LSST Applications
21.0.0-172-gfb10e10a+18fedfabac,22.0.0+297cba6710,22.0.0+80564b0ff1,22.0.0+8d77f4f51a,22.0.0+a28f4c53b1,22.0.0+dcf3732eb2,22.0.1-1-g7d6de66+2a20fdde0d,22.0.1-1-g8e32f31+297cba6710,22.0.1-1-geca5380+7fa3b7d9b6,22.0.1-12-g44dc1dc+2a20fdde0d,22.0.1-15-g6a90155+515f58c32b,22.0.1-16-g9282f48+790f5f2caa,22.0.1-2-g92698f7+dcf3732eb2,22.0.1-2-ga9b0f51+7fa3b7d9b6,22.0.1-2-gd1925c9+bf4f0e694f,22.0.1-24-g1ad7a390+a9625a72a8,22.0.1-25-g5bf6245+3ad8ecd50b,22.0.1-25-gb120d7b+8b5510f75f,22.0.1-27-g97737f7+2a20fdde0d,22.0.1-32-gf62ce7b1+aa4237961e,22.0.1-4-g0b3f228+2a20fdde0d,22.0.1-4-g243d05b+871c1b8305,22.0.1-4-g3a563be+32dcf1063f,22.0.1-4-g44f2e3d+9e4ab0f4fa,22.0.1-42-gca6935d93+ba5e5ca3eb,22.0.1-5-g15c806e+85460ae5f3,22.0.1-5-g58711c4+611d128589,22.0.1-5-g75bb458+99c117b92f,22.0.1-6-g1c63a23+7fa3b7d9b6,22.0.1-6-g50866e6+84ff5a128b,22.0.1-6-g8d3140d+720564cf76,22.0.1-6-gd805d02+cc5644f571,22.0.1-8-ge5750ce+85460ae5f3,master-g6e05de7fdc+babf819c66,master-g99da0e417a+8d77f4f51a,w.2021.48
LSST Data Management Base Package
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Public Member Functions | |
def | __init__ (self, *args, **kwargs) |
def | computeVarianceMean (self, exposure) |
def | run (self, scienceExposure, templateExposure, subtractedExposure, psfMatchingKernel, spatiallyVarying=True, preConvKernel=None, templateMatched=True, preConvMode=False) |
Public Attributes | |
statsControl | |
Static Public Attributes | |
ConfigClass = DecorrelateALKernelSpatialConfig | |
Decorrelate the effect of convolution by Alard-Lupton matching kernel in image difference Notes ----- 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. 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`.
Definition at line 788 of file imageDecorrelation.py.
def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelSpatialTask.__init__ | ( | self, | |
* | args, | ||
** | kwargs | ||
) |
Create the image decorrelation Task Parameters ---------- args : arguments to be passed to `lsst.pipe.base.task.Task.__init__` kwargs : additional keyword arguments to be passed to `lsst.pipe.base.task.Task.__init__`
Definition at line 815 of file imageDecorrelation.py.
def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelSpatialTask.computeVarianceMean | ( | self, | |
exposure | |||
) |
Compute the mean of the variance plane of `exposure`.
Definition at line 834 of file imageDecorrelation.py.
def lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelSpatialTask.run | ( | self, | |
scienceExposure, | |||
templateExposure, | |||
subtractedExposure, | |||
psfMatchingKernel, | |||
spatiallyVarying = True , |
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preConvKernel = None , |
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templateMatched = True , |
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preConvMode = False |
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) |
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.) templateMatched : `bool`, optional If True, the template exposure was matched (convolved) to the science exposure. preConvMode : `bool`, optional If True, ``subtractedExposure`` is assumed to be a likelihood difference image and will be noise corrected as a likelihood image. Returns ------- results : `lsst.pipe.base.Struct` a structure containing: - ``correctedExposure`` : the decorrelated diffim
Definition at line 843 of file imageDecorrelation.py.
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static |
Definition at line 812 of file imageDecorrelation.py.
lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelSpatialTask.statsControl |
Definition at line 829 of file imageDecorrelation.py.