ForcedPhotCoaddTask¶

ForcedPhotCoaddTask performs forced measurement on a co-added image using as a reference catalog detections which were made on coadds in other bands.

Butler datasets¶

Input datasets¶

A Coadd_src variant (e.g. deepCoadd_src): Used as the reference catalog. This is not loaded directly from the provided dataRef; only the patch and tract are used, while the filter is set by the configuration of the references subtask. See lsst.meas.base.references.CoaddSrcReferencesTask.
A Coadd_calexp variant (e.g. deepCoadd_calexp): Used as the measurement image. Note that this means that lsst.pipe.tasks.multiBand.DetectCoaddSourcesTask must have been run on the image previously.

Ouptut datasets¶

A Coadd_forced_src variant (e.g. deepCoadd_forced_src): The resulting measurement catalog.

Python API summary¶

from lsst.meas.base.forcedPhotCoadd import ForcedPhotCoaddTask

classForcedPhotCoaddTask(butler=None, refSchema=None, initInputs=None, **kwds): A command-line driver for performing forced measurement on coadd images...

attributeconfig: Access configuration fields and retargetable subtasks.

methodrun(measCat, exposure, refCat, refWcs, exposureId=None): Perform forced measurement on a single exposure...

methodrunDataRef(dataRef, psfCache=None): Perform forced measurement on a single exposure...

Retargetable subtasks¶

applyApCorr¶

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

Subtask to apply aperture corrections

catalogCalculation¶

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

Subtask to run catalogCalculation plugins on catalog

measurement¶

Default: lsst.meas.base.forcedMeasurement.ForcedMeasurementTask
Field type: ConfigurableField

subtask to do forced measurement

references¶

Default: lsst.meas.base.references.MultiBandReferencesTask
Field type: ConfigurableField

subtask to retrieve reference source catalog

Configuration fields¶

coaddName¶

Default: 'deep'
Field type: str Field

coadd name: typically one of deep or goodSeeing

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 subtask to apply aperture corrections

doConserveFlux¶

Default: True
Field type: bool Field

Whether to use the deblender models as templates to re-distribute the flux from the ‘exposure’ (True), or to perform measurements on the deblender model footprints. If footprintDatasetName != ‘ScarletModelData’ then this field is ignored.

doStripFootprints¶

Default: True
Field type: bool Field

Whether to strip footprints from the output catalog before saving to disk. This is usually done when using scarlet models to save disk space.

footprintDatasetName¶

Default: 'ScarletModelData'
Field type: str Field (optional)

Dataset (without coadd prefix) that should be used to obtain (Heavy)Footprints for sources. Must have IDs that match those of the reference catalog.If None, Footprints will be generated by transforming the reference Footprints.

hasFakes¶

Default: False
Field type: bool Field

Should be set to True if fake sources have been inserted into the input data.

saveLogOutput¶

Default: True
Field type: bool Field

Flag to enable/disable saving of log output for a task, enabled by default.

saveMetadata¶

Default: True
Field type: bool Field

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

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