CharacterizeImageTask¶

Python API summary¶

from lsst.pipe.tasks.characterizeImage import CharacterizeImageTask

classCharacterizeImageTask(butler=None, refObjLoader=None, schema=None, **kwargs): !Measure bright sources and use this to estimate background and PSF of an exposure...

attributeconfig: Access configuration fields and retargetable subtasks.

methodrun(exposure, exposureIdInfo=None, background=None): !Characterize a science image...

methodrunDataRef(dataRef, exposure=None, background=None, doUnpersist=True): !Characterize a science image and, if wanted, persist the results...

Retargetable subtasks¶

applyApCorr¶

Default: lsst.meas.base.applyApCorr.ApplyApCorrTask
Field type: ConfigurableField

Subtask to apply aperture corrections

background¶

Default: lsst.meas.algorithms.subtractBackground.SubtractBackgroundTask
Field type: ConfigurableField

Configuration for initial background estimation

catalogCalculation¶

Default: lsst.meas.base.catalogCalculation.CatalogCalculationTask
Field type: ConfigurableField

Subtask to run catalogCalculation plugins on catalog

deblend¶

Default: lsst.meas.deblender.deblend.SourceDeblendTask
Field type: ConfigurableField

Split blended source into their components

detection¶

Default: lsst.meas.algorithms.detection.SourceDetectionTask
Field type: ConfigurableField

Detect sources

installSimplePsf¶

Default: lsst.meas.algorithms.installGaussianPsf.InstallGaussianPsfTask
Field type: ConfigurableField

Install a simple PSF model

measureApCorr¶

Default: lsst.meas.algorithms.measureApCorr.MeasureApCorrTask
Field type: ConfigurableField

Subtask to measure aperture corrections

measurePsf¶

Default: lsst.pipe.tasks.measurePsf.MeasurePsfTask
Field type: ConfigurableField

Measure PSF

measurement¶

Default: lsst.meas.base.sfm.SingleFrameMeasurementTask
Field type: ConfigurableField

Measure sources

refObjLoader¶

Default: lsst.meas.algorithms.loadIndexedReferenceObjects.LoadIndexedReferenceObjectsTask
Field type: ConfigurableField

reference object loader

ref_match¶

Default: lsst.meas.astrom.ref_match.RefMatchTask
Field type: ConfigurableField

Task to load and match reference objects. Only used if measurePsf can use matches. Warning: matching will only work well if the initial WCS is accurate enough to give good matches (roughly: good to 3 arcsec across the CCD).

repair¶

Default: lsst.pipe.tasks.repair.RepairTask
Field type: ConfigurableField

Remove cosmic rays

Configuration fields¶

checkUnitsParseStrict¶

Default: 'raise'
Field type: str Field

Strictness of Astropy unit compatibility check, can be ‘raise’, ‘warn’ or ‘silent’

connections¶

Data type: lsst.pipe.base.config.Connections
Field type: ConfigField

Configurations describing the connections of the PipelineTask to datatypes

doApCorr¶

Default: True
Field type: bool Field

Run subtasks to measure and apply aperture corrections

doDeblend¶

Default: True
Field type: bool Field

Run deblender input exposure

doMeasurePsf¶

Default: True
Field type: bool Field

Measure PSF? If False then for all subsequent operations use either existing PSF model when present, or install simple PSF model when not (see installSimplePsf config options)

doWrite¶

Default: True
Field type: bool Field

Persist results?

doWriteExposure¶

Default: True
Field type: bool Field

Write icExp and icExpBackground in addition to icSrc? Ignored if doWrite False.

psfIterations¶

Default: 2
Field type: int RangeField
Range: [1,inf)

Number of iterations of detect sources, measure sources, estimate PSF. If useSimplePsf is True then 2 should be plenty; otherwise more may be wanted.

saveMetadata¶

Default: True
Field type: bool Field

Flag to enable/disable metadata saving for a task, enabled by default.

useSimplePsf¶

Default: True
Field type: bool Field

Replace the existing PSF model with a simplified version that has the same sigma at the start of each PSF determination iteration? Doing so makes PSF determination converge more robustly and quickly.

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