ZogyImagePsfMatchTask

class lsst.ip.diffim.ZogyImagePsfMatchTask(*args, **kwargs)

Bases: lsst.ip.diffim.ImagePsfMatchTask

Task to perform Zogy PSF matching and image subtraction.

This class inherits from ImagePsfMatchTask to contain the _warper subtask and related methods.

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(templateExposure, …[, …]) 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.
matchExposures(templateExposure, scienceExposure) Warp and PSF-match an exposure to the reference.
matchMaskedImages(templateMaskedImage, …) PSF-match a MaskedImage (templateMaskedImage) to a reference MaskedImage (scienceMaskedImage).
run(scienceExposure, templateExposure[, …]) Register, PSF-match, and subtract two Exposures, scienceExposure - templateExposure using the ZOGY algorithm.
subtractExposures(templateExposure, …) Register, Psf-match and subtract two Exposures.
subtractMaskedImages(templateExposure, …) Psf-match and subtract two MaskedImages.
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() → lsst.pipe.base._task_metadata.TaskMetadata

Get metadata for all tasks.

Returns:
metadata : TaskMetadata

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:
fullName : str

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:
taskName : str

Name of the task.

See also

getFullName
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:
exposure : lsst.afw.image.Exposure

Exposure on which to run detection/measurement

sigma : float

Detection threshold

doSmooth : bool

Whether or not to smooth the Exposure with Psf before detection

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:
taskDict : dict

Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

makeCandidateList(templateExposure, scienceExposure, kernelSize, candidateList=None)

Make a list of acceptable KernelCandidates.

Accept or generate a list of candidate sources for Psf-matching, and examine the Mask planes in both of the images for indications of bad pixels

Parameters:
templateExposure : lsst.afw.image.Exposure

Exposure that will be convolved

scienceExposure : lsst.afw.image.Exposure

Exposure that will be matched-to

kernelSize : float

Dimensions of the Psf-matching Kernel, used to grow detection footprints

candidateList : list, optional

List of Sources to examine. Elements must be of type afw.table.Source or a type that wraps a Source and has a getSource() method, such as meas.algorithms.PsfCandidateF.

Returns:
candidateList : list of dict

A list of dicts having a “source” and “footprint” field for the Sources deemed to be appropriate for Psf matching

classmethod makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:
doc : str

Help text for the field.

Returns:
configurableField : lsst.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:
targetFwhmPix : float, optional

Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.

referenceFwhmPix : float, optional

Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.

basisDegGauss : list of int, optional

Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.

basisSigmaGauss : list of int, optional

Passed on to lsst.ip.diffim.generateAlardLuptonBasisList. Not used for delta function basis sets.

metadata : lsst.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) → None

Create a subtask as a new instance as the name attribute of this task.

Parameters:
name : str

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.

matchExposures(templateExposure, scienceExposure, templateFwhmPix=None, scienceFwhmPix=None, candidateList=None, doWarping=True, convolveTemplate=True)

Warp and PSF-match an exposure to the reference.

Do the following, in order:

  • Warp templateExposure to match scienceExposure,
    if doWarping True and their WCSs do not already match
  • Determine a PSF matching kernel and differential background model
    that matches templateExposure to scienceExposure
  • Convolve templateExposure by PSF matching kernel
Parameters:
templateExposure : lsst.afw.image.Exposure

Exposure to warp and PSF-match to the reference masked image

scienceExposure : lsst.afw.image.Exposure

Exposure whose WCS and PSF are to be matched to

templateFwhmPix : float

FWHM (in pixels) of the Psf in the template image (image to convolve)

scienceFwhmPix : float

FWHM (in pixels) of the Psf in the science image

candidateList : list, optional

a list of footprints/maskedImages for kernel candidates; if None then source detection is run.

  • Currently supported: list of Footprints or measAlg.PsfCandidateF
doWarping : bool

what to do if templateExposure and scienceExposure WCSs do not match:

  • if True then warp templateExposure to match scienceExposure
  • if False then raise an Exception
convolveTemplate : bool

Whether to convolve the template image or the science image:

  • if True, templateExposure is warped if doWarping, templateExposure is convolved
  • if False, templateExposure is warped if doWarping, scienceExposure is convolved
Returns:
results : lsst.pipe.base.Struct

An lsst.pipe.base.Struct containing these fields:

  • matchedImage : the PSF-matched exposure =
    Warped templateExposure convolved by psfMatchingKernel. This has:
    • the same parent bbox, Wcs and PhotoCalib as scienceExposure
    • the same filter as templateExposure
    • no Psf (because the PSF-matching process does not compute one)
  • psfMatchingKernel : the PSF matching kernel
  • backgroundModel : differential background model
  • kernelCellSet : SpatialCellSet used to solve for the PSF matching kernel
Raises:
RuntimeError

Raised if doWarping is False and templateExposure and scienceExposure WCSs do not match

matchMaskedImages(templateMaskedImage, scienceMaskedImage, candidateList, templateFwhmPix=None, scienceFwhmPix=None)

PSF-match a MaskedImage (templateMaskedImage) to a reference MaskedImage (scienceMaskedImage).

Do the following, in order:

  • Determine a PSF matching kernel and differential background model
    that matches templateMaskedImage to scienceMaskedImage
  • Convolve templateMaskedImage by the PSF matching kernel
Parameters:
templateMaskedImage : lsst.afw.image.MaskedImage

masked image to PSF-match to the reference masked image; must be warped to match the reference masked image

scienceMaskedImage : lsst.afw.image.MaskedImage

maskedImage whose PSF is to be matched to

templateFwhmPix : float

FWHM (in pixels) of the Psf in the template image (image to convolve)

scienceFwhmPix : float

FWHM (in pixels) of the Psf in the science image

candidateList : list, optional

A list of footprints/maskedImages for kernel candidates; if None then source detection is run.

  • Currently supported: list of Footprints or measAlg.PsfCandidateF
Returns:
result : callable
An lsst.pipe.base.Struct containing these fields:
  • psfMatchedMaskedImage: the PSF-matched masked image =
    templateMaskedImage convolved with psfMatchingKernel. This has the same xy0, dimensions and wcs as scienceMaskedImage.
  • psfMatchingKernel: the PSF matching kernel
  • backgroundModel: differential background model
  • kernelCellSet: SpatialCellSet used to solve for the PSF matching kernel
Raises:
RuntimeError

Raised if input images have different dimensions

run(scienceExposure, templateExposure, doWarping=True)

Register, PSF-match, and subtract two Exposures, scienceExposure - templateExposure using the ZOGY algorithm.

Parameters:
templateExposure : lsst.afw.image.Exposure

exposure to be warped to scienceExposure.

scienceExposure : lsst.afw.image.Exposure

reference Exposure.

doWarping : bool

what to do if templateExposure’s and scienceExposure’s WCSs do not match: - if True then warp templateExposure to match scienceExposure - if False then raise an Exception

Returns:
results : lsst.pipe.base.Struct containing these fields:
  • subtractedExposure: lsst.afw.image.Exposure
    The subtraction result.
  • warpedExposure: lsst.afw.image.Exposure or None
    templateExposure after warping to match scienceExposure

Notes

Do the following, in order:
  • Warp templateExposure to match scienceExposure, if their WCSs do not already match
  • Compute subtracted exposure ZOGY image subtraction algorithm on the two exposures

This is the new entry point of the task as of DM-25115.

subtractExposures(templateExposure, scienceExposure, *args)

Register, Psf-match and subtract two Exposures.

Do the following, in order:

  • Warp templateExposure to match scienceExposure, if their WCSs do not already match
  • Determine a PSF matching kernel and differential background model
    that matches templateExposure to scienceExposure
  • PSF-match templateExposure to scienceExposure
  • Compute subtracted exposure (see return values for equation).
Parameters:
templateExposure : lsst.afw.image.ExposureF

Exposure to PSF-match to scienceExposure

scienceExposure : lsst.afw.image.ExposureF

Reference Exposure

templateFwhmPix : float

FWHM (in pixels) of the Psf in the template image (image to convolve)

scienceFwhmPix : float

FWHM (in pixels) of the Psf in the science image

candidateList : list, optional

A list of footprints/maskedImages for kernel candidates; if None then source detection is run.

  • Currently supported: list of Footprints or measAlg.PsfCandidateF
doWarping : bool

What to do if templateExposure` and scienceExposure WCSs do not match:

  • if True then warp templateExposure to match scienceExposure
  • if False then raise an Exception
convolveTemplate : bool

Convolve the template image or the science image

  • if True, templateExposure is warped if doWarping, templateExposure is convolved
  • if False, templateExposure is warped if doWarping, scienceExposure is convolved
Returns:
result : lsst.pipe.base.Struct

An lsst.pipe.base.Struct containing these fields:

  • subtractedExposure : subtracted Exposure

    scienceExposure - (matchedImage + backgroundModel)

  • matchedImage : templateExposure after warping to match

    templateExposure (if doWarping true), and convolving with psfMatchingKernel

  • psfMatchingKernel : PSF matching kernel

  • backgroundModel : differential background model

  • kernelCellSet : SpatialCellSet used to determine PSF matching kernel

subtractMaskedImages(templateExposure, scienceExposure, *args)

Psf-match and subtract two MaskedImages.

Do the following, in order:

  • PSF-match templateMaskedImage to scienceMaskedImage
  • Determine the differential background
  • Return the difference: scienceMaskedImage
    ((warped templateMaskedImage convolved with psfMatchingKernel) + backgroundModel)
Parameters:
templateMaskedImage : lsst.afw.image.MaskedImage

MaskedImage to PSF-match to scienceMaskedImage

scienceMaskedImage : lsst.afw.image.MaskedImage

Reference MaskedImage

templateFwhmPix : float

FWHM (in pixels) of the Psf in the template image (image to convolve)

scienceFwhmPix : float

FWHM (in pixels) of the Psf in the science image

candidateList : list, optional

A list of footprints/maskedImages for kernel candidates; if None then source detection is run.

  • Currently supported: list of Footprints or measAlg.PsfCandidateF
Returns:
results : lsst.pipe.base.Struct

An lsst.pipe.base.Struct containing these fields:

  • subtractedMaskedImage : scienceMaskedImage - (matchedImage + backgroundModel)
  • matchedImage : templateMaskedImage convolved with psfMatchingKernel
  • psfMatchingKernel` : PSF matching kernel
  • backgroundModel : differential background model
  • kernelCellSet : SpatialCellSet used to determine PSF matching kernel
timer(name: str, logLevel: int = 10) → Iterator[None]

Context manager to log performance data for an arbitrary block of code.

Parameters:
name : str

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