DecorrelateALKernelSpatialTask

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

Bases: lsst.pipe.base.Task

! @anchor DecorrelateALKernelSpatialTask

@brief Decorrelate the effect of convolution by Alard-Lupton matching kernel in image difference

@section ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Contents Contents

• @ref ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Purpose
• @ref ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Config
• @ref ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Run
• @ref ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Debug
• @ref ip_diffim_imDecorr_DecorrALKerSpatTask_Example

@section ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Purpose Description

Pipe-task that removes the neighboring-pixel covariance in an image difference that are added when the template image is convolved with the Alard-Lupton PSF matching kernel.

This task is a simple wrapper around @ref DecorrelateALKernelTask, which takes a spatiallyVarying parameter in its run method. If it is False, then it simply calls the run method of @ref DecorrelateALKernelTask. If it is True, then it uses the @ref ImageMapReduceTask framework to break the exposures into subExposures on a grid, and performs the run method of @ref DecorrelateALKernelTask on each subExposure. This enables it to account for spatially-varying PSFs and noise in the exposures when performing the decorrelation.

@section ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Initialize Task initialization

@copydoc __init__

@section ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Run Invoking the Task

@copydoc run

@section ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Config Configuration parameters

See @ref DecorrelateALKernelSpatialConfig

@section ip_diffim_imageDecorrelation_DecorrelateALKernelSpatialTask_Debug Debug variables

This task has no debug variables

@section ip_diffim_imDecorr_DecorrALKerSpatTask_Example Example of using DecorrelateALKernelSpatialTask

This task has no standalone example, however it is applied as a subtask of pipe.tasks.imageDifference.ImageDifferenceTask. There is also an example of its use in tests/testImageDecorrelation.py.

Methods Summary

computeVarianceMean(exposure)	Compute the mean of the variance plane of exposure.
run(scienceExposure, templateExposure, …)	! Perform decorrelation of an image difference exposure.

Methods Documentation

computeVarianceMean(exposure)

Compute the mean of the variance plane of exposure.

run(scienceExposure, templateExposure, subtractedExposure, psfMatchingKernel, spatiallyVarying=True, preConvKernel=None)

! Perform decorrelation of an image difference exposure.

Decorrelates the diffim due to the convolution of the templateExposure with the A&L psfMatchingKernel. If spatiallyVarying is True, it utilizes the spatially varying matching kernel via the imageMapReduce framework to perform spatially-varying decorrelation on a grid of subExposures.

Parameters:

scienceExposure : lsst.afw.image.Exposure

the science Exposure used for PSF matching

templateExposure : lsst.afw.image.Exposure

the template Exposure used for PSF matching

subtractedExposure : lsst.afw.image.Exposure

the subtracted Exposure produced by ip_diffim.ImagePsfMatchTask.subtractExposures()

psfMatchingKernel :

an (optionally spatially-varying) PSF matching kernel produced by ip_diffim.ImagePsfMatchTask.subtractExposures()

spatiallyVarying : bool

if True, perform the spatially-varying operation

preConvKernel : lsst.meas.algorithms.Psf

if not none, the scienceExposure has been pre-filtered with this kernel. (Currently this option is experimental.)

Returns:

a `pipeBase.Struct` containing:

• correctedExposure: the decorrelated diffim