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`s 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', 'skymap', 'tract', 'patch'}

exposure

initInputs = frozenset({'inputSchema'})

initOutputs = frozenset({'outputSchema'})

inputSchema

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

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`s 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`s

Returns:

datasetRefMap : dict

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

Raises:

Exception

Overrides of this function have the option of raising and 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