DiaPipelineConnections

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

Bases: lsst.pipe.base.PipelineTaskConnections

Butler connections for DiaPipelineTask.

Attributes Summary

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

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='Config', 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'), isCalibration=False), 'associatedDiaSources': Output(name='{fakesType}{coaddName}Diff_assocDiaSrc', storageClass='DataFrame', doc='Optional output storing the DiaSource catalog after matching, calibration, and standardization for insertation into the Apdb.', multiple=False, dimensions=('instrument', 'visit', 'detector'), isCalibration=False), 'diaSourceCat': Input(name='{fakesType}{coaddName}Diff_diaSrc', storageClass='SourceCatalog', doc='Catalog of DiaSources produced during image differencing.', multiple=False, dimensions=('instrument', 'visit', 'detector'), isCalibration=False, deferLoad=False), 'diaSourceSchema': InitInput(name='{fakesType}{coaddName}Diff_diaSrc_schema', storageClass='SourceCatalog', doc='Schema of the DiaSource catalog produced during image differencing', multiple=True), 'diffIm': Input(name='{fakesType}{coaddName}Diff_differenceExp', storageClass='ExposureF', doc='Difference image on which the DiaSources were detected.', multiple=False, dimensions=('instrument', 'visit', 'detector'), isCalibration=False, 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'), isCalibration=False, deferLoad=False), 'warpedExposure': Input(name='{fakesType}{coaddName}Diff_warpedExp', storageClass='ExposureF', doc='Warped template used to create `subtractedExposure`. Not PSF matched.', multiple=False, dimensions=('instrument', 'visit', 'detector'), isCalibration=False, deferLoad=False)}

apdbMarker

associatedDiaSources

defaultTemplates = {'coaddName': 'deep', 'fakesType': ''}

diaSourceCat

diaSourceSchema

diffIm

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

exposure

initInputs = frozenset({'diaSourceSchema'})

initOutputs = frozenset()

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

outputs = frozenset({'apdbMarker', 'associatedDiaSources'})

prerequisiteInputs = frozenset()

warpedExposure

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.

This implementation checks to make sure that the filters in the dataset are compatible with AP processing as set by the Apdb/DPDD schema.

Parameters:

datasetRefMap : NamedKeyDict

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

Returns:

datasetRefMap : NamedKeyDict

Mapping of input with assurances that bands incompatible with the Apdb are present.

Raises:

ValueError

Raises if a data ref in the quantum has a band not available in the Apdb.

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