ForcedPhotImageConnections

class lsst.meas.base.ForcedPhotImageConnections(*, config: PipelineTaskConfig = None)

Bases: lsst.pipe.base.PipelineTaskConnections

Attributes Summary

allConnections
defaultTemplates
dimensions
exposure
initInputs
initOutputs
inputSchema
inputs
measCat
outputSchema
outputs
prerequisiteInputs
refCat
refWcs

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 = {'exposure': Input(name='{inputCoaddName}Coadd', storageClass='ExposureF', doc='Input exposure to perform photometry on.', multiple=False, dimensions=['abstract_filter', 'skymap', 'tract', 'patch'], deferLoad=False), 'inputSchema': InitInput(name='{inputCoaddName}Coadd_ref_schema', storageClass='SourceCatalog', doc='Schema for the input measurement catalogs.', multiple=False), 'measCat': Output(name='{outputCoaddName}Coadd_forced_src', storageClass='SourceCatalog', doc='Output forced photometry catalog.', multiple=False, dimensions=['abstract_filter', 'skymap', 'tract', 'patch']), 'outputSchema': InitOutput(name='{outputCoaddName}Coadd_forced_src_schema', storageClass='SourceCatalog', doc='Schema for the output forced measurement catalogs.', multiple=False), 'refCat': Input(name='{inputCoaddName}Coadd_ref', storageClass='SourceCatalog', doc='Catalog of shapes and positions at which to force photometry.', multiple=False, dimensions=['skymap', 'tract', 'patch'], deferLoad=False), 'refWcs': Input(name='{inputCoaddName}Coadd.wcs', storageClass='Wcs', doc='Reference world coordinate system.', multiple=False, dimensions=['abstract_filter', 'skymap', 'tract', 'patch'], deferLoad=False)}

defaultTemplates = {'inputCoaddName': 'deep', 'outputCoaddName': 'deep'}

dimensions = {'abstract_filter', 'tract', 'patch', 'skymap'}

exposure

initInputs = frozenset({'inputSchema'})

initOutputs = frozenset({'outputSchema'})

inputSchema

inputs = frozenset({'refCat', 'refWcs', 'exposure'})

measCat

outputSchema

outputs = frozenset({'measCat'})

prerequisiteInputs = frozenset()

refCat

refWcs

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