MergeMeasurementsTask

class lsst.pipe.tasks.mergeMeasurements.MergeMeasurementsTask(butler=None, schema=None, initInputs=None, **kwargs)

Bases: PipelineTask

Merge measurements from multiple bands.

Combines consistent (i.e. with the same peaks and footprints) catalogs of sources from multiple filter bands to construct a unified catalog that is suitable for driving forced photometry. Every source is required to have centroid, shape and flux measurements in each band.

MergeMeasurementsTask is meant to be run after deblending & measuring sources in every band. The purpose of the task is to generate a catalog of sources suitable for driving forced photometry in coadds and individual exposures.

Parameters:
butlerNone, optional

Compatibility parameter. Should always be None.

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 inputSchema containing the input schema. If present will override the value of schema.

**kwargs

Additional keyword arguments.

Attributes Summary

canMultiprocess

inputDataset

outputDataset

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.

getResourceConfig()

Return resource configuration for this 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(catalogs)

Merge measurement catalogs to create a single reference catalog for forced photometry.

runQuantum(butlerQC, inputRefs, outputRefs)

Method to do butler IO and or transforms 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
inputDataset = 'meas'
outputDataset = 'ref'

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
getResourceConfig() ResourceConfig | None

Return resource configuration for this task.

Returns:
Object of type ResourceConfig or None if resource
configuration is not defined for this task.
getTaskDict() Dict[str, ReferenceType[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)

Merge measurement catalogs to create a single reference catalog for forced photometry.

Parameters:
catalogslsst.afw.table.SourceCatalog

Catalogs to be merged.

Raises:
ValueError

Raised if no catalog records were found; if there is no valid reference for the input record ID; or if there is a mismatch between catalog sizes.

Notes

For parent sources, we choose the first band in config.priorityList for which the merge_footprint flag for that band is is True.

For child sources, the logic is the same, except that we use the merge_peak flags.

runQuantum(butlerQC, inputRefs, outputRefs)

Method to do butler IO and or transforms to provide in memory objects for tasks run method

Parameters:
butlerQCButlerQuantumContext

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.

logLevel

A logging level constant.

See also

timer.logInfo

Examples

Creating a timer context:

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