DiaPipelineConnections

class lsst.ap.association.DiaPipelineConnections(*, config: PipelineTaskConfig = None)

Bases: lsst.pipe.base.PipelineTaskConnections

Butler connections for DiaPipelineTask.

Attributes Summary

allConnections
apdbMarker
defaultTemplates
diaSourceCat
diaSourceSchema
diffIm
dimensions
exposure
initInputs
initOutputs
inputs
outputs
prerequisiteInputs

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 = {'apdbMarker': Output(name='apdb_marker', storageClass='', doc='Marker dataset storing the configuration of the Apdb for each visit/detector. Used to signal the completion of the pipeline.', multiple=False, dimensions=('instrument', 'visit', 'detector')), 'diaSourceCat': Input(name='{coaddName}Diff_diaSrc', storageClass='SourceCatalog', doc='Catalog of DiaSources produced during image differencing.', multiple=False, dimensions=('instrument', 'visit', 'detector'), deferLoad=False), 'diaSourceSchema': InitInput(name='{coaddName}Diff_diaSrc_schema', storageClass='SourceCatalog', doc='Schema of the DiaSource catalog produced during image differencing', multiple=True), 'diffIm': Input(name='{coaddName}Diff_differenceExp', storageClass='ExposureF', doc='Difference image on which the DiaSources were detected.', multiple=False, dimensions=('instrument', 'visit', 'detector'), deferLoad=False), 'exposure': Input(name='calexp', storageClass='ExposureF', doc='Calibrated exposure differenced with a template image during image differencing.', multiple=False, dimensions=('instrument', 'visit', 'detector'), deferLoad=False)}

apdbMarker

defaultTemplates = {'coaddName': 'deep'}

diaSourceCat

diaSourceSchema

diffIm

dimensions = {'detector', 'instrument', 'visit'}

exposure

initInputs = frozenset({'diaSourceSchema'})

initOutputs = frozenset()

inputs = frozenset({'exposure', 'diffIm', 'diaSourceCat'})

outputs = frozenset({'apdbMarker'})

prerequisiteInputs = frozenset()

Methods Documentation

adjustQuantum(datasetRefMap: lsst.pipe.base.connections.InputQuantizedConnection)

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.

Parameters:

datasetRefMap : dict

Mapping with keys of dataset type name to list of lsst.daf.butler.DatasetRef objects

Returns:

datasetRefMap : dict

Modified mapping of input with possible adjusted lsst.daf.butler.DatasetRef objects

Raises:

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