AssembleCoaddConnections¶
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class
lsst.pipe.tasks.assembleCoadd.
AssembleCoaddConnections
(*, config=None)¶ Bases:
lsst.pipe.base.PipelineTaskConnections
Attributes Summary
allConnections
brightObjectMask
coaddExposure
defaultTemplates
dimensions
initInputs
initOutputs
inputWarps
inputs
nImage
outputs
prerequisiteInputs
skyMap
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
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allConnections
= {'brightObjectMask': PrerequisiteInput(name='brightObjectMask', storageClass='ObjectMaskCatalog', doc='Input Bright Object Mask mask produced with external catalogs to be applied to the mask plane BRIGHT_OBJECT.', multiple=False, dimensions=('tract', 'patch', 'skymap', 'abstract_filter'), deferLoad=False), 'coaddExposure': Output(name='{fakesType}{outputCoaddName}Coadd{warpTypeSuffix}', storageClass='ExposureF', doc='Output coadded exposure, produced by stacking input warps', multiple=False, dimensions=('tract', 'patch', 'skymap', 'abstract_filter')), 'inputWarps': Input(name='{inputCoaddName}Coadd_{warpType}Warp', storageClass='ExposureF', doc='Input list of warps to be assemebled i.e. stacked.WarpType (e.g. direct, psfMatched) is controlled by the warpType config parameter', multiple=True, dimensions=('tract', 'patch', 'skymap', 'visit', 'instrument'), deferLoad=True), 'nImage': Output(name='{outputCoaddName}Coadd_nImage', storageClass='ImageU', doc='Output image of number of input images per pixel', multiple=False, dimensions=('tract', 'patch', 'skymap', 'abstract_filter')), 'skyMap': Input(name='{inputCoaddName}Coadd_skyMap', storageClass='SkyMap', doc='Input definition of geometry/bbox and projection/wcs for coadded exposures', multiple=False, dimensions=('skymap',), deferLoad=False)}¶
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brightObjectMask
¶
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coaddExposure
¶
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defaultTemplates
= {'fakesType': '', 'inputCoaddName': 'deep', 'outputCoaddName': 'deep', 'warpType': 'direct', 'warpTypeSuffix': ''}¶
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dimensions
= {'patch', 'abstract_filter', 'tract', 'skymap'}¶
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initInputs
= frozenset()¶
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initOutputs
= frozenset()¶
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inputWarps
¶
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inputs
= frozenset({'inputWarps', 'skyMap'})¶
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nImage
¶
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outputs
= frozenset({'coaddExposure', 'nImage'})¶
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prerequisiteInputs
= frozenset({'brightObjectMask'})¶
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skyMap
¶
Methods Documentation
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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: Returns: 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.
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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 inputlsst.daf.butler.Quantum
- quantum :
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