PrerequisiteFinder¶
- class lsst.pipe.base.prerequisite_helpers.PrerequisiteFinder(edge: ReadEdge, bounds: PrerequisiteBounds, pipeline_graph: PipelineGraph)¶
Bases:
object
A QuantumGraph-generation helper class that manages the searches for a prerequisite input connection.
- Parameters:
- edge
pipeline_graph.ReadEdge
A
PipelineGraph
edge that represents a single prerequisite input connection.- bounds
PrerequisiteBounds
Another helper object that manages the spatial/temporal bounds of the task’s quanta, shared by all prerequisite inputs for that task.
- pipeline_graph
pipeline_graph.PipelineGraph
Graph representation of the pipeline.
- edge
Notes
PrerequisiteFinder
instances are usually constructed by aPrerequisiteInfo
instance, which is in turn constructed by and attached to the baseQuantumGraphBuilder
when a new builder is constructed. During theQuantumGraphBuilder.process_subgraph
hook implemented by a builder subclass, prerequisite inputs may be found in other ways (e.g. via bulk queries), as long as the results are consistent with the finder’s attributes, and this is indicated to the baseQuantumGraphBuilder
by removing those finder instances after those prerequisites have been found and added to aQuantumGraphSkeleton
. Finder instances that remain in the builder are used by callingPrerequisiteFinder.find
on each quantum later inQuantumGraphBuilder.build
.Attributes Summary
The
PipelineGraph
node that represents the task for this connection.Methods Summary
find
(butler, input_collections, data_id, ...)Find prerequisite input datasets for a single quantum.
Attributes Documentation
- task_node¶
The
PipelineGraph
node that represents the task for this connection.
Methods Documentation
- find(butler: Butler, input_collections: Sequence[str], data_id: DataCoordinate, skypix_bounds: Mapping[str, RangeSet], timespan: Timespan | None) list[lsst.daf.butler._dataset_ref.DatasetRef] ¶
Find prerequisite input datasets for a single quantum.
- Parameters:
- butler
lsst.daf.butler.Butler
Butler client to use for queries.
- input_collections
Sequence
[str
] Sequence of collections to search, in order.
- data_id
lsst.daf.butler.DataCoordinate
Data ID for the quantum.
- skypix_bounds
Mapping
[str
,lsst.sphgeom.RangeSet
] The spatial bounds of this quantum in various skypix dimensions. Keys are skypix dimension names (a superset of those in
dataset_skypix
) and values are sets of integer pixel ID ranges.- timespan
lsst.daf.butler.Timespan
orNone
The temporal bounds of this quantum. Guaranteed to not be
None
ifdataset_has_timespan
isTrue
.
- butler
- Returns:
- refs
list
[lsst.daf.butler.DatasetRef
] Dataset references. These use
self.dataset_type_node.dataset_type
, which may differ from the connection’s dataset type in storage class or [lack of] component.
- refs
- Raises:
- NotImplementedError
Raised for certain relationships between task and dataset type dimensions that are possible to define but not believed to be useful in practice. These errors occur late rather than early in order to allow a
QuantumGraphBuilder
subclass to handle them first, in case an unusual task’s needs must be met by a custom builder class anyway.