AlardLuptonSubtractTask

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

Bases: PipelineTask

Compute the image difference of a science and template image using the Alard & Lupton (1998) algorithm.

Attributes Summary

canMultiprocess

Methods Summary

emptyMetadata()

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

finalize(template, science, difference, kernel)

Decorrelate the difference image to undo the noise correlations caused by convolution.

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(template, science, sources[, ...])

PSF match, subtract, and decorrelate two images.

runConvolveScience(template, science, ...)

Convolve the science image with a PSF-matching kernel and subtract the template image.

runConvolveTemplate(template, science, ...)

Convolve the template image with a PSF-matching kernel and subtract from the science 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.

updateMasks(template, science)

Update the science and template mask planes before differencing.

Attributes Documentation

canMultiprocess: ClassVar[bool] = True

Methods Documentation

emptyMetadata() None

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

finalize(template, science, difference, kernel, templateMatched=True, preConvMode=False, preConvKernel=None, spatiallyVarying=False)

Decorrelate the difference image to undo the noise correlations caused by convolution.

Parameters:
templatelsst.afw.image.ExposureF

Template exposure, warped to match the science exposure.

sciencelsst.afw.image.ExposureF

Science exposure to subtract from the template.

differencelsst.afw.image.ExposureF

Result of subtracting template and science.

kernellsst.afw.math.Kernel

An (optionally spatially-varying) PSF matching kernel

templateMatchedbool, optional

Was the template PSF-matched to the science image?

preConvModebool, optional

Was the science image preconvolved with its own PSF before PSF matching the template?

preConvKernellsst.afw.detection.Psf, optional

If not None, then the science image was pre-convolved with (the reflection of) this kernel. Must be normalized to sum to 1.

spatiallyVaryingbool, optional

Compute the decorrelation kernel spatially varying across the image?

Returns:
correctedExposurelsst.afw.image.ExposureF

The decorrelated image difference.

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(template, science, sources, finalizedPsfApCorrCatalog=None, visitSummary=None)

PSF match, subtract, and decorrelate two images.

Parameters:
templatelsst.afw.image.ExposureF

Template exposure, warped to match the science exposure.

sciencelsst.afw.image.ExposureF

Science exposure to subtract from the template.

sourceslsst.afw.table.SourceCatalog

Identified sources on the science exposure. This catalog is used to select sources in order to perform the AL PSF matching on stamp images around them.

finalizedPsfApCorrCataloglsst.afw.table.ExposureCatalog, optional

Exposure catalog with finalized psf models and aperture correction maps to be applied. Catalog uses the detector id for the catalog id, sorted on id for fast lookup. Deprecated in favor of visitSummary, and will be removed after v26.

visitSummarylsst.afw.table.ExposureCatalog, optional

Exposure catalog with external calibrations to be applied. Catalog uses the detector id for the catalog id, sorted on id for fast lookup. Ignored (for temporary backwards compatibility) if finalizedPsfApCorrCatalog is provided.

Returns:
resultslsst.pipe.base.Struct
differencelsst.afw.image.ExposureF

Result of subtracting template and science.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template exposure.

backgroundModellsst.afw.math.Function2D

Background model that was fit while solving for the PSF-matching kernel

psfMatchingKernellsst.afw.math.Kernel

Kernel used to PSF-match the convolved image.

Raises:
RuntimeError

If an unsupported convolution mode is supplied.

RuntimeError

If there are too few sources to calculate the PSF matching kernel.

lsst.pipe.base.NoWorkFound

Raised if fraction of good pixels, defined as not having NO_DATA set, is less then the configured requiredTemplateFraction

runConvolveScience(template, science, selectSources)

Convolve the science image with a PSF-matching kernel and subtract the template image.

Parameters:
templatelsst.afw.image.ExposureF

Template exposure, warped to match the science exposure.

sciencelsst.afw.image.ExposureF

Science exposure to subtract from the template.

selectSourceslsst.afw.table.SourceCatalog

Identified sources on the science exposure. This catalog is used to select sources in order to perform the AL PSF matching on stamp images around them.

Returns:
resultslsst.pipe.base.Struct
differencelsst.afw.image.ExposureF

Result of subtracting template and science.

matchedTemplatelsst.afw.image.ExposureF

Warped template exposure. Note that in this case, the template is not PSF-matched to the science image.

backgroundModellsst.afw.math.Function2D

Background model that was fit while solving for the PSF-matching kernel

psfMatchingKernellsst.afw.math.Kernel

Kernel used to PSF-match the science image to the template.

runConvolveTemplate(template, science, selectSources)

Convolve the template image with a PSF-matching kernel and subtract from the science image.

Parameters:
templatelsst.afw.image.ExposureF

Template exposure, warped to match the science exposure.

sciencelsst.afw.image.ExposureF

Science exposure to subtract from the template.

selectSourceslsst.afw.table.SourceCatalog

Identified sources on the science exposure. This catalog is used to select sources in order to perform the AL PSF matching on stamp images around them.

Returns:
resultslsst.pipe.base.Struct
differencelsst.afw.image.ExposureF

Result of subtracting template and science.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template exposure.

backgroundModellsst.afw.math.Function2D

Background model that was fit while solving for the PSF-matching kernel

psfMatchingKernellsst.afw.math.Kernel

Kernel used to PSF-match the template to the science image.

runQuantum(butlerQC: QuantumContext, inputRefs: InputQuantizedConnection, outputRefs: OutputQuantizedConnection) None

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
updateMasks(template, science)

Update the science and template mask planes before differencing.

Parameters:
templatelsst.afw.image.Exposure

Template exposure, warped to match the science exposure. The template mask planes will be erased, except for a few specified in the task config.

sciencelsst.afw.image.Exposure

Science exposure to subtract from the template. The DETECTED and DETECTED_NEGATIVE mask planes of the science image will be erased.