an exposure, optionally unpersisting inputs and
persisting outputs.
This is a wrapper around the `calibrate` method that unpersists inputs
(if `doUnpersist` true) and persists outputs (if `config.doWrite` true)
@param[in] dataRef butler data reference corresponding to a science
image
@param[in,out] exposure characterized exposure (an
lsst.afw.image.ExposureF or similar), or None to unpersist existing
icExp and icBackground. See calibrate method for details of what is
read and written.
@param[in,out] background initial model of background already
subtracted from exposure (an lsst.afw.math.BackgroundList). May be
None if no background has been subtracted, though that is unusual
for calibration. A refined background model is output. Ignored if
exposure is None.
@param[in] icSourceCat catalog from which to copy the fields specified
by icSourceKeys, or None;
@param[in] doUnpersist unpersist data:
- if True, exposure, background and icSourceCat are read from
dataRef and those three arguments must all be None;
- if False the exposure must be provided; background and
icSourceCat are optional. True is intended for running as a
command-line task, False for running as a subtask
@return same data as the calibrate method
"""
self.log.info("Processing %s" % (dataRef.dataId))
if doUnpersist:
if any(item is not None
for item in (exposure, background, icSourceCat)):
raise RuntimeError("doUnpersist true; exposure, background "
"and icSourceCat must all be None")
exposure = dataRef.get("icExp", immediate=True)
background = dataRef.get("icExpBackground", immediate=True)
icSourceCat = dataRef.get("icSrc", immediate=True)
elif exposure is None:
raise RuntimeError("doUnpersist false; exposure must be provided")
if self.config.doWrite and self.config.doAstrometry:
matchMeta = createMatchMetadata(exposure, border=self.pixelMargin)
else:
matchMeta = None
exposureIdInfo = dataRef.get("expIdInfo")
calRes = self.calibrate(
exposure=exposure,
exposureIdInfo=exposureIdInfo,
background=background,
icSourceCat=icSourceCat,
)
if self.config.doWrite:
self.writeOutputs(
dataRef=dataRef,
exposure=calRes.exposure,
background=calRes.background,
sourceCat=calRes.sourceCat,
astromMatches=calRes.astromMatches,
matchMeta=matchMeta,
)
return calRes