ObjectEpochTableTask

class lsst.analysis.tools.tasks.ObjectEpochTableTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)

Bases: PipelineTask

Collect mean epochs for the observations that went into each object.

TODO: DM-46202, Remove this task once the object epochs are available elsewhere.

Methods Summary

getEpochs(cat, epochMapDict)	Get mean epoch of the visits corresponding to object position.
runQuantum(butlerQC, inputRefs, outputRefs)	Do butler IO and transform to provide in memory objects for tasks run method.

Methods Documentation

getEpochs(cat, epochMapDict)

Get mean epoch of the visits corresponding to object position.

Parameters

catastropy.table.Table

Catalog containing object positions.

epochMapDict: dict [DeferredDatasetHandle]

Dictionary of handles for healsparse maps containing the mean epoch for positions in the reference catalog.

Returns

epochDf = astropy.table.Table

Catalog with mean epoch of visits at each object position.

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.