MakeKernelTask¶

class lsst.ip.diffim.MakeKernelTask(*args, **kwargs)¶

Bases: PsfMatchTask

Construct a kernel for PSF matching two exposures.

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.
`getSelectSources`(exposure[, sigma, ...])	Get sources to use for Psf-matching.
`getTaskDict`()	Get a dictionary of all tasks as a shallow copy.
`makeCandidateList`(convolved, reference, ...)	Make a list of acceptable KernelCandidates.
`makeField`(doc)	Make a `lsst.pex.config.ConfigurableField` for this task.
`makeKernelBasisList`([targetFwhmPix, ...])	Wrapper to set log messages for `lsst.ip.diffim.makeKernelBasisList`.
`makeSubtask`(name, **keyArgs)	Create a subtask as a new instance as the `name` attribute of this task.
`run`(template, science, kernelSources[, ...])	Solve for the kernel and background model that best match two Exposures evaluated at the given source locations.
`selectKernelSources`(template, science[, ...])	Select sources from a list of candidates, and extract footprints.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.

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.

getSelectSources(exposure, sigma=None, doSmooth=True, idFactory=None)¶

Get sources to use for Psf-matching.

This method runs detection and measurement on an exposure. The returned set of sources will be used as candidates for Psf-matching.

Parameters:

exposurelsst.afw.image.Exposure: Exposure on which to run detection/measurement
sigmafloat, optional: PSF sigma, in pixels, used for smoothing the image for detection. If None, the PSF width will be used.
doSmoothbool: Whether or not to smooth the Exposure with Psf before detection
idFactorylsst.afw.table.IdFactory: Factory for the generation of Source ids

Returns:

selectSources: source catalog containing candidates for the Psf-matching

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.

makeCandidateList(convolved, reference, kernelSize, candidateList, preconvolved=False, sigma=None)¶

Make a list of acceptable KernelCandidates.

Generate a list of candidate sources for Psf-matching, remove sources with bad pixel masks set or that extend off the image.

Parameters:

convolvedlsst.afw.image.Exposure: Exposure that will be convolved. This is typically the template image, and may have a large bbox than the reference exposure.
referencelsst.afw.image.Exposure: Exposure that will be matched-to. This is typically the science image.
kernelSizefloat: Dimensions of the Psf-matching Kernel, used to set detection footprints.
candidateListlsst.afw.table.SourceCatalog: List of Sources to examine for kernel candidacy.
preconvolvedbool, optional: Was the science exposure already convolved with its PSF?

Returns:

candidateslsst.afw.table.SourceCatalog: Candidates with footprints extended to a kernelSize box.

Raises:

RuntimeError: If candidateList is empty after sub-selection.

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")

makeKernelBasisList(targetFwhmPix=None, referenceFwhmPix=None, basisDegGauss=None, basisSigmaGauss=None, metadata=None)¶

Wrapper to set log messages for lsst.ip.diffim.makeKernelBasisList.

Parameters:

targetFwhmPixfloat, optional: Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.
referenceFwhmPixfloat, optional: Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.
basisDegGausslist of int, optional: Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.
basisSigmaGausslist of int, optional: Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.
metadatalsst.daf.base.PropertySet, optional: Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.

Returns:

basisList: list of lsst.afw.math.kernel.FixedKernel: List of basis kernels.

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, kernelSources, preconvolved=False)¶

Solve for the kernel and background model that best match two Exposures evaluated at the given source locations.

Parameters:

templatelsst.afw.image.Exposure: Exposure that will be convolved.
sciencelsst.afw.image.Exposure: The exposure that will be matched.
kernelSourceslsst.afw.table.SourceCatalog: Kernel candidate sources with appropriately sized footprints. Typically the output of MakeKernelTask.selectKernelSources.
preconvolvedbool, optional: Was the science image convolved with its own PSF?

Returns:

resultslsst.pipe.base.Struct

psfMatchingKernellsst.afw.math.LinearCombinationKernel: Spatially varying Psf-matching kernel.
backgroundModellsst.afw.math.Function2D: Spatially varying background-matching function.

selectKernelSources(template, science, candidateList=None, preconvolved=False)¶

Select sources from a list of candidates, and extract footprints.

Parameters:

templatelsst.afw.image.Exposure: Exposure that will be convolved.
sciencelsst.afw.image.Exposure: The exposure that will be matched.
candidateListlsst.afw.table.SourceCatalog: Sources to check as possible kernel candidates.
preconvolvedbool, optional: Was the science image convolved with its own PSF?

Returns:

kernelSourceslsst.afw.table.SourceCatalog: Kernel candidates with appropriate sized footprints.

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.

Navigation

MakeKernelTask¶