def run(display=False):
#
# Create the tasks
#
charImageConfig = CharacterizeImageTask.ConfigClass()
charImageTask = CharacterizeImageTask(config=charImageConfig)
config = CalibrateTask.ConfigClass()
config.astrometry.retarget(MyAstrometryTask)
calibrateTask = CalibrateTask(config=config)
# load the data
# Exposure ID and the number of bits required for exposure IDs are usually obtained from a data repo,
# but here we pick reasonable values (there are 64 bits to share between exposure IDs and source IDs).
exposure = loadData()
exposureIdInfo = ExposureIdInfo(expId=1, expBits=5)
# characterize the exposure to repair cosmic rays and fit a PSF model
# display now because CalibrateTask modifies the exposure in place
charRes = charImageTask.characterize(exposure=exposure,
exposureIdInfo=exposureIdInfo)
if display:
displayFunc(charRes.exposure, charRes.sourceCat, frame=1)
# calibrate the exposure
calRes = calibrateTask.calibrate(exposure=charRes.exposure,
exposureIdInfo=exposureIdInfo)
if display:
displayFunc(calRes.exposure, calRes.sourceCat, frame=2)
def run(self,
ccdExposure,
*,
camera=None,
bias=None,
dark=None,
flat=None,
defects=None,
linearizer=None,
crosstalk=None,
bfKernel=None,
bfGains=None,
ptc=None,
crosstalkSources=None,
isrBaseConfig=None):
"""Run isr and cosmic ray repair using, doing as much isr as possible.
Retrieves as many calibration products as are available, and runs isr
with those settings enabled, but always returns an assembled image at
a minimum. Then performs cosmic ray repair if configured to.
Parameters
----------
ccdExposure : `lsst.afw.image.Exposure`
The raw exposure that is to be run through ISR. The
exposure is modified by this method.
camera : `lsst.afw.cameraGeom.Camera`, optional
The camera geometry for this exposure. Required if
one or more of ``ccdExposure``, ``bias``, ``dark``, or
``flat`` does not have an associated detector.
bias : `lsst.afw.image.Exposure`, optional
Bias calibration frame.
linearizer : `lsst.ip.isr.linearize.LinearizeBase`, optional
Functor for linearization.
crosstalk : `lsst.ip.isr.crosstalk.CrosstalkCalib`, optional
Calibration for crosstalk.
crosstalkSources : `list`, optional
List of possible crosstalk sources.
dark : `lsst.afw.image.Exposure`, optional
Dark calibration frame.
flat : `lsst.afw.image.Exposure`, optional
Flat calibration frame.
ptc : `lsst.ip.isr.PhotonTransferCurveDataset`, optional
Photon transfer curve dataset, with, e.g., gains
and read noise.
bfKernel : `numpy.ndarray`, optional
Brighter-fatter kernel.
bfGains : `dict` of `float`, optional
Gains used to override the detector's nominal gains for the
brighter-fatter correction. A dict keyed by amplifier name for
the detector in question.
defects : `lsst.ip.isr.Defects`, optional
List of defects.
fringes : `lsst.pipe.base.Struct`, optional
Struct containing the fringe correction data, with
elements:
- ``fringes``: fringe calibration frame (`afw.image.Exposure`)
- ``seed``: random seed derived from the ccdExposureId for random
number generator (`uint32`)
opticsTransmission: `lsst.afw.image.TransmissionCurve`, optional
A ``TransmissionCurve`` that represents the throughput of the,
optics, to be evaluated in focal-plane coordinates.
filterTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the
filter itself, to be evaluated in focal-plane coordinates.
sensorTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the
sensor itself, to be evaluated in post-assembly trimmed detector
coordinates.
atmosphereTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the
atmosphere, assumed to be spatially constant.
detectorNum : `int`, optional
The integer number for the detector to process.
strayLightData : `object`, optional
Opaque object containing calibration information for stray-light
correction. If `None`, no correction will be performed.
illumMaskedImage : `lsst.afw.image.MaskedImage`, optional
Illumination correction image.
isrBaseConfig : `lsst.ip.isr.IsrTaskConfig`, optional
An isrTask config to act as the base configuration. Options which
involve applying a calibration product are ignored, but this allows
for the configuration of e.g. the number of overscan columns.
Returns
-------
result : `lsst.pipe.base.Struct`
Result struct with component:
- ``exposure`` : `afw.image.Exposure`
The ISRed and cosmic-ray-repaired exposure.
"""
isrConfig = isrBaseConfig if isrBaseConfig else IsrTask.ConfigClass()
isrConfig.doBias = False
isrConfig.doDark = False
isrConfig.doFlat = False
isrConfig.doFringe = False
isrConfig.doDefect = False
isrConfig.doLinearize = False
isrConfig.doCrosstalk = False
isrConfig.doBrighterFatter = False
isrConfig.usePtcGains = False
if bias:
isrConfig.doBias = True
self.log.info("Running with bias correction")
if dark:
isrConfig.doDark = True
self.log.info("Running with dark correction")
if flat:
isrConfig.doFlat = True
self.log.info("Running with flat correction")
# TODO: deal with fringes here
if defects:
isrConfig.doDefect = True
self.log.info("Running with defect correction")
if linearizer:
isrConfig.doLinearize = True
self.log.info("Running with linearity correction")
if crosstalk:
isrConfig.doCrosstalk = True
self.log.info("Running with crosstalk correction")
if bfKernel:
isrConfig.doBrighterFatter = True
self.log.info("Running with brighter-fatter correction")
if ptc:
isrConfig.usePtcGains = True
self.log.info("Running with ptc correction")
isrConfig.doWrite = False
isrTask = IsrTask(config=isrConfig)
result = isrTask.run(
ccdExposure,
camera=camera,
bias=bias,
dark=dark,
flat=flat,
# fringes=pipeBase.Struct(fringes=None),
defects=defects,
linearizer=linearizer,
crosstalk=crosstalk,
bfKernel=bfKernel,
bfGains=bfGains,
ptc=ptc,
crosstalkSources=crosstalkSources,
isGen3=True,
)
postIsr = result.exposure
if self.config.doRepairCosmics:
try: # can fail due to too many CRs detected, and we always want an exposure back
self.log.info("Repairing cosmics...")
if postIsr.getPsf() is None:
installPsfTask = InstallGaussianPsfTask()
installPsfTask.run(postIsr)
# TODO: try adding a reasonably wide Gaussian as a temp PSF
# and then just running repairTask on its own without any
# imChar. It should work, and be faster.
repairConfig = CharacterizeImageTask.ConfigClass()
repairConfig.doMeasurePsf = False
repairConfig.doApCorr = False
repairConfig.doDeblend = False
repairConfig.doWrite = False
repairConfig.repair.cosmicray.nCrPixelMax = 200000
repairTask = CharacterizeImageTask(config=repairConfig)
repairTask.repair.run(postIsr)
except Exception as e:
self.log.warning(f"During CR repair caught: {e}")
# exposure is returned for convenience to mimic isrTask's API.
return pipeBase.Struct(exposure=postIsr, outputExposure=postIsr)
