Inheritance diagram for lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper:

Public Member Functions
	__init__ (self, args, *kwargs)

	run (self, subExposure, expandedSubExposure, fullBBox, template, science, alTaskResult=None, psfMatchingKernel=None, preConvKernel=None, **kwargs)

Static Public Attributes
	ConfigClass = DecorrelateALKernelConfig

Static Protected Attributes
str	_DefaultName = 'ip_diffim_decorrelateALKernelMapper'

Detailed Description

Task to be used as an ImageMapper for performing
A&L decorrelation on subimages on a grid across a A&L difference image.

This task subclasses DecorrelateALKernelTask in order to implement
all of that task's configuration parameters, as well as its `run` method.

Definition at line 649 of file imageDecorrelation.py.

Constructor & Destructor Documentation

◆ init()

lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper.__init__	(		self,
		*	args,
		**	kwargs )

Create the image decorrelation Task

Parameters
----------
args :
    arguments to be passed to ``lsst.pipe.base.task.Task.__init__``
kwargs :
    keyword arguments to be passed to ``lsst.pipe.base.task.Task.__init__``

Reimplemented from lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask.

Definition at line 660 of file imageDecorrelation.py.

    def __init__(self, *args, **kwargs):
        DecorrelateALKernelTask.__init__(self, *args, **kwargs)
 

Member Function Documentation

◆ run()

lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper.run	(		self,
			subExposure,
			expandedSubExposure,
			fullBBox,
			template,
			science,
			alTaskResult = None,
			psfMatchingKernel = None,
			preConvKernel = None,
		**	kwargs )

Perform decorrelation operation on `subExposure`, using
`expandedSubExposure` to allow for invalid edge pixels arising from
convolutions.

This method performs A&L decorrelation on `subExposure` using
local measures for image variances and PSF. `subExposure` is a
sub-exposure of the non-decorrelated A&L diffim. It also
requires the corresponding sub-exposures of the template
(`template`) and science (`science`) exposures.

Parameters
----------
subExposure : `lsst.afw.image.Exposure`
    the sub-exposure of the diffim
expandedSubExposure : `lsst.afw.image.Exposure`
    the expanded sub-exposure upon which to operate
fullBBox : `lsst.geom.Box2I`
    the bounding box of the original exposure
template : `lsst.afw.image.Exposure`
    the corresponding sub-exposure of the template exposure
science : `lsst.afw.image.Exposure`
    the corresponding sub-exposure of the science exposure
alTaskResult : `lsst.pipe.base.Struct`
    the result of A&L image differencing on `science` and
    `template`, importantly containing the resulting
    `psfMatchingKernel`. Can be `None`, only if
    `psfMatchingKernel` is not `None`.
psfMatchingKernel : Alternative parameter for passing the
    A&L `psfMatchingKernel` directly.
preConvKernel : If not None, then pre-filtering was applied
    to science exposure, and this is the pre-convolution
    kernel.
kwargs :
    additional keyword arguments propagated from
    `ImageMapReduceTask.run`.

Returns
-------
A `pipeBase.Struct` containing:

    - ``subExposure`` : the result of the `subExposure` processing.
    - ``decorrelationKernel`` : the decorrelation kernel, currently
        not used.

Notes
-----
This `run` method accepts parameters identical to those of
`ImageMapper.run`, since it is called from the
`ImageMapperTask`. See that class for more information.

Reimplemented from lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask.

Definition at line 663 of file imageDecorrelation.py.

            preConvKernel=None, **kwargs):
        """Perform decorrelation operation on `subExposure`, using
        `expandedSubExposure` to allow for invalid edge pixels arising from
        convolutions.
 
        This method performs A&L decorrelation on `subExposure` using
        local measures for image variances and PSF. `subExposure` is a
        sub-exposure of the non-decorrelated A&L diffim. It also
        requires the corresponding sub-exposures of the template
        (`template`) and science (`science`) exposures.
 
        Parameters
        ----------
        subExposure : `lsst.afw.image.Exposure`
            the sub-exposure of the diffim
        expandedSubExposure : `lsst.afw.image.Exposure`
            the expanded sub-exposure upon which to operate
        fullBBox : `lsst.geom.Box2I`
            the bounding box of the original exposure
        template : `lsst.afw.image.Exposure`
            the corresponding sub-exposure of the template exposure
        science : `lsst.afw.image.Exposure`
            the corresponding sub-exposure of the science exposure
        alTaskResult : `lsst.pipe.base.Struct`
            the result of A&L image differencing on `science` and
            `template`, importantly containing the resulting
            `psfMatchingKernel`. Can be `None`, only if
            `psfMatchingKernel` is not `None`.
        psfMatchingKernel : Alternative parameter for passing the
            A&L `psfMatchingKernel` directly.
        preConvKernel : If not None, then pre-filtering was applied
            to science exposure, and this is the pre-convolution
            kernel.
        kwargs :
            additional keyword arguments propagated from
            `ImageMapReduceTask.run`.
 
        Returns
        -------
        A `pipeBase.Struct` containing:
 
            - ``subExposure`` : the result of the `subExposure` processing.
            - ``decorrelationKernel`` : the decorrelation kernel, currently
                not used.
 
        Notes
        -----
        This `run` method accepts parameters identical to those of
        `ImageMapper.run`, since it is called from the
        `ImageMapperTask`. See that class for more information.
        """
        templateExposure = template  # input template
        scienceExposure = science  # input science image
        if alTaskResult is None and psfMatchingKernel is None:
            raise RuntimeError('Both alTaskResult and psfMatchingKernel cannot be None')
        psfMatchingKernel = alTaskResult.psfMatchingKernel if alTaskResult is not None else psfMatchingKernel
 
        # subExp and expandedSubExp are subimages of the (un-decorrelated) diffim!
        # So here we compute corresponding subimages of templateExposure and scienceExposure
        subExp2 = scienceExposure.Factory(scienceExposure, expandedSubExposure.getBBox())
        subExp1 = templateExposure.Factory(templateExposure, expandedSubExposure.getBBox())
 
        # Prevent too much log INFO verbosity from DecorrelateALKernelTask.run
        logLevel = self.log.level
        self.log.setLevel(self.log.WARNING)
        res = DecorrelateALKernelTask.run(self, subExp2, subExp1, expandedSubExposure,
                                          psfMatchingKernel, preConvKernel, **kwargs)
        self.log.setLevel(logLevel)  # reset the log level
 
        diffim = res.correctedExposure.Factory(res.correctedExposure, subExposure.getBBox())
        out = pipeBase.Struct(subExposure=diffim, )
        return out
 
 

Member Data Documentation

◆ _DefaultName

str lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper._DefaultName = 'ip_diffim_decorrelateALKernelMapper'

staticprotected

Definition at line 658 of file imageDecorrelation.py.

◆ ConfigClass

lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelMapper.ConfigClass = DecorrelateALKernelConfig

static

Definition at line 657 of file imageDecorrelation.py.

The documentation for this class was generated from the following file:

/j/snowflake/release/lsstsw/stack/lsst-scipipe-8.0.0/Linux64/ip_diffim/g1470d8bcf6+6be6c9203b/python/lsst/ip/diffim/imageDecorrelation.py

Public Member Functions

Static Public Attributes

Static Protected Attributes