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def | __init__ (self, **kwargs) |
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def | run (self, template, science, sources, finalizedPsfApCorrCatalog=None) |
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def | runConvolveTemplate (self, template, science, selectSources) |
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def | runConvolveScience (self, template, science, selectSources) |
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def | finalize (self, template, science, difference, kernel, templateMatched=True, preConvMode=False, preConvKernel=None, spatiallyVarying=False) |
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Compute the image difference of a science and template image using
the Alard & Lupton (1998) algorithm.
Definition at line 169 of file subtractImages.py.
◆ __init__()
def lsst.ip.diffim.subtractImages.AlardLuptonSubtractTask.__init__ |
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self, |
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** |
kwargs |
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◆ finalize()
def lsst.ip.diffim.subtractImages.AlardLuptonSubtractTask.finalize |
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self, |
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template, |
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science, |
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difference, |
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kernel, |
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templateMatched = True , |
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preConvMode = False , |
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preConvKernel = None , |
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spatiallyVarying = False |
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Decorrelate the difference image to undo the noise correlations
caused by convolution.
Parameters
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template : `lsst.afw.image.ExposureF`
Template exposure, warped to match the science exposure.
science : `lsst.afw.image.ExposureF`
Science exposure to subtract from the template.
difference : `lsst.afw.image.ExposureF`
Result of subtracting template and science.
kernel : `lsst.afw.math.Kernel`
An (optionally spatially-varying) PSF matching kernel
templateMatched : `bool`, optional
Was the template PSF-matched to the science image?
preConvMode : `bool`, optional
Was the science image preconvolved with its own PSF
before PSF matching the template?
preConvKernel : `lsst.afw.detection.Psf`, optional
If not `None`, then the science image was pre-convolved with
(the reflection of) this kernel. Must be normalized to sum to 1.
spatiallyVarying : `bool`, optional
Compute the decorrelation kernel spatially varying across the image?
Returns
-------
correctedExposure : `lsst.afw.image.ExposureF`
The decorrelated image difference.
Definition at line 442 of file subtractImages.py.
◆ run()
def lsst.ip.diffim.subtractImages.AlardLuptonSubtractTask.run |
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self, |
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template, |
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science, |
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sources, |
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finalizedPsfApCorrCatalog = None |
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PSF match, subtract, and decorrelate two images.
Parameters
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template : `lsst.afw.image.ExposureF`
Template exposure, warped to match the science exposure.
science : `lsst.afw.image.ExposureF`
Science exposure to subtract from the template.
sources : `lsst.afw.table.SourceCatalog`
Identified sources on the science exposure. This catalog is used to
select sources in order to perform the AL PSF matching on stamp
images around them.
finalizedPsfApCorrCatalog : `lsst.afw.table.ExposureCatalog`, optional
Exposure catalog with finalized psf models and aperture correction
maps to be applied if config.doApplyFinalizedPsf=True. Catalog uses
the detector id for the catalog id, sorted on id for fast lookup.
Returns
-------
results : `lsst.pipe.base.Struct`
``difference`` : `lsst.afw.image.ExposureF`
Result of subtracting template and science.
``matchedTemplate`` : `lsst.afw.image.ExposureF`
Warped and PSF-matched template exposure.
``backgroundModel`` : `lsst.afw.math.Function2D`
Background model that was fit while solving for the PSF-matching kernel
``psfMatchingKernel`` : `lsst.afw.math.Kernel`
Kernel used to PSF-match the convolved image.
Raises
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RuntimeError
If an unsupported convolution mode is supplied.
RuntimeError
If there are too few sources to calculate the PSF matching kernel.
lsst.pipe.base.NoWorkFound
Raised if fraction of good pixels, defined as not having NO_DATA
set, is less then the configured requiredTemplateFraction
Definition at line 230 of file subtractImages.py.
◆ runConvolveScience()
def lsst.ip.diffim.subtractImages.AlardLuptonSubtractTask.runConvolveScience |
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self, |
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template, |
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science, |
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selectSources |
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Convolve the science image with a PSF-matching kernel and subtract the template image.
Parameters
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template : `lsst.afw.image.ExposureF`
Template exposure, warped to match the science exposure.
science : `lsst.afw.image.ExposureF`
Science exposure to subtract from the template.
selectSources : `lsst.afw.table.SourceCatalog`
Identified sources on the science exposure. This catalog is used to
select sources in order to perform the AL PSF matching on stamp
images around them.
Returns
-------
results : `lsst.pipe.base.Struct`
``difference`` : `lsst.afw.image.ExposureF`
Result of subtracting template and science.
``matchedTemplate`` : `lsst.afw.image.ExposureF`
Warped template exposure. Note that in this case, the template
is not PSF-matched to the science image.
``backgroundModel`` : `lsst.afw.math.Function2D`
Background model that was fit while solving for the PSF-matching kernel
``psfMatchingKernel`` : `lsst.afw.math.Kernel`
Kernel used to PSF-match the science image to the template.
Definition at line 379 of file subtractImages.py.
◆ runConvolveTemplate()
def lsst.ip.diffim.subtractImages.AlardLuptonSubtractTask.runConvolveTemplate |
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self, |
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template, |
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science, |
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selectSources |
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Convolve the template image with a PSF-matching kernel and subtract
from the science image.
Parameters
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template : `lsst.afw.image.ExposureF`
Template exposure, warped to match the science exposure.
science : `lsst.afw.image.ExposureF`
Science exposure to subtract from the template.
selectSources : `lsst.afw.table.SourceCatalog`
Identified sources on the science exposure. This catalog is used to
select sources in order to perform the AL PSF matching on stamp
images around them.
Returns
-------
results : `lsst.pipe.base.Struct`
``difference`` : `lsst.afw.image.ExposureF`
Result of subtracting template and science.
``matchedTemplate`` : `lsst.afw.image.ExposureF`
Warped and PSF-matched template exposure.
``backgroundModel`` : `lsst.afw.math.Function2D`
Background model that was fit while solving for the PSF-matching kernel
``psfMatchingKernel`` : `lsst.afw.math.Kernel`
Kernel used to PSF-match the template to the science image.
Definition at line 328 of file subtractImages.py.
◆ ConfigClass
◆ convolutionControl
lsst.ip.diffim.subtractImages.AlardLuptonSubtractTask.convolutionControl |
The documentation for this class was generated from the following file: