IsrTaskLSST

class lsst.ip.isr.IsrTaskLSST(**kwargs)

Bases: PipelineTask

Methods Summary

addVariancePlane(exposure, detector)	Add the variance plane to the image.
applyBrighterFatterCorrection(ccdExposure, ...)	Apply a brighter fatter correction to the image using the method defined in Coulton et al. 2019.
applyElectrostaticBrighterFatterCorrection(...)	Apply an electrostatic brighter fatter correction to the image using the method defined in Astier et al. 2023.
applyFluxConservingBrighterFatterCorrection(...)	Apply a brighter fatter correction to the image using the method defined in Coulton et al. 2019 with flux-conserving corrections.
checkAllBadAmps(badAmpDict, detector)	Check if all amps are marked as bad.
checkAmpNoise(badAmpDict, exposure, ptc)	Check if amplifier noise levels are above threshold.
checkAmpOverscanLevel(badAmpDict, exposure, ptc)	Check if the amplifier overscan levels have changed.
checkBssVoltage(exposure)	Check the back-side bias voltage to see if the detector is on.
compareUnits(calibMetadata, calibName)	Compare units from calibration to ISR units.
convertIntToFloat(exposure)	Convert exposure image from uint16 to float.
darkCorrection(exposure, darkExposure[, invert])	Apply dark correction in place.
diffNonLinearCorrection(ccdExposure, dnlLUT, ...)
ditherCounts(exposure, detectorConfig[, ...])	Dither the counts in the exposure.
extractCalibDate(calib)	Extract common calibration metadata values that will be written to output header.
flatContext(exp, flat[, dark])	Context manager that applies and removes flats and darks, if the task is configured to apply them.
getBrighterFatterKernel(detector, bfKernel)
makeBinnedImages(exposure)	Make visualizeVisit style binned exposures.
maskDefects(exposure, defectBaseList)	Mask defects using mask plane "BAD", in place.
maskEdges(exposure[, numEdgePixels, ...])	Mask edge pixels with applicable mask plane.
maskFullAmplifiers(ccdExposure, detector, ...)	Check for fully masked bad amplifiers and mask them.
maskITLSatEdgesAndColumns(exposure, badAmpDict)
maskNan(exposure)	Mask NaNs using mask plane "UNMASKEDNAN", in place.
maskNegativeVariance(exposure)	Identify and mask pixels with negative variance values.
maskSaturatedPixels(badAmpDict, ccdExposure, ...)	Mask SATURATED and SUSPECT pixels and check if any amplifiers are fully masked.
overscanCorrection(mode, detectorConfig, ...)	Apply serial overscan correction in place to all amps.
run(ccdExposure, *[, dnlLUT, bias, ...])	Run the IsrTaskLSST task.
runQuantum(butlerQC, inputRefs, outputRefs)	Do butler IO and transform to provide in memory objects for tasks run method.
setBadRegions(exposure)	Set bad regions from large contiguous regions.
validateInput(inputs)	This is a check that all the inputs required by the config are available.

Methods Documentation

addVariancePlane(exposure, detector)

Add the variance plane to the image.

The gain and read noise per amp must have been set in the exposure metadata as LSST ISR GAIN ampName and LSST ISR READNOISE ampName with the units of the image. Unit conversions for the variance plane will be done as necessary based on the exposure units.

The units of the variance plane will always be of the same type as the units of the input image itself (``LSST ISR UNITS``^2).

Parameters

exposurelsst.afw.image.Exposure

The exposure to add the variance plane.

detectorlsst.afw.cameraGeom.Detector

Detector with geometry info.

applyBrighterFatterCorrection(ccdExposure, flat, dark, bfKernel, brighterFatterApplyGain, bfGains)

Apply a brighter fatter correction to the image using the method defined in Coulton et al. 2019.

Note that this correction requires that the image is in units electrons.

Parameters

ccdExposurelsst.afw.image.Exposure

Exposure to process.

flatlsst.afw.image.Exposure

Flat exposure the same size as exp.

darklsst.afw.image.Exposure, optional

Dark exposure the same size as exp.

bfKernellsst.ip.isr.BrighterFatterKernel

The brighter-fatter kernel.

brighterFatterApplyGainbool

Apply the gain to convert the image to electrons?

bfGainsdict

The gains to use if brighterFatterApplyGain = True.

Yields

explsst.afw.image.Exposure

The flat and dark corrected exposure.

applyElectrostaticBrighterFatterCorrection(ccdExposure, flat, dark, electroBfDistortionMatrix, brighterFatterApplyGain, bfGains)

Apply an electrostatic brighter fatter correction to the image using the method defined in Astier et al. 2023.

Note that this correction requires that the image is in units electrons.

Parameters

ccdExposurelsst.afw.image.Exposure

Exposure to process.

flatlsst.afw.image.Exposure

Flat exposure the same size as exp.

darklsst.afw.image.Exposure, optional

Dark exposure the same size as exp.

electroBfDistortionMatrixlsst.ip.isr.ElectrostaticBrighterFatter

The brighter-fatter kernel.

brighterFatterApplyGainbool

Apply the gain to convert the image to electrons?

bfGainsdict

The gains to use if brighterFatterApplyGain = True.

Yields

explsst.afw.image.Exposure

The flat and dark corrected exposure.

applyFluxConservingBrighterFatterCorrection(ccdExposure, flat, dark, bfKernel, brighterFatterApplyGain, bfGains)

Apply a brighter fatter correction to the image using the method defined in Coulton et al. 2019 with flux-conserving corrections.

Note that this correction requires that the image is in units electrons.

Parameters

ccdExposurelsst.afw.image.Exposure

Exposure to process.

flatlsst.afw.image.Exposure

Flat exposure the same size as exp.

darklsst.afw.image.Exposure, optional

Dark exposure the same size as exp.

bfKernellsst.ip.isr.BrighterFatterKernel

The brighter-fatter kernel.

brighterFatterApplyGainbool

Apply the gain to convert the image to electrons?

bfGainsdict

The gains to use if brighterFatterApplyGain = True.

Yields

explsst.afw.image.Exposure

The flat and dark corrected exposure.

checkAllBadAmps(badAmpDict, detector)

Check if all amps are marked as bad.

Parameters

badAmpDictstr`[`bool]

Dictionary of amplifiers, keyed by name, value is True if amplifier is fully masked.

detectorlsst.afw.cameraGeom.Detector

Detector object.

Raises

UnprocessableDataError if all amps are bad and doCheckUnprocessableData configuration is True.

checkAmpNoise(badAmpDict, exposure, ptc)

Check if amplifier noise levels are above threshold.

Any amplifier that is above the noise level will be masked as BAD and added to the badAmpDict.

Parameters

badAmpDictstr [bool]

Dictionary of amplifiers, keyed by name, value is True if amplifier is fully masked.

exposurelsst.afw.image.Exposure

Input exposure to be masked (untrimmed).

ptclsst.ip.isr.PhotonTransferCurveDataset

PTC dataset with gains/read noises.

Returns

badAmpDictstr`[`bool]

Dictionary of amplifiers, keyed by name.

checkAmpOverscanLevel(badAmpDict, exposure, ptc)

Check if the amplifier overscan levels have changed.

Any amplifier that has an overscan median level that has changed significantly will be masked as BAD and added to toe badAmpDict.

Parameters

badAmpDictstr [bool]

Dictionary of amplifiers, keyed by name, value is True if amplifier is fully masked.

exposurelsst.afw.image.Exposure

Input exposure to be masked (untrimmed).

ptclsst.ip.isr.PhotonTransferCurveDataset

PTC dataset with gains/read noises.

Returns

badAmpDictstr`[`bool]

Dictionary of amplifiers, keyed by name.

checkBssVoltage(exposure)

Check the back-side bias voltage to see if the detector is on.

Parameters

exposurelsst.afw.image.ExposureF

Input exposure.

Raises

UnprocessableDataError if voltage is off.

compareUnits(calibMetadata, calibName)

Compare units from calibration to ISR units.

This compares calibration units (adu or electron) to whether doApplyGain is set.

Parameters

calibMetadatalsst.daf.base.PropertyList

Calibration metadata from header.

calibNamestr

Calibration name for log message.

convertIntToFloat(exposure)

Convert exposure image from uint16 to float.

If the exposure does not need to be converted, the input is immediately returned. For exposures that are converted to use floating point pixels, the variance is set to unity and the mask to zero.

Parameters

exposurelsst.afw.image.Exposure

The raw exposure to be converted.

Returns

newexposurelsst.afw.image.Exposure

The input exposure, converted to floating point pixels.

Raises

RuntimeError

Raised if the exposure type cannot be converted to float.

darkCorrection(exposure, darkExposure, invert=False)

Apply dark correction in place.

Parameters

exposurelsst.afw.image.Exposure

Exposure to process.

darkExposurelsst.afw.image.Exposure

Dark exposure of the same size as exposure.

invertBool, optional

If True, re-add the dark to an already corrected image.

Raises

RuntimeError

Raised if either exposure or darkExposure do not have their dark time defined.

See Also

lsst.ip.isr.isrFunctions.darkCorrection

diffNonLinearCorrection(ccdExposure, dnlLUT, **kwargs)

ditherCounts(exposure, detectorConfig, fallbackSeed=12345)

Dither the counts in the exposure.

Parameters

exposurelsst.afw.image.Exposure

The raw exposure to be dithered.

detectorConfiglsst.ip.isr.OverscanDetectorConfig

Configuration for overscan/etc for this detector.

fallbackSeedint, optional

Random seed to fall back to if exposure.getInfo().getId() is not set.

static extractCalibDate(calib)

Extract common calibration metadata values that will be written to output header.

Parameters

caliblsst.afw.image.Exposure or lsst.ip.isr.IsrCalib

Calibration to pull date information from.

Returns

dateStringstr

Calibration creation date string to add to header.

flatContext(exp, flat, dark=None)

Context manager that applies and removes flats and darks, if the task is configured to apply them.

Parameters

explsst.afw.image.Exposure

Exposure to process.

flatlsst.afw.image.Exposure

Flat exposure the same size as exp.

darklsst.afw.image.Exposure, optional

Dark exposure the same size as exp.

Yields

explsst.afw.image.Exposure

The flat and dark corrected exposure.

getBrighterFatterKernel(detector, bfKernel)

makeBinnedImages(exposure)

Make visualizeVisit style binned exposures.

Parameters

exposurelsst.afw.image.Exposure

Exposure to bin.

Returns

bin1lsst.afw.image.Exposure

Binned exposure using binFactor1.

bin2lsst.afw.image.Exposure

Binned exposure using binFactor2.

Deprecated since version v28: makeBinnedImages is no longer used. Please subtask lsst.ip.isr.BinImageDataTask instead.

maskDefects(exposure, defectBaseList)

Mask defects using mask plane “BAD”, in place.

Parameters

exposurelsst.afw.image.Exposure

Exposure to process.

defectBaseListdefect-type

List of defects to mask. Can be of type lsst.ip.isr.Defects or list of lsst.afw.image.DefectBase.

maskEdges(exposure, numEdgePixels=0, maskPlane='SUSPECT', level='DETECTOR')

Mask edge pixels with applicable mask plane.

Parameters

exposurelsst.afw.image.Exposure

Exposure to process.

numEdgePixelsint, optional

Number of edge pixels to mask.

maskPlanestr, optional

Mask plane name to use.

levelstr, optional

Level at which to mask edges.

maskFullAmplifiers(ccdExposure, detector, defects, gains=None)

Check for fully masked bad amplifiers and mask them.

This includes defects which cover full amplifiers, as well as amplifiers with nan gain values which should be used if self.config.doApplyGains=True.

Full defect masking happens later to allow for defects which cross amplifier boundaries.

Parameters

ccdExposurelsst.afw.image.Exposure

Input exposure to be masked.

detectorlsst.afw.cameraGeom.Detector

Detector object.

defectslsst.ip.isr.Defects

List of defects. Used to determine if an entire amplifier is bad.

gainsdict [str, float], optional

Dictionary of gains to check if self.config.doApplyGains=True.

Returns

badAmpDictstr`[`bool]

Dictionary of amplifiers, keyed by name, value is True if amplifier is fully masked.

maskITLSatEdgesAndColumns(exposure, badAmpDict)

maskNan(exposure)

Mask NaNs using mask plane “UNMASKEDNAN”, in place.

Parameters

exposurelsst.afw.image.Exposure

Exposure to process.

Notes

We mask over all non-finite values (NaN, inf), including those that are masked with other bits (because those may or may not be interpolated over later, and we want to remove all NaN/infs). Despite this behaviour, the “UNMASKEDNAN” mask plane is used to preserve the historical name.

maskNegativeVariance(exposure)

Identify and mask pixels with negative variance values.

Parameters

exposurelsst.afw.image.Exposure

Exposure to process.

See Also

lsst.ip.isr.isrFunctions.updateVariance

maskSaturatedPixels(badAmpDict, ccdExposure, detector, detectorConfig, ptc=None)

Mask SATURATED and SUSPECT pixels and check if any amplifiers are fully masked.

Parameters

badAmpDictstr [bool]

Dictionary of amplifiers, keyed by name, value is True if amplifier is fully masked.

ccdExposurelsst.afw.image.Exposure

Input exposure to be masked.

detectorlsst.afw.cameraGeom.Detector

Detector object.

defectslsst.ip.isr.Defects

List of defects. Used to determine if an entire amplifier is bad.

detectorConfiglsst.ip.isr.OverscanDetectorConfig

Per-amplifier configurations.

ptclsst.ip.isr.PhotonTransferCurveDataset, optional

PTC dataset (used if configured to use PTCTURNOFF).

Returns

badAmpDictstr`[`bool]

Dictionary of amplifiers, keyed by name.

overscanCorrection(mode, detectorConfig, detector, badAmpDict, ccdExposure)

Apply serial overscan correction in place to all amps.

The actual overscan subtraction is performed by the lsst.ip.isr.overscan.OverscanTask, which is called here.

Parameters

modestr

Must be SERIAL or PARALLEL.

detectorConfiglsst.ip.isr.OverscanDetectorConfig

Per-amplifier configurations.

detectorlsst.afw.cameraGeom.Detector

Detector object.

badAmpDictdict

Dictionary of amp name to whether it is a bad amp.

ccdExposurelsst.afw.image.Exposure

Exposure to have overscan correction performed.

Returns

overscanslist [lsst.pipe.base.Struct or None]

Overscan measurements (always in adu). Each result struct has components:

imageFit

Value or fit subtracted from the amplifier image data. (scalar or lsst.afw.image.Image)

overscanFit

Value or fit subtracted from the overscan image data. (scalar or lsst.afw.image.Image)

overscanImage

Image of the overscan region with the overscan correction applied. This quantity is used to estimate the amplifier read noise empirically. (lsst.afw.image.Image)

overscanMean

Mean overscan fit value. (float)

overscanMedian

Median overscan fit value. (float)

overscanSigma

Clipped standard deviation of the overscan fit. (float)

residualMean

Mean of the overscan after fit subtraction. (float)

residualMedian

Median of the overscan after fit subtraction. (float)

residualSigma

Clipped standard deviation of the overscan after fit subtraction. (float)

See Also

lsst.ip.isr.overscan.OverscanTask

run(ccdExposure, *, dnlLUT=None, bias=None, deferredChargeCalib=None, linearizer=None, ptc=None, gainCorrection=None, crosstalk=None, defects=None, bfKernel=None, electroBfDistortionMatrix=None, dark=None, flat=None, camera=None)

Run the IsrTaskLSST task.

Parameters

ccdExposurelsst.afw.image.Exposure

Exposure to run ISR.

dnlLUTNone, optional

DNL lookup table; placeholder, unused.

biaslsst.afw.image.Exposure, optional

Bias frame.

deferredChargeCaliblsst.ip.isr.DeferredChargeCalib, optional

Deferred charge calibration.

linearizerlsst.ip.isr.Linearizer, optional

Linearizer calibration.

ptclsst.ip.isr.PhotonTransferCurveDataset, optional

PTC dataset.

gainCorrectionlsst.ip.isr.GainCorrection, optional

Gain correction dataset.

crosstalklsst.ip.isr.CrosstalkCalib, optional

Crosstalk calibration dataset.

defectslsst.ip.isr.Defects, optional

Defects dataset.

bfKernellsst.ip.isr.BrighterFatterKernel, optional

Brighter-fatter kernel dataset.

darklsst.afw.image.Exposure, optional

Dark frame.

flatlsst.afw.image.Exposure, optional

Flat-field frame.

cameralsst.afw.cameraGeom.Camera, optional

Camera object.

Returns

resultlsst.pipe.base.Struct

Struct with fields:

exposure: lsst.afw.image.Exposure

Calibrated exposure.

outputBin1Exposure: lsst.afw.image.Exposure

Binned exposure (bin1 config).

outputBin2Exposure: lsst.afw.image.Exposure

Binned exposure (bin2 config).

outputExposure: lsst.afw.image.Exposure

Calibrated exposure (same as exposure).

outputStatistics: lsst.ip.isr.isrStatistics

Calibrated exposure statistics.

runQuantum(butlerQC, inputRefs, outputRefs)

Do butler IO and transform to provide in memory objects for tasks run method.

Parameters

butlerQCQuantumContext

A butler which is specialized to operate in the context of a lsst.daf.butler.Quantum.

inputRefsInputQuantizedConnection

Datastructure whose attribute names are the names that identify connections defined in corresponding PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined input/prerequisite connections.

outputRefsOutputQuantizedConnection

Datastructure whose attribute names are the names that identify connections defined in corresponding PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined output connections.

setBadRegions(exposure)

Set bad regions from large contiguous regions.

Parameters

exposurelsst.afw.Exposure

Exposure to set bad regions.

Notes

Reset and interpolate bad pixels.

Large contiguous bad regions (which should have the BAD mask bit set) should have their values set to the image median. This group should include defects and bad amplifiers. As the area covered by these defects are large, there’s little reason to expect that interpolation would provide a more useful value.

Smaller defects can be safely interpolated after the larger regions have had their pixel values reset. This ensures that the remaining defects adjacent to bad amplifiers (as an example) do not attempt to interpolate extreme values.

validateInput(inputs)

This is a check that all the inputs required by the config are available.