MatchedBaseTaskConnections¶

class lsst.faro.base.MatchedBaseTaskConnections(*, config=None)¶

Bases: lsst.pipe.base.PipelineTaskConnections

Attributes Summary

`allConnections`
`astrom_calibs`
`defaultTemplates`
`dimensions`
`initInputs`
`initOutputs`
`inputs`
`outputs`
`photo_calibs`
`prerequisiteInputs`
`skyMap`
`source_catalogs`

Methods Summary

`adjustQuantum`(datasetRefMap)	Override to make adjustments to `lsst.daf.butler.DatasetRef` objects in the `lsst.daf.butler.core.Quantum` during the graph generation stage of the activator.
`buildDatasetRefs`(quantum)	Builds QuantizedConnections corresponding to input Quantum

Attributes Documentation

allConnections = {'astrom_calibs': Input(name='{wcsName}', storageClass='Wcs', doc='WCS for the catalog.', multiple=True, dimensions=('instrument', 'visit', 'detector', 'band'), isCalibration=False, deferLoad=False), 'photo_calibs': Input(name='{photoCalibName}', storageClass='PhotoCalib', doc='Photometric calibration object.', multiple=True, dimensions=('instrument', 'visit', 'detector', 'band'), isCalibration=False, deferLoad=False), 'skyMap': Input(name='skyMap', storageClass='SkyMap', doc='Input definition of geometry/bbox and projection/wcs for warped exposures', multiple=False, dimensions=('skymap',), isCalibration=False, deferLoad=False), 'source_catalogs': Input(name='src', storageClass='SourceCatalog', doc='Source catalogs to match up.', multiple=True, dimensions=('instrument', 'visit', 'detector', 'band'), isCalibration=False, deferLoad=False)}¶

astrom_calibs¶

defaultTemplates = {'coaddName': 'deep', 'photoCalibName': 'calexp.photoCalib', 'wcsName': 'calexp.wcs'}¶

dimensions = {}¶

initInputs = frozenset({})¶

initOutputs = frozenset({})¶

inputs = frozenset({'astrom_calibs', 'photo_calibs', 'skyMap', 'source_catalogs'})¶

outputs = frozenset({})¶

photo_calibs¶

prerequisiteInputs = frozenset({})¶

skyMap¶

source_catalogs¶

Methods Documentation

adjustQuantum(datasetRefMap: lsst.daf.butler.NamedKeyDict[lsst.daf.butler.DatasetType, Set[lsst.daf.butler.DatasetRef]]) → lsst.daf.butler.NamedKeyDict[lsst.daf.butler.DatasetType, Set[lsst.daf.butler.DatasetRef]]¶

Override to make adjustments to lsst.daf.butler.DatasetRef objects in the lsst.daf.butler.core.Quantum during the graph generation stage of the activator.

The base class implementation simply checks that input connections with multiple set to False have no more than one dataset.

Parameters

datasetRefMapNamedKeyDict: Mapping from dataset type to a set of lsst.daf.butler.DatasetRef objects

Returns

datasetRefMapNamedKeyDict: Modified mapping of input with possibly adjusted lsst.daf.butler.DatasetRef objects.

Raises

ScalarError: Raised if any Input or PrerequisiteInput connection has multiple set to False, but multiple datasets.
Exception: Overrides of this function have the option of raising an Exception if a field in the input does not satisfy a need for a corresponding pipelineTask, i.e. no reference catalogs are found.

buildDatasetRefs(quantum: lsst.daf.butler.Quantum) → Tuple[lsst.pipe.base.InputQuantizedConnection, lsst.pipe.base.OutputQuantizedConnection]¶

Builds QuantizedConnections corresponding to input Quantum

Parameters

quantumlsst.daf.butler.Quantum: Quantum object which defines the inputs and outputs for a given unit of processing

Returns

retValtuple of (InputQuantizedConnection,: OutputQuantizedConnection) Namespaces mapping attribute names (identifiers of connections) to butler references defined in the input lsst.daf.butler.Quantum

Navigation

MatchedBaseTaskConnections¶