DcrAssembleCoaddConfig#

class lsst.drp.tasks.dcr_assemble_coadd.DcrAssembleCoaddConfig(*args, **kw)#

Bases: CompareWarpAssembleCoaddConfig

Attributes Summary

`accelerateModel`	Factor to amplify the differences between model planes by to speed convergence.
`assembleStaticSkyModel`	Task to assemble an artifact-free, PSF-matched Coadd to serve as a naive/first-iteration model of the static sky.
`badMaskPlanes`	Mask planes that, if set, the associated pixel should not be included in the coaddTempExp.
`bandwidth`	Bandwidth of the physical filter, in nm.Required if transmission curves aren't used.Support for using transmission curves is to be added in DM-13668.
`baseGain`	Relative weight to give the new solution vs.
`brightObjectMaskName`	Name of mask bit used for bright objects (`str`, default `'BRIGHT_OBJECT'`)
`calcErrorFromInputVariance`	Calculate coadd variance from input variance by stacking statistic.
`clipIter`	Number of iterations of outlier rejection; ignored if non-clipping statistic selected.
`coaddName`	Coadd name: typically one of deep or goodSeeing.
`coaddPsf`	Configuration for CoaddPsf (`CoaddPsfConfig`, default `<class 'lsst.meas.algorithms.CoaddPsfConfig'>`)
`connections`	Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.
`convergenceMaskPlanes`	Mask planes to use to calculate convergence.
`convergenceThreshold`	Target relative change in convergence between iterations of forward modeling.
`dcrNumSubfilters`	Number of sub-filters to forward model chromatic effects to fit the supplied exposures.
`detect`	Detect outlier sources on difference between each psfMatched warp and static sky model (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>`)
`detectPsfSources`	Task to detect sources for PSF measurement, if `doCalculatePsf` is set.
`detectTemplate`	Detect sources on static sky model.
`doAirmassWeight`	Weight exposures by airmass? Useful if there are relatively few high-airmass observations.
`doAttachTransmissionCurve`	Attach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves).
`doCalculatePsf`	Set to detect stars and recalculate the PSF from the final coadd.Otherwise the PSF is estimated from a selection of the best input exposures (`bool`, default `False`)
`doFilterMorphological`	Filter artifact candidates based on morphological criteria, i.g.
`doInputMap`	Create a bitwise map of coadd inputs (`bool`, default `False`)
`doInterp`	Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly.
`doMaskBrightObjects`	Set mask and flag bits for bright objects? (`bool`, default `False`)
`doNImage`	Create image of number of contributing exposures for each pixel (`bool`, default `False`)
`doOnlineForMean`	Perform online coaddition when statistic="MEAN" to save memory? (`bool`, default `False`)
`doPrefilterArtifacts`	Ignore artifact candidates that are mostly covered by the bad pixel mask, because they will be excluded anyway.
`doPreserveContainedBySource`	Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd.
`doScaleWarpVariance`	Rescale Warp variance plane using empirical noise? (`bool`, default `True`)
`doScaleZeroPoint`	Scale the photometric zero point of the coadd temp exposures such that the magnitude zero point results in a flux in nJy.
`doSelectVisits`	Coadd only visits selected by a SelectVisitsTask (`bool`, default `False`)
`doWrite`	Persist coadd? (`bool`, default `True`)
`doWriteArtifactMasks`	Persist artifact masks? Should be True for CompareWarp only.
`effectiveWavelength`	Effective wavelength of the filter, in nm.Required if transmission curves aren't used.Support for using transmission curves is to be added in DM-13668.
`growStreakFp`	Grow streak footprints by this number multiplied by the PSF width (`float`, default `5`)
`hasFakes`	Should be set to True if fake sources have been inserted into the input data.
`imageInterpOrder`	The order of the spline interpolation used to shift the image plane.
`includeCalibVar`	Add photometric calibration variance to warp variance plane.
`inputMapper`	Input map creation subtask.
`inputRecorder`	Subtask that helps fill CoaddInputs catalogs added to the final Exposure (`ConfigurableInstance`, default `<class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>`)
`interpImage`	Task to interpolate (and extrapolate) over NaN pixels (`ConfigurableInstance`, default `<class 'lsst.pipe.tasks.interpImage.InterpImageConfig'>`)
`maskPropagationThresholds`	Threshold (in fractional weight) of rejection at which we propagate a mask plane to the coadd; that is, we set the mask bit on the coadd if the fraction the rejected frames would have contributed exceeds this value.
`maskStreaks`	Detect streaks on difference between each psfMatched warp and static sky model.
`maxFractionEpochsHigh`	Fraction of local number of epochs (N) to use as effective maxNumEpochs for high N.
`maxFractionEpochsLow`	Fraction of local number of epochs (N) to use as effective maxNumEpochs for low N.
`maxNumEpochs`	Charactistic maximum local number of epochs/visits in which an artifact candidate can appear and still be masked.
`maxNumIter`	Maximum number of iterations of forward modeling.
`measurePsf`	Task to measure the PSF of the coadd, if `doCalculatePsf` is set.
`measurePsfSources`	Task to measure sources for PSF measurement, if `doCalculatePsf` is set.
`minNumIter`	Minimum number of iterations of forward modeling.
`modelWeightsWidth`	Width of the region around detected sources to include in the DcrModel.
`prefilterArtifactsMaskPlanes`	Prefilter artifact candidates that are mostly covered by these bad mask planes.
`prefilterArtifactsRatio`	Prefilter artifact candidates with less than this fraction overlapping good pixels (`float`, default `0.05`)
`regularizationWidth`	Minimum radius of a region to include in regularization, in pixels.
`regularizeModelFrequency`	Maximum relative change of the model allowed between subfilters.
`regularizeModelIterations`	Maximum relative change of the model allowed between iterations.
`removeMaskPlanes`	Mask planes to remove before coadding (`List`, default `['NOT_DEBLENDED']`)
`saveLogOutput`	Flag to enable/disable saving of log output for a task, enabled by default.
`scaleWarpVariance`	Rescale variance on warps (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.scaleVariance.ScaleVarianceConfig'>`)
`scaleZeroPoint`	Task to adjust the photometric zero point of the coadd temp exposures Deprecated: Now that visits are scaled to nJy it is no longer necessary or recommended to scale the zero point, so this will be removed after v29.
`select`	Image selection subtask.
`sigmaClip`	Sigma for outlier rejection; ignored if non-clipping statistic selected.
`spatialThreshold`	Unitless fraction of pixels defining how much of the outlier region has to meet the temporal criteria.
`splitSubfilters`	Calculate DCR for two evenly-spaced wavelengths in each subfilter.
`splitThreshold`	Minimum DCR difference within a subfilter to use `splitSubfilters`, in pixels.Set to 0 to always split the subfilters.
`statistic`	Main stacking statistic for aggregating over the epochs.
`streakMaskName`	Name of mask bit used for streaks (`str`, default `'STREAK'`)
`subregionSize`	Width, height of stack subregion size; make small enough that a full stack of images will fit into memory at once.
`useConvergence`	Use convergence test as a forward modeling end condition?If not set, skips calculating convergence and runs for `maxNumIter` iterations (`bool`, default `True`)
`useModelWeights`	Width of the region around detected sources to include in the DcrModel.
`useProgressiveGain`	Use a gain that slowly increases above `baseGain` to accelerate convergence? When calculating the next gain, we use up to 5 previous gains and convergence values.Can be set to False to force the model to change at the rate of `baseGain`.
`warpType`	Warp name: one of 'direct' or 'psfMatched' (`str`, default `'direct'`)

Methods Summary

setDefaults()

Subclass hook for computing defaults.

Attributes Documentation

accelerateModel#: Factor to amplify the differences between model planes by to speed convergence. (float, default 3)

assembleStaticSkyModel#: Task to assemble an artifact-free, PSF-matched Coadd to serve as a naive/first-iteration model of the static sky. (ConfigurableInstance, default <class 'lsst.drp.tasks.assemble_coadd.AssembleCoaddConfig'>)

badMaskPlanes#: Mask planes that, if set, the associated pixel should not be included in the coaddTempExp. (List, default ('NO_DATA',))

bandwidth#: Bandwidth of the physical filter, in nm.Required if transmission curves aren’t used.Support for using transmission curves is to be added in DM-13668. (float)

baseGain#: Relative weight to give the new solution vs. the last solution when updating the model.A value of 1.0 gives equal weight to both solutions.Small values imply slower convergence of the solution, but can help prevent overshooting and failures in the fit.If baseGain is None, a conservative gain will be calculated from the number of subfilters. (float, default None)

brightObjectMaskName#: Name of mask bit used for bright objects (str, default 'BRIGHT_OBJECT')

calcErrorFromInputVariance#: Calculate coadd variance from input variance by stacking statistic. Passed to StatisticsControl.setCalcErrorFromInputVariance() (bool, default True)

clipIter#: Number of iterations of outlier rejection; ignored if non-clipping statistic selected. (int, default 2)

coaddName#: Coadd name: typically one of deep or goodSeeing. (str, default 'deep')

coaddPsf#: Configuration for CoaddPsf (CoaddPsfConfig, default <class 'lsst.meas.algorithms.CoaddPsfConfig'>)

connections: pexConfig.ConfigField#: Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.

convergenceMaskPlanes#: Mask planes to use to calculate convergence. (List, default ['DETECTED'])

convergenceThreshold#: Target relative change in convergence between iterations of forward modeling. (float, default 0.001)

dcrNumSubfilters#: Number of sub-filters to forward model chromatic effects to fit the supplied exposures. (int, default 3)

detect#: Detect outlier sources on difference between each psfMatched warp and static sky model (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

detectPsfSources#: Task to detect sources for PSF measurement, if doCalculatePsf is set. (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

detectTemplate#: Detect sources on static sky model. Only used if doPreserveContainedBySource is True (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

doAirmassWeight#: Weight exposures by airmass? Useful if there are relatively few high-airmass observations. (bool, default False)

doAttachTransmissionCurve#: Attach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves). (bool, default False)

doCalculatePsf#: Set to detect stars and recalculate the PSF from the final coadd.Otherwise the PSF is estimated from a selection of the best input exposures (bool, default False)

doFilterMorphological#: Filter artifact candidates based on morphological criteria, i.g. those that appear to be streaks. (bool, default False)

doInputMap#: Create a bitwise map of coadd inputs (bool, default False)

doInterp#: Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly. (bool, default True)

doMaskBrightObjects#: Set mask and flag bits for bright objects? (bool, default False)

doNImage#: Create image of number of contributing exposures for each pixel (bool, default False)

doOnlineForMean#: Perform online coaddition when statistic=”MEAN” to save memory? (bool, default False)

doPrefilterArtifacts#: Ignore artifact candidates that are mostly covered by the bad pixel mask, because they will be excluded anyway. This prevents them from contributing to the outlier epoch count image and potentially being labeled as persistant.’Mostly’ is defined by the config ‘prefilterArtifactsRatio’. (bool, default True)

doPreserveContainedBySource#: Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd. Replicates a behavior of SafeClip. (bool, default True)

doScaleWarpVariance#: Rescale Warp variance plane using empirical noise? (bool, default True)

doScaleZeroPoint#: Scale the photometric zero point of the coadd temp exposures such that the magnitude zero point results in a flux in nJy. Deprecated: Now that visits are scaled to nJy it is no longer necessary or recommended to scale the zero point, so this will be removed after v29. (bool, default False)

doSelectVisits#: Coadd only visits selected by a SelectVisitsTask (bool, default False)

doWrite#: Persist coadd? (bool, default True)

doWriteArtifactMasks#: Persist artifact masks? Should be True for CompareWarp only. (bool, default False)

effectiveWavelength#: Effective wavelength of the filter, in nm.Required if transmission curves aren’t used.Support for using transmission curves is to be added in DM-13668. (float)

growStreakFp#: Grow streak footprints by this number multiplied by the PSF width (float, default 5)

hasFakes#: Should be set to True if fake sources have been inserted into the input data. (bool, default False)

imageInterpOrder#: The order of the spline interpolation used to shift the image plane. (int, default 1)

includeCalibVar#: Add photometric calibration variance to warp variance plane. Deprecated: Deprecated and ignored. Will be removed after v29. (bool, default False)

inputMapper#: Input map creation subtask. (ConfigurableInstance, default <class 'lsst.pipe.tasks.healSparseMapping.HealSparseInputMapConfig'>)

inputRecorder#: Subtask that helps fill CoaddInputs catalogs added to the final Exposure (ConfigurableInstance, default <class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)

interpImage#: Task to interpolate (and extrapolate) over NaN pixels (ConfigurableInstance, default <class 'lsst.pipe.tasks.interpImage.InterpImageConfig'>)

maskPropagationThresholds#: Threshold (in fractional weight) of rejection at which we propagate a mask plane to the coadd; that is, we set the mask bit on the coadd if the fraction the rejected frames would have contributed exceeds this value. (Dict, default {'SAT': 0.1})

maskStreaks#: Detect streaks on difference between each psfMatched warp and static sky model. Only used if doFilterMorphological is True. Adds a mask plane to an exposure, with the mask plane name set bystreakMaskName (ConfigurableInstance, default <class 'lsst.meas.algorithms.maskStreaks.MaskStreaksConfig'>)

maxFractionEpochsHigh#

Fraction of local number of epochs (N) to use as effective maxNumEpochs for high N. Effective maxNumEpochs = min(maxFractionEpochsLow * N, maxNumEpochs + maxFractionEpochsHigh * N) (float, default 0.03)

Valid Range = [0.0,1.0)

maxFractionEpochsLow#

Fraction of local number of epochs (N) to use as effective maxNumEpochs for low N. Effective maxNumEpochs = min(maxFractionEpochsLow * N, maxNumEpochs + maxFractionEpochsHigh * N) (float, default 0.4)

Valid Range = [0.0,1.0)

maxNumEpochs#: Charactistic maximum local number of epochs/visits in which an artifact candidate can appear and still be masked. The effective maxNumEpochs is a broken linear function of local number of epochs (N): min(maxFractionEpochsLow*N, maxNumEpochs + maxFractionEpochsHigh*N). For each footprint detected on the image difference between the psfMatched warp and static sky model, if a significant fraction of pixels (defined by spatialThreshold) are residuals in more than the computed effective maxNumEpochs, the artifact candidate is deemed persistant rather than transient and not masked. (int, default 2)

maxNumIter#: Maximum number of iterations of forward modeling. (int, default None)

measurePsf#: Task to measure the PSF of the coadd, if doCalculatePsf is set. (ConfigurableInstance, default <class 'lsst.pipe.tasks.measurePsf.MeasurePsfConfig'>)

measurePsfSources#: Task to measure sources for PSF measurement, if doCalculatePsf is set. (ConfigurableInstance, default <class 'lsst.meas.base.sfm.SingleFrameMeasurementConfig'>)

minNumIter#: Minimum number of iterations of forward modeling. (int, default None)

modelWeightsWidth#: Width of the region around detected sources to include in the DcrModel. (float, default 3)

prefilterArtifactsMaskPlanes#: Prefilter artifact candidates that are mostly covered by these bad mask planes. (List, default ('NO_DATA', 'BAD', 'SUSPECT'))

prefilterArtifactsRatio#: Prefilter artifact candidates with less than this fraction overlapping good pixels (float, default 0.05)

regularizationWidth#: Minimum radius of a region to include in regularization, in pixels. (int, default 2)

regularizeModelFrequency#: Maximum relative change of the model allowed between subfilters. Set to zero to disable. (float, default 4.0)

regularizeModelIterations#: Maximum relative change of the model allowed between iterations. Set to zero to disable. (float, default 2.0)

removeMaskPlanes#: Mask planes to remove before coadding (List, default ['NOT_DEBLENDED'])

saveLogOutput#: Flag to enable/disable saving of log output for a task, enabled by default. (bool, default True)

scaleWarpVariance#: Rescale variance on warps (ConfigurableInstance, default <class 'lsst.meas.algorithms.scaleVariance.ScaleVarianceConfig'>)

scaleZeroPoint#: Task to adjust the photometric zero point of the coadd temp exposures Deprecated: Now that visits are scaled to nJy it is no longer necessary or recommended to scale the zero point, so this will be removed after v29. (ConfigurableInstance, default <class 'lsst.pipe.tasks.scaleZeroPoint.ScaleZeroPointConfig'>)

select#: Image selection subtask. (ConfigurableInstance, default <class 'lsst.pipe.tasks.selectImages.PsfWcsSelectImagesConfig'>)

sigmaClip#: Sigma for outlier rejection; ignored if non-clipping statistic selected. (float, default 3.0)

spatialThreshold#

Unitless fraction of pixels defining how much of the outlier region has to meet the temporal criteria. If 0, clip all. If 1, clip none. (float, default 0.5)

Valid Range = [0.0,1.0]

splitSubfilters#: Calculate DCR for two evenly-spaced wavelengths in each subfilter. Instead of at the midpoint (bool, default True)

splitThreshold#: Minimum DCR difference within a subfilter to use splitSubfilters, in pixels.Set to 0 to always split the subfilters. (float, default 0.1)

statistic#: Main stacking statistic for aggregating over the epochs. (str, default 'MEANCLIP')

streakMaskName#: Name of mask bit used for streaks (str, default 'STREAK')

subregionSize#: Width, height of stack subregion size; make small enough that a full stack of images will fit into memory at once. (List, default (2000, 2000))

useConvergence#: Use convergence test as a forward modeling end condition?If not set, skips calculating convergence and runs for maxNumIter iterations (bool, default True)

useModelWeights#: Width of the region around detected sources to include in the DcrModel. (bool, default True)

useProgressiveGain#: Use a gain that slowly increases above baseGain to accelerate convergence? When calculating the next gain, we use up to 5 previous gains and convergence values.Can be set to False to force the model to change at the rate of baseGain. (bool, default True)

warpType#

Warp name: one of ‘direct’ or ‘psfMatched’ (str, default 'direct')

Allowed values:

'direct': Weighted mean of directWarps, with outlier rejection
'psfMatched': Weighted mean of PSF-matched warps
'None': Field is optional

Methods Documentation

setDefaults()#: Subclass hook for computing defaults.

Notes#

Derived Config classes that must compute defaults rather than using the Field instances’s defaults should do so here. To correctly use inherited defaults, implementations of setDefaults must call their base class’s setDefaults.

DcrAssembleCoaddConfig#

Notes#