DetectAndMeasureTask

class lsst.ip.diffim.DetectAndMeasureTask(**kwargs)

Bases: PipelineTask

Detect and measure sources on a difference image.

Attributes Summary

canMultiprocess

Methods Summary

addSkySources(diaSources, mask, seed[, subtask])

Add sources in empty regions of the difference image for measuring the background.

calculateMetrics(difference)

Add image QA metrics to the Task metadata.

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.

measureDiaSources(diaSources, science, ...)

Use (matched) template and science image to constrain dipole fitting.

measureForcedSources(diaSources, science, wcs)

Perform forced measurement of the diaSources on the science image.

processResults(science, matchedTemplate, ...)

Measure and process the results of source detection.

run(science, matchedTemplate, difference[, ...])

Detect and measure sources on a difference image.

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

addSkySources(diaSources, mask, seed, subtask=None)

Add sources in empty regions of the difference image for measuring the background.

Parameters:
diaSourceslsst.afw.table.SourceCatalog

The catalog of detected sources.

masklsst.afw.image.Mask

Mask plane for determining regions where Sky sources can be added.

seedint

Seed value to initialize the random number generator.

calculateMetrics(difference)

Add image QA metrics to the Task metadata.

Parameters:
differencelsst.afw.image.Exposure

The target image to calculate metrics for.

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.

measureDiaSources(diaSources, science, difference, matchedTemplate)

Use (matched) template and science image to constrain dipole fitting.

Parameters:
diaSourceslsst.afw.table.SourceCatalog

The catalog of detected sources.

sciencelsst.afw.image.ExposureF

Science exposure that the template was subtracted from.

differencelsst.afw.image.ExposureF

Result of subtracting template from the science image.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template that was used produce the difference image.

measureForcedSources(diaSources, science, wcs)

Perform forced measurement of the diaSources on the science image.

Parameters:
diaSourceslsst.afw.table.SourceCatalog

The catalog of detected sources.

sciencelsst.afw.image.ExposureF

Science exposure that the template was subtracted from.

wcslsst.afw.geom.SkyWcs

Coordinate system definition (wcs) for the exposure.

processResults(science, matchedTemplate, difference, sources, idFactory, positiveFootprints=None, negativeFootprints=None)

Measure and process the results of source detection.

Parameters:
sciencelsst.afw.image.ExposureF

Science exposure that the template was subtracted from.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template that was used produce the difference image.

differencelsst.afw.image.ExposureF

Result of subtracting template from the science image.

sourceslsst.afw.table.SourceCatalog

Detected sources on the difference exposure.

idFactorylsst.afw.table.IdFactory

Generator object used to assign ids to detected sources in the difference image.

positiveFootprintslsst.afw.detection.FootprintSet, optional

Positive polarity footprints.

negativeFootprintslsst.afw.detection.FootprintSet, optional

Negative polarity footprints.

Returns:
measurementResultslsst.pipe.base.Struct
subtractedMeasuredExposurelsst.afw.image.ExposureF

Subtracted exposure with detection mask applied.

diaSourceslsst.afw.table.SourceCatalog

The catalog of detected sources.

run(science, matchedTemplate, difference, idFactory=None)

Detect and measure sources on a difference image.

The difference image will be convolved with a gaussian approximation of the PSF to form a maximum likelihood image for detection. Close positive and negative detections will optionally be merged into dipole diaSources. Sky sources, or forced detections in background regions, will optionally be added, and the configured measurement algorithm will be run on all detections.

Parameters:
sciencelsst.afw.image.ExposureF

Science exposure that the template was subtracted from.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template that was used produce the difference image.

differencelsst.afw.image.ExposureF

Result of subtracting template from the science image.

idFactorylsst.afw.table.IdFactory, optional

Generator object used to assign ids to detected sources in the difference image. Ids from this generator are not set until after deblending and merging positive/negative peaks.

Returns:
measurementResultslsst.pipe.base.Struct
subtractedMeasuredExposurelsst.afw.image.ExposureF

Subtracted exposure with detection mask applied.

diaSourceslsst.afw.table.SourceCatalog

The catalog of detected sources.

runQuantum(butlerQC: QuantumContext, inputRefs: InputQuantizedConnection, outputRefs: OutputQuantizedConnection)

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