SimplifiedSubtractConfig#

class lsst.ip.diffim.SimplifiedSubtractConfig(*args, **kw)#

Bases: AlardLuptonSubtractBaseConfig, PipelineTaskConfig

Attributes Summary

`allowKernelSourceDetection`	Re-run source detection for kernel candidates if an error is encountered while calculating the matching kernel.
`badMaskPlanes`	Mask planes to interpolate over.
`connections`	Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.
`decorrelate`	Task to decorrelate the image difference.
`detectionThreshold`	Minimum signal to noise ratio of detected sources to use for calculating the PSF matching kernel.
`detectionThresholdMax`	Maximum signal to noise ratio of detected sources to use for calculating the PSF matching kernel.
`doApplyExternalCalibrations`	Replace science Exposure's calibration objects with those in visitSummary.
`doDecorrelation`	Perform diffim decorrelation to undo pixel correlation due to A&L kernel convolution? If True, also update the diffim PSF.
`doScaleVariance`	Scale variance of the image difference? (`bool`, default `True`)
`doSubtractBackground`	Subtract the background fit when solving the kernel? It is generally better to instead subtract the background in detectAndMeasure.
`excludeMaskPlanes`	Template mask planes to exclude when selecting sources for PSF matching.
`fallbackSourceSelector`	Task to select sources to be used for PSF matching.Used only if the kernel calculation fails and`allowKernelSourceDetection` is set.
`makeKernel`	Task to construct a matching kernel for convolution.
`maxKernelSources`	Maximum number of sources to use for calculating the PSF matching kernel.Set to -1 to disable.
`minKernelSources`	Minimum number of sources needed for calculating the PSF matching kernel.
`minTemplateFractionForExpectedSuccess`	Raise NoWorkFound if PSF-matching fails and template covers less than this fraction of pixels.
`mode`	Choose which image to convolve at runtime, or require that a specific image is convolved.
`preserveTemplateMask`	Mask planes from the template to propagate to the image difference.
`renameTemplateMask`	Mask planes from the template to propagate to the image differencewith '_TEMPLATE' appended to the name.
`requiredTemplateFraction`	Raise NoWorkFound and do not attempt image subtraction if template covers less than this fraction of pixels.
`restrictKernelEdgeSources`	Exclude sources close to the edge from the kernel calculation? (`bool`, default `True`)
`saveLogOutput`	Flag to enable/disable saving of log output for a task, enabled by default.
`scaleVariance`	Subtask to rescale the variance of the template to the statistically expected level.
`sourceSelector`	Task to select sources to be used for PSF matching.
`useExistingKernel`	Use a pre-existing PSF matching kernel?If False, source detection and measurement will be run.

Attributes Documentation

allowKernelSourceDetection#: Re-run source detection for kernel candidates if an error is encountered while calculating the matching kernel. (bool, default False)

badMaskPlanes#: Mask planes to interpolate over. (List, default ('NO_DATA', 'BAD', 'SAT', 'EDGE'))

connections: pexConfig.ConfigField#: Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.

decorrelate#: Task to decorrelate the image difference. (ConfigurableInstance, default <class 'lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelConfig'>)

detectionThreshold#: Minimum signal to noise ratio of detected sources to use for calculating the PSF matching kernel. Deprecated: No longer used. Will be removed after v30 (float, default 10)

detectionThresholdMax#: Maximum signal to noise ratio of detected sources to use for calculating the PSF matching kernel. Deprecated: No longer used. Will be removed after v30 (float, default 500)

doApplyExternalCalibrations#: Replace science Exposure’s calibration objects with those in visitSummary. Ignored if doApplyFinalizedPsf is True. (`bool, default False)

doDecorrelation#: Perform diffim decorrelation to undo pixel correlation due to A&L kernel convolution? If True, also update the diffim PSF. (bool, default True)

doScaleVariance#: Scale variance of the image difference? (bool, default True)

doSubtractBackground#: Subtract the background fit when solving the kernel? It is generally better to instead subtract the background in detectAndMeasure. (bool, default False)

excludeMaskPlanes#: Template mask planes to exclude when selecting sources for PSF matching. (List, default ('NO_DATA', 'BAD', 'SAT', 'EDGE', 'FAKE', 'HIGH_VARIANCE'))

fallbackSourceSelector#: Task to select sources to be used for PSF matching.Used only if the kernel calculation fails and`allowKernelSourceDetection` is set. The fallback source detection will not include all of the same plugins as the original source detection, so not all of the same flags can be used. (ConfigurableInstance, default <class 'lsst.meas.algorithms.sourceSelector.ScienceSourceSelectorConfig'>)

makeKernel#: Task to construct a matching kernel for convolution. (ConfigurableInstance, default <class 'lsst.ip.diffim.makeKernel.MakeKernelConfig'>)

maxKernelSources#: Maximum number of sources to use for calculating the PSF matching kernel.Set to -1 to disable. (int, default 1000)

minKernelSources#: Minimum number of sources needed for calculating the PSF matching kernel. (int, default 3)

minTemplateFractionForExpectedSuccess#: Raise NoWorkFound if PSF-matching fails and template covers less than this fraction of pixels. If the fraction of pixels covered by the template is less than this value (and greater than requiredTemplateFraction) this task is attempted but failure is anticipated and tolerated. (float, default 0.2)

mode#

Choose which image to convolve at runtime, or require that a specific image is convolved. (str, default 'convolveTemplate')

Allowed values:

'auto': Choose which image to convolve at runtime.
'convolveScience': Only convolve the science image.
'convolveTemplate': Only convolve the template image.
'None': Field is optional

preserveTemplateMask#: Mask planes from the template to propagate to the image difference. (List, default ('NO_DATA', 'BAD', 'HIGH_VARIANCE'))

renameTemplateMask#: Mask planes from the template to propagate to the image differencewith ‘_TEMPLATE’ appended to the name. (List, default ('SAT', 'INJECTED', 'INJECTED_CORE'))

requiredTemplateFraction#: Raise NoWorkFound and do not attempt image subtraction if template covers less than this fraction of pixels. Setting to 0 will always attempt image subtraction. (float, default 0.1)

restrictKernelEdgeSources#: Exclude sources close to the edge from the kernel calculation? (bool, default True)

saveLogOutput#: Flag to enable/disable saving of log output for a task, enabled by default. (bool, default True)

scaleVariance#: Subtask to rescale the variance of the template to the statistically expected level. (ConfigurableInstance, default <class 'lsst.meas.algorithms.scaleVariance.ScaleVarianceConfig'>)

sourceSelector#: Task to select sources to be used for PSF matching. (ConfigurableInstance, default <class 'lsst.meas.algorithms.sourceSelector.ScienceSourceSelectorConfig'>)

useExistingKernel#: Use a pre-existing PSF matching kernel?If False, source detection and measurement will be run. (bool, default True)