SingleMetadataMetricConnections¶
-
class
lsst.verify.tasks.
SingleMetadataMetricConnections
(*, config=None)¶ Bases:
lsst.verify.tasks.MetricConnections
An abstract connections class defining a metadata input.
Notes
SingleMetadataMetricConnections
defines the following dataset templates:package
- Name of the metric’s namespace. By verify_metrics convention, this is the name of the package the metric is most closely associated with.
metric
- Name of the metric, excluding any namespace.
labelName
- Pipeline label of the
PipelineTask
or name of theCmdLineTask
whose metadata are being read.
Attributes Summary
allConnections
defaultTemplates
dimensions
initInputs
initOutputs
inputs
measurement
metadata
outputs
prerequisiteInputs
Methods Summary
adjustQuantum
(datasetRefMap, …)Override to make adjustments to lsst.daf.butler.DatasetRef
objects in thelsst.daf.butler.core.Quantum
during the graph generation stage of the activator.buildDatasetRefs
(quantum)Builds QuantizedConnections corresponding to input Quantum Attributes Documentation
-
allConnections
= {'measurement': Output(name='metricvalue_{package}_{metric}', storageClass='MetricValue', doc='The metric value computed by this task.', multiple=False, dimensions={'detector', 'visit', 'instrument'}, isCalibration=False), 'metadata': Input(name='{labelName}_metadata', storageClass='PropertySet', doc="The target top-level task's metadata. The name must be set to the metadata's butler type, such as 'processCcd_metadata'.", multiple=False, dimensions={'detector', 'visit', 'instrument'}, isCalibration=False, deferLoad=False)}¶
-
defaultTemplates
= {'labelName': '', 'metric': None, 'package': None}¶
-
dimensions
= {'detector', 'visit', 'instrument'}¶
-
initInputs
= frozenset()¶
-
initOutputs
= frozenset()¶
-
inputs
= frozenset({'metadata'})¶
-
measurement
¶
-
metadata
¶
-
outputs
= frozenset({'measurement'})¶
-
prerequisiteInputs
= frozenset()¶
Methods Documentation
-
adjustQuantum
(datasetRefMap: lsst.daf.butler.core.named.NamedKeyDict[lsst.daf.butler.core.datasets.type.DatasetType, typing.Set[lsst.daf.butler.core.datasets.ref.DatasetRef]][lsst.daf.butler.core.datasets.type.DatasetType, Set[lsst.daf.butler.core.datasets.ref.DatasetRef]]) → lsst.daf.butler.core.named.NamedKeyDict[lsst.daf.butler.core.datasets.type.DatasetType, typing.Set[lsst.daf.butler.core.datasets.ref.DatasetRef]][lsst.daf.butler.core.datasets.type.DatasetType, Set[lsst.daf.butler.core.datasets.ref.DatasetRef]]¶ Override to make adjustments to
lsst.daf.butler.DatasetRef
objects in thelsst.daf.butler.core.Quantum
during the graph generation stage of the activator.The base class implementation simply checks that input connections with
multiple
set toFalse
have no more than one dataset.Parameters: - datasetRefMap :
NamedKeyDict
Mapping from dataset type to a
set
oflsst.daf.butler.DatasetRef
objects
Returns: - datasetRefMap :
NamedKeyDict
Modified mapping of input with possibly adjusted
lsst.daf.butler.DatasetRef
objects.
Raises: - ScalarError
Raised if any
Input
orPrerequisiteInput
connection hasmultiple
set toFalse
, but multiple datasets.- 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.
- datasetRefMap :
-
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 :