MergeDetectionsTask

class lsst.pipe.tasks.mergeDetections.MergeDetectionsTask(schema=None, initInputs=None, **kwargs)

Bases: PipelineTask

Merge sources detected in coadds of exposures obtained with different filters.

Merge sources detected in coadds of exposures obtained with different filters. To perform photometry consistently across coadds in multiple filter bands, we create a master catalog of sources from all bands by merging the sources (peaks & footprints) detected in each coadd, while keeping track of which band each source originates in. The catalog merge is performed by getMergedSourceCatalog. Spurious peaks detected around bright objects are culled as described in CullPeaksConfig.

MergeDetectionsTask is meant to be run after detecting sources in coadds generated for the chosen subset of the available bands. The purpose of the task is to merge sources (peaks & footprints) detected in the coadds generated from the chosen subset of filters. Subsequent tasks in the multi-band processing procedure will deblend the generated master list of sources and, eventually, perform forced photometry.

Parameters:
schemalsst.afw.table.Schema, optional

The schema of the detection catalogs used as input to this task.

initInputsdict, optional

Dictionary that can contain a key schema containing the input schema. If present will override the value of schema.

**kwargs

Additional keyword arguments.

Attributes Summary

canMultiprocess

Methods Summary

cullPeaks(catalog)

Attempt to remove garbage peaks (mostly on the outskirts of large blends).

emptyMetadata()

Empty (clear) the metadata for this Task and all sub-Tasks.

getFullMetadata()

Get metadata for all tasks.

getFullName()

Get the task name as a hierarchical name including parent task names.

getName()

Get the name of the task.

getSkySourceFootprints(mergedList, skyInfo, seed)

Return a list of Footprints of sky objects which don't overlap with anything in mergedList.

getTaskDict()

Get a dictionary of all tasks as a shallow copy.

makeField(doc)

Make a lsst.pex.config.ConfigurableField for this task.

makeSubtask(name, **keyArgs)

Create a subtask as a new instance as the name attribute of this task.

run(catalogs, skyInfo, idFactory, skySeed)

Merge multiple catalogs.

runQuantum(butlerQC, inputRefs, outputRefs)

Do butler IO and transform to provide in memory objects for tasks run method.

timer(name[, logLevel])

Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess: ClassVar[bool] = True

Methods Documentation

cullPeaks(catalog)

Attempt to remove garbage peaks (mostly on the outskirts of large blends).

Parameters:
cataloglsst.afw.table.SourceCatalog

Source catalog.

emptyMetadata() None

Empty (clear) the metadata for this Task and all sub-Tasks.

getFullMetadata() TaskMetadata

Get metadata for all tasks.

Returns:
metadataTaskMetadata

The keys are the full task name. Values are metadata for the top-level task and all subtasks, sub-subtasks, etc.

Notes

The returned metadata includes timing information (if @timer.timeMethod is used) and any metadata set by the task. The name of each item consists of the full task name with . replaced by :, followed by . and the name of the item, e.g.:

topLevelTaskName:subtaskName:subsubtaskName.itemName

using : in the full task name disambiguates the rare situation that a task has a subtask and a metadata item with the same name.

getFullName() str

Get the task name as a hierarchical name including parent task names.

Returns:
fullNamestr

The full name consists of the name of the parent task and each subtask separated by periods. For example:

  • The full name of top-level task “top” is simply “top”.

  • The full name of subtask “sub” of top-level task “top” is “top.sub”.

  • The full name of subtask “sub2” of subtask “sub” of top-level task “top” is “top.sub.sub2”.

getName() str

Get the name of the task.

Returns:
taskNamestr

Name of the task.

See also

getFullName

Get the full name of the task.

getSkySourceFootprints(mergedList, skyInfo, seed)

Return a list of Footprints of sky objects which don’t overlap with anything in mergedList.

Parameters:
mergedListlsst.afw.table.SourceCatalog

The merged Footprints from all the input bands.

skyInfolsst.pipe.base.Struct

A description of the patch.

seedint

Seed for the random number generator.

getTaskDict() dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]]

Get a dictionary of all tasks as a shallow copy.

Returns:
taskDictdict

Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

classmethod makeField(doc: str) ConfigurableField

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:
docstr

Help text for the field.

Returns:
configurableFieldlsst.pex.config.ConfigurableField

A ConfigurableField for this task.

Examples

Provides a convenient way to specify this task is a subtask of another task.

Here is an example of use:

class OtherTaskConfig(lsst.pex.config.Config):
    aSubtask = ATaskClass.makeField("brief description of task")
makeSubtask(name: str, **keyArgs: Any) None

Create a subtask as a new instance as the name attribute of this task.

Parameters:
namestr

Brief name of the subtask.

**keyArgs

Extra keyword arguments used to construct the task. The following arguments are automatically provided and cannot be overridden:

  • config.

  • parentTask.

Notes

The subtask must be defined by Task.config.name, an instance of ConfigurableField or RegistryField.

run(catalogs, skyInfo, idFactory, skySeed)

Merge multiple catalogs.

After ordering the catalogs and filters in priority order, getMergedSourceCatalog of the FootprintMergeList created by __init__ is used to perform the actual merging. Finally, cullPeaks is used to remove garbage peaks detected around bright objects.

Parameters:
catalogslsst.afw.table.SourceCatalog

Catalogs to be merged.

mergedListlsst.afw.table.SourceCatalog

Merged catalogs.

Returns:
resultlsst.pipe.base.Struct

Results as a struct with attributes:

outputCatalog

Merged catalogs (lsst.afw.table.SourceCatalog).

runQuantum(butlerQC, inputRefs, outputRefs)

Do butler IO and transform to provide in memory objects for tasks run method.

Parameters:
butlerQCQuantumContext

A butler which is specialized to operate in the context of a lsst.daf.butler.Quantum.

inputRefsInputQuantizedConnection

Datastructure whose attribute names are the names that identify connections defined in corresponding PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined input/prerequisite connections.

outputRefsOutputQuantizedConnection

Datastructure whose attribute names are the names that identify connections defined in corresponding PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined output connections.

timer(name: str, logLevel: int = 10) Iterator[None]

Context manager to log performance data for an arbitrary block of code.

Parameters:
namestr

Name of code being timed; data will be logged using item name: Start and End.

logLevelint

A logging level constant.

See also

lsst.utils.timer.logInfo

Implementation function.

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time