AlardLuptonPreconvolveSubtractTask

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

Bases: AlardLuptonSubtractTask

Subtract a template from a science image, convolving the science image before computing the kernel, and also convolving the template before subtraction.

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[, ...])

Preconvolve the science image with its own PSF, convolve the template image with a PSF-matching kernel and subtract from the preconvolved science image.

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.

runPreconvolve(template, science, ...)

Convolve the science image with its own PSF, then convolve the template with a matching kernel and subtract to form the Score exposure.

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, difference)

Update the mask planes on images for finalizing.

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)

Preconvolve the science image with its own PSF, convolve the template image with a PSF-matching kernel and subtract from the preconvolved science image.

Parameters:
templatelsst.afw.image.ExposureF

The template image, which has previously been warped to the science image. The template bbox will be padded by a few pixels compared to the science bbox.

sciencelsst.afw.image.ExposureF

The science exposure.

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 complete external calibrations. 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
scoreExposurelsst.afw.image.ExposureF

Result of subtracting the convolved template and science images. Attached PSF is that of the original science image.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template exposure. Attached PSF is that of the original science image.

matchedSciencelsst.afw.image.ExposureF

The science exposure after convolving with its own PSF. Attached PSF is that of the original science image.

backgroundModellsst.afw.math.Function2D

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

psfMatchingKernellsst.afw.math.Kernel

Final kernel used to PSF-match the template to the science image.

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.

runPreconvolve(template, science, matchedScience, selectSources, preConvKernel)

Convolve the science image with its own PSF, then convolve the template with a matching kernel and subtract to form the Score exposure.

Parameters:
templatelsst.afw.image.ExposureF

Template exposure, warped to match the science exposure.

sciencelsst.afw.image.ExposureF

Science exposure to subtract from the template.

matchedSciencelsst.afw.image.ExposureF

The science exposure, convolved with the reflection of its own PSF.

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.

preConvKernellsst.afw.math.Kernel

The reflection of the kernel that was used to preconvolve the science exposure. Must be normalized to sum to 1.

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

Result of subtracting the convolved template and science images. Attached PSF is that of the original science image.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template exposure. Attached PSF is that of the original science image.

matchedSciencelsst.afw.image.ExposureF

The science exposure after convolving with its own PSF. Attached PSF is that of the original science image.

backgroundModellsst.afw.math.Function2D

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

psfMatchingKernellsst.afw.math.Kernel

Final 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, difference)

Update the mask planes on images for finalizing.