MatchedBaseTaskConnections¶

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

Bases: lsst.pipe.base.PipelineTaskConnections

Attributes Summary

`allConnections`
`astromCalibs`
`defaultTemplates`
`dimensions`
`externalPhotoCalibGlobalCatalog`
`externalPhotoCalibTractCatalog`
`externalSkyWcsGlobalCatalog`
`externalSkyWcsTractCatalog`
`initInputs`
`initOutputs`
`inputs`
`outputs`
`photoCalibs`
`prerequisiteInputs`
`skyMap`
`sourceCatalogs`

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 = {'astromCalibs': Input(name='{wcsName}', storageClass='Wcs', doc='WCS for the catalog.', multiple=True, dimensions=('instrument', 'visit', 'detector', 'band'), isCalibration=False, deferLoad=False), 'externalPhotoCalibGlobalCatalog': Input(name='{externalPhotoCalibName}PhotoCalibCatalog', storageClass='ExposureCatalog', doc='Per-visit photometric calibrations computed globally (with no tract information). These catalogs use the detector id for the catalog id, sorted on id for fast lookup.', multiple=True, dimensions=('instrument', 'visit', 'band'), isCalibration=False, deferLoad=False), 'externalPhotoCalibTractCatalog': Input(name='{externalPhotoCalibName}PhotoCalibCatalog', storageClass='ExposureCatalog', doc='Per-tract, per-visit photometric calibrations. These catalogs use the detector id for the catalog id, sorted on id for fast lookup.', multiple=True, dimensions=('instrument', 'visit', 'tract', 'band'), isCalibration=False, deferLoad=False), 'externalSkyWcsGlobalCatalog': Input(name='{externalWcsName}SkyWcsCatalog', storageClass='ExposureCatalog', doc='Per-visit wcs calibrations computed globally (with no tract information). These catalogs use the detector id for the catalog id, sorted on id for fast lookup.', multiple=True, dimensions=('instrument', 'visit', 'band'), isCalibration=False, deferLoad=False), 'externalSkyWcsTractCatalog': Input(name='{externalWcsName}SkyWcsCatalog', storageClass='ExposureCatalog', doc='Per-tract, per-visit wcs calibrations. These catalogs use the detector id for the catalog id, sorted on id for fast lookup.', multiple=True, dimensions=('instrument', 'visit', 'tract', 'band'), isCalibration=False, deferLoad=False), 'photoCalibs': 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), 'sourceCatalogs': Input(name='src', storageClass='SourceCatalog', doc='Source catalogs to match up.', multiple=True, dimensions=('instrument', 'visit', 'detector', 'band'), isCalibration=False, deferLoad=False)}¶

astromCalibs¶

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

dimensions = set()¶

externalPhotoCalibGlobalCatalog¶

externalPhotoCalibTractCatalog¶

externalSkyWcsGlobalCatalog¶

externalSkyWcsTractCatalog¶

initInputs = frozenset()¶

initOutputs = frozenset()¶

inputs = frozenset({'photoCalibs', 'skyMap', 'sourceCatalogs', 'astromCalibs', 'externalSkyWcsGlobalCatalog', 'externalPhotoCalibTractCatalog', 'externalSkyWcsTractCatalog', 'externalPhotoCalibGlobalCatalog'})¶

outputs = frozenset()¶

photoCalibs¶

prerequisiteInputs = frozenset()¶

skyMap¶

sourceCatalogs¶

Methods Documentation

adjustQuantum(datasetRefMap: lsst.daf.butler.core.named.NamedKeyDict[lsst.daf.butler.core.datasets.type.DatasetType, typing.Set[lsst.daf.butler.core.datasets.ref.DatasetRef]][lsst.daf.butler.core.datasets.type.DatasetType, Set[lsst.daf.butler.core.datasets.ref.DatasetRef]]) → lsst.daf.butler.core.named.NamedKeyDict[lsst.daf.butler.core.datasets.type.DatasetType, typing.Set[lsst.daf.butler.core.datasets.ref.DatasetRef]][lsst.daf.butler.core.datasets.type.DatasetType, Set[lsst.daf.butler.core.datasets.ref.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:	datasetRefMap : `NamedKeyDict` Mapping from dataset type to a `set` of `lsst.daf.butler.DatasetRef` objects
Returns:	datasetRefMap : `NamedKeyDict` 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.core.quantum.Quantum) → Tuple[lsst.pipe.base.connections.InputQuantizedConnection, lsst.pipe.base.connections.OutputQuantizedConnection]¶

Builds QuantizedConnections corresponding to input Quantum

Parameters:	quantum : `lsst.daf.butler.Quantum` Quantum object which defines the inputs and outputs for a given unit of processing
Returns:	retVal : `tuple` of (`InputQuantizedConnection`, `OutputQuantizedConnection`) Namespaces mapping attribute names (identifiers of connections) to butler references defined in the input `lsst.daf.butler.Quantum`

Navigation

MatchedBaseTaskConnections¶