DcrAssembleCoaddTask¶
Python API summary¶
from lsst.pipe.tasks.dcrAssembleCoadd import DcrAssembleCoaddTask
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class
DcrAssembleCoaddTask Assemble DCR coadded images from a set of warps
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attribute
config Access configuration fields and retargetable subtasks.
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method
run Assemble the coadd
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method
runDataRef Assemble a coadd from a set of warps
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See also
See the DcrAssembleCoaddTask API reference for complete details.
Retargetable subtasks¶
assembleStaticSkyModel¶
- Default
lsst.pipe.tasks.assembleCoadd.AssembleCoaddTask- Field type
ConfigurableField
Task to assemble an artifact-free, PSF-matched Coadd to serve as a naive/first-iteration model of the static sky.
detect¶
- Default
lsst.meas.algorithms.detection.SourceDetectionTask- Field type
ConfigurableField
Detect outlier sources on difference between each psfMatched warp and static sky model
detectPsfSources¶
- Default
lsst.meas.algorithms.detection.SourceDetectionTask- Field type
ConfigurableField
Task to detect sources for PSF measurement, if
doCalculatePsf is set.detectTemplate¶
- Default
lsst.meas.algorithms.detection.SourceDetectionTask- Field type
ConfigurableField
Detect sources on static sky model. Only used if doPreserveContainedBySource is True
inputRecorder¶
- Default
lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderTask- Field type
ConfigurableField
Subtask that helps fill CoaddInputs catalogs added to the final Exposure
interpImage¶
- Default
lsst.pipe.tasks.interpImage.InterpImageTask- Field type
ConfigurableField
Task to interpolate (and extrapolate) over NaN pixels
measurePsf¶
- Default
lsst.pipe.tasks.measurePsf.MeasurePsfTask- Field type
ConfigurableField
Task to measure the PSF of the coadd, if
doCalculatePsf is set.measurePsfSources¶
- Default
lsst.meas.base.sfm.SingleFrameMeasurementTask- Field type
ConfigurableField
Task to measure sources for PSF measurement, if
doCalculatePsf is set.modelPsf¶
- Default
lsst.meas.algorithms.gaussianPsfFactory.applyWrapper- Field type
ConfigurableField
Model Psf factory
scaleWarpVariance¶
- Default
lsst.pipe.tasks.scaleVariance.ScaleVarianceTask- Field type
ConfigurableField
Rescale variance on warps
scaleZeroPoint¶
- Default
lsst.pipe.tasks.scaleZeroPoint.ScaleZeroPointTask- Field type
ConfigurableField
Task to adjust the photometric zero point of the coadd temp exposures
select¶
- Default
lsst.pipe.tasks.selectImages.WcsSelectImagesTask- Field type
ConfigurableField
Image selection subtask.
Configuration fields¶
accelerateModel¶
Factor to amplify the differences between model planes by to speed convergence.
badMaskPlanes¶
Mask planes that, if set, the associated pixel should not be included in the coaddTempExp.
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.brightObjectMask¶
- Data type
lsst.pipe.base.config.InputDatasetConfig- Field type
ConfigField
Input Bright Object Mask mask produced with external catalogs to be applied to the mask plane BRIGHT_OBJECT.
brightObjectMaskName¶
Name of mask bit used for bright objects
calcErrorFromInputVariance¶
Calculate coadd variance from input variance by stacking statistic.Passed to StatisticsControl.setCalcErrorFromInputVariance()
clipIter¶
Number of iterations of outlier rejection; ignored if non-clipping statistic selected.
coaddExposure¶
- Data type
lsst.pipe.base.config.OutputDatasetConfig- Field type
ConfigField
Output coadded exposure, produced by stacking input warps
coaddPsf¶
- Data type
lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsfConfig- Field type
ConfigField
Configuration for CoaddPsf
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.
doAirmassWeight¶
Weight exposures by airmass? Useful if there are relatively few high-airmass observations.
doApplyUberCal¶
Apply jointcal WCS and PhotoCalib results to input calexps?
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
doInterp¶
Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly.
doNImage¶
Create image of number of contributing exposures for each pixel
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’.
doPreserveContainedBySource¶
Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd. Replicates a behavior of SafeClip.
doPsfMatch¶
Match to modelPsf? Deprecated. Sets makePsfMatched=True, makeDirect=False
doScaleWarpVariance¶
Rescale Warp variance plane using empirical noise?
doSigmaClip¶
Perform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED)
doUsePsfMatchedPolygons¶
Use ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only.
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.
inputWarps¶
- Data type
lsst.pipe.base.config.InputDatasetConfig- Field type
ConfigField
Input list of warps to be assemebled i.e. stacked.WarpType (e.g. direct, psfMatched) is controlled by we warpType config parameter
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.
maxFractionEpochsHigh¶
- Default
0.03- Field type
floatRangeField- Range
- [0.0,1.0)
Fraction of local number of epochs (N) to use as effective maxNumEpochs for high N. Effective maxNumEpochs = min(maxFractionEpochsLow * N, maxNumEpochs + maxFractionEpochsHigh * N)
maxFractionEpochsLow¶
- Default
0.4- Field type
floatRangeField- Range
- [0.0,1.0)
Fraction of local number of epochs (N) to use as effective maxNumEpochs for low N. Effective maxNumEpochs = min(maxFractionEpochsLow * N, maxNumEpochs + maxFractionEpochsHigh * N)
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.
maxNumIter¶
Maximum number of iterations of forward modeling.
minNumIter¶
Minimum number of iterations of forward modeling.
modelWeightsWidth¶
Width of the region around detected sources to include in the DcrModel.
nImage¶
- Data type
lsst.pipe.base.config.OutputDatasetConfig- Field type
ConfigField
Output image of number of input images per pixel
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
psfMatchedWarps¶
- Data type
lsst.pipe.base.config.InputDatasetConfig- Field type
ConfigField
PSF-Matched Warps are required by CompareWarp regardless of the coadd type requested. Only PSF-Matched Warps make sense for image subtraction. Therefore, they must be in the InputDatasetField and made available to the task.
quantum¶
- Data type
lsst.pipe.base.config.QuantumConfig- Field type
ConfigField
configuration for PipelineTask quantum
regularizationWidth¶
Minimum radius of a region to include in regularization, in pixels.
regularizeModelFrequency¶
Maximum relative change of the model allowed between subfilters.Set to zero to disable.
regularizeModelIterations¶
Maximum relative change of the model allowed between iterations.Set to zero to disable.
removeMaskPlanes¶
Mask planes to remove before coadding
sigmaClip¶
Sigma for outlier rejection; ignored if non-clipping statistic selected.
skyMap¶
- Data type
lsst.pipe.base.config.InputDatasetConfig- Field type
ConfigField
Input definition of geometry/bbox and projection/wcs for coadded exposures
spatialThreshold¶
- Default
0.5- Field type
floatRangeField- Range
- [0.0,1.0]
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.
splitSubfilters¶
Calculate DCR for two evenly-spaced wavelengths in each subfilter.Instead of at the midpoint
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.
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 iterationsuseMeasMosaic¶
Use meas_mosaic’s applyMosaicResultsExposure() to do the photometric calibration/wcs update (deprecated).
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.