Quantum¶
-
class
lsst.daf.butler.
Quantum
(*, taskName: Optional[str] = None, taskClass: Optional[Type[CT_co]] = None, dataId: Optional[lsst.daf.butler.core.dimensions._coordinate.DataCoordinate] = None, initInputs: Union[Mapping[lsst.daf.butler.core.datasets.type.DatasetType, lsst.daf.butler.core.datasets.ref.DatasetRef], Iterable[lsst.daf.butler.core.datasets.ref.DatasetRef], None] = None, inputs: Optional[Mapping[lsst.daf.butler.core.datasets.type.DatasetType, List[lsst.daf.butler.core.datasets.ref.DatasetRef]]] = None, outputs: Optional[Mapping[lsst.daf.butler.core.datasets.type.DatasetType, List[lsst.daf.butler.core.datasets.ref.DatasetRef]]] = None)¶ Bases:
object
A discrete unit of work that may depend on one or more datasets and produces one or more datasets.
Most Quanta will be executions of a particular
PipelineTask
’srunQuantum
method, but they can also be used to represent discrete units of work performed manually by human operators or other software agents.Parameters: - taskName :
str
, optional Fully-qualified name of the Task class that executed or will execute this Quantum. If not provided,
taskClass
must be.- taskClass :
type
, optional The Task class that executed or will execute this Quantum. If not provided,
taskName
must be. OverridestaskName
if both are provided.- dataId :
DataId
, optional The dimension values that identify this
Quantum
.- initInputs : collection of
DatasetRef
, optional Datasets that are needed to construct an instance of the Task. May be a flat iterable of
DatasetRef
instances or a mapping fromDatasetType
toDatasetRef
.- inputs :
Mapping
, optional Inputs identified prior to execution, organized as a mapping from
DatasetType
to a list ofDatasetRef
.- outputs :
Mapping
, optional Outputs from executing this quantum of work, organized as a mapping from
DatasetType
to a list ofDatasetRef
.
Attributes Summary
dataId
The dimension values of the unit of processing ( DataId
).initInputs
A mapping of datasets used to construct the Task, with DatasetType
instances as keys (names can also be used for lookups) andDatasetRef
instances as values.inputs
A mapping of input datasets that were expected to be used, with DatasetType
instances as keys (names can also be used for lookups) and a list ofDatasetRef
instances as values.outputs
A mapping of output datasets (to be) generated for this quantum, with the same form as predictedInputs
.taskClass
Task class associated with this Quantum
(type
).taskName
Fully-qualified name of the task associated with Quantum
(str
).Attributes Documentation
-
dataId
¶ The dimension values of the unit of processing (
DataId
).
-
initInputs
¶ A mapping of datasets used to construct the Task, with
DatasetType
instances as keys (names can also be used for lookups) andDatasetRef
instances as values.
-
inputs
¶ A mapping of input datasets that were expected to be used, with
DatasetType
instances as keys (names can also be used for lookups) and a list ofDatasetRef
instances as values.Notes
We cannot use
set
instead oflist
for the nested container becauseDatasetRef
instances cannot be compared reliably when some have integers IDs and others do not.
-
outputs
¶ A mapping of output datasets (to be) generated for this quantum, with the same form as
predictedInputs
.Notes
We cannot use
set
instead oflist
for the nested container becauseDatasetRef
instances cannot be compared reliably when some have integers IDs and others do not.
- taskName :