AdjustQuantumHelper#

class lsst.pipe.base.AdjustQuantumHelper(inputs: NamedKeyMapping[DatasetType, Sequence[DatasetRef]], outputs: NamedKeyMapping[DatasetType, Sequence[DatasetRef]], inputs_adjusted: bool = False, outputs_adjusted: bool = False)#

Bases: object

This class holds inputs and outputs mappings in the form used by lsst.daf.butler.Quantum and execution harness code, i.e. with DatasetType keys, translating them to and from the connection-oriented mappings used inside PipelineTaskConnections.

Attributes Summary

`inputs`	Mapping of regular input and prerequisite input datasets, grouped by `DatasetType`.
`inputs_adjusted`	Whether any inputs were removed in the last call to `adjust_in_place`.
`outputs`	Mapping of output datasets, grouped by `DatasetType`.
`outputs_adjusted`	Whether any outputs were removed in the last call to `adjust_in_place`.

Methods Summary

adjust_in_place(connections, label, data_id)

Call adjustQuantum and update self with its results.

Attributes Documentation

inputs: NamedKeyMapping[DatasetType, Sequence[DatasetRef]] = <dataclasses._MISSING_TYPE object>#: Mapping of regular input and prerequisite input datasets, grouped by DatasetType.

inputs_adjusted: bool = False#: Whether any inputs were removed in the last call to adjust_in_place.

outputs: NamedKeyMapping[DatasetType, Sequence[DatasetRef]] = <dataclasses._MISSING_TYPE object>#: Mapping of output datasets, grouped by DatasetType.

outputs_adjusted: bool = False#: Whether any outputs were removed in the last call to adjust_in_place.

Methods Documentation

adjust_in_place(connections: PipelineTaskConnections, label: str, data_id: DataCoordinate) → None#

Call adjustQuantum and update self with its results.

Parameters#

connectionsPipelineTaskConnections: Instance on which to call adjustQuantum.
labelstr: Label for this task in the pipeline (should be used in all diagnostic messages).
data_idlsst.daf.butler.DataCoordinate: Data ID for this quantum in the pipeline (should be used in all diagnostic messages).