MeasureMergedCoaddSourcesTask

class lsst.pipe.tasks.multiBand.MeasureMergedCoaddSourcesTask(schema=None, peakSchema=None, refObjLoader=None, initInputs=None, **kwargs)

Bases: PipelineTask

Deblend sources from main catalog in each coadd seperately and measure.

Use peaks and footprints from a master catalog to perform deblending and measurement in each coadd.

Given a master input catalog of sources (peaks and footprints) or deblender outputs(including a HeavyFootprint in each band), measure each source on the coadd. Repeating this procedure with the same master catalog across multiple coadds will generate a consistent set of child sources.

The deblender retains all peaks and deblends any missing peaks (dropouts in that band) as PSFs. Source properties are measured and the @c is-primary flag (indicating sources with no children) is set. Visit flags are propagated to the coadd sources.

Optionally, we can match the coadd sources to an external reference catalog.

After MeasureMergedCoaddSourcesTask has been run on multiple coadds, we have a set of per-band catalogs. The next stage in the multi-band processing procedure will merge these measurements into a suitable catalog for driving forced photometry.

Parameters:
schema``lsst.afw.table.Schema`, optional

The schema of the merged detection catalog used as input to this one.

peakSchema``lsst.afw.table.Schema`, optional

The schema of the PeakRecords in the Footprints in the merged detection catalog.

refObjLoaderlsst.meas.algorithms.ReferenceObjectLoader, optional

An instance of ReferenceObjectLoader that supplies an external reference catalog. May be None if the loader can be constructed from the butler argument or all steps requiring a reference catalog are disabled.

initInputsdict, optional

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

**kwargs

Additional keyword arguments.

Attributes Summary

canMultiprocess

Methods Summary

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.

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(exposure, sources, skyInfo, exposureId)

Run measurement algorithms on the input exposure, and optionally populate the resulting catalog with extra information.

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

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.

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(exposure, sources, skyInfo, exposureId, ccdInputs=None, sourceTableHandleDict=None, finalizedSourceTableHandleDict=None, finalVisitSummaryHandleDict=None, apCorrMap=None)

Run measurement algorithms on the input exposure, and optionally populate the resulting catalog with extra information.

Parameters:
exposurelsst.afw.exposure.Exposure

The input exposure on which measurements are to be performed.

sourceslsst.afw.table.SourceCatalog

A catalog built from the results of merged detections, or deblender outputs.

skyInfolsst.pipe.base.Struct

A struct containing information about the position of the input exposure within a SkyMap, the SkyMap, its Wcs, and its bounding box.

exposureIdint or bytes

Packed unique number or bytes unique to the input exposure.

ccdInputslsst.afw.table.ExposureCatalog, optional

Catalog containing information on the individual visits which went into making the coadd.

sourceTableHandleDictdict [int, lsst.daf.butler.DeferredDatasetHandle], optional

Dict for sourceTable_visit handles (key is visit) for propagating flags. These tables contain astrometry and photometry flags, and optionally PSF flags.

finalizedSourceTableHandleDictdict [int, lsst.daf.butler.DeferredDatasetHandle], optional

Dict for finalized_src_table handles (key is visit) for propagating flags. These tables contain PSF flags from the finalized PSF estimation.

finalVisitSummaryHandleDictdict [int, lsst.daf.butler.DeferredDatasetHandle], optional

Dict for visit_summary handles (key is visit) for visit-level information. These tables contain the WCS information of the single-visit input images.

apCorrMaplsst.afw.image.ApCorrMap, optional

Aperture correction map attached to the exposure. If None, it will be read from the exposure.

Returns:
resultslsst.pipe.base.Struct

Results of running measurement task. Will contain the catalog in the sources attribute. Optionally will have results of matching to a reference catalog in the matchResults attribute, and denormalized matches in the denormMatches attribute.

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