SimplifiedSubtractTask#

class lsst.ip.diffim.SimplifiedSubtractTask(**kwargs)#

Bases: AlardLuptonSubtractTask

Compute the image difference of a science and template image using the Alard & Lupton (1998) algorithm.

Methods Summary

run(template, science[, visitSummary, ...])

PSF match, subtract, and decorrelate two images.

Methods Documentation

run(template, science, visitSummary=None, inputPsfMatchingKernel=None)#

PSF match, subtract, and decorrelate two images.

Parameters#

templatelsst.afw.image.ExposureF

Template exposure, warped to match the science exposure.

sciencelsst.afw.image.ExposureF

Science exposure to subtract from the template.

visitSummarylsst.afw.table.ExposureCatalog, optional

Exposure catalog with external calibrations to be applied. Catalog uses the detector id for the catalog id, sorted on id for fast lookup.

inputPsfMatchingKernellsst.afw.math.Kernel, optional

Pre-existing PSF matching kernel to use for convolution. Required, and only used, if config.useExistingKernel is set.

Returns#

resultslsst.pipe.base.Struct
differencelsst.afw.image.ExposureF

Result of subtracting template and science.

matchedTemplatelsst.afw.image.ExposureF

Warped and PSF-matched template exposure.

backgroundModellsst.afw.math.Function2D

Background model that was fit while solving for the PSF-matching kernel

psfMatchingKernellsst.afw.math.Kernel

Kernel used to PSF-match the convolved image.

``kernelSources`lsst.afw.table.SourceCatalog

Sources detected on the science image that were used to construct the PSF-matching kernel.

Raises#

lsst.pipe.base.NoWorkFound

Raised if fraction of good pixels, defined as not having NO_DATA set, is less then the configured requiredTemplateFraction