AlardLuptonSubtractTask¶

AlardLuptonSubtractTask performs image differencing, including decorrelation.

Description¶

This task takes the pair of science and template exposures, together with the science image source catalog, and produces difference and matched template exposures as outputs.

The process involves selecting sources from the science exposure source catalog, obtaining the convolution kernel, applying this to the target image, and subtracting the images.

As discussed in the general package overview the task has two possible modes: one convolving the template image and the alternative convolving the science image. Both modes share the preparation sub-tasks, but the method that performs the convolution is not the same. The parameter that controls this behavior is mode (check AlardLuptonSubtractConfig), and it allows convolveScience, convolveTemplate and finally auto which means that the decision is made at runtime automatically.

Finally, mask planes are set on the difference and matched template outputs based on the masks of the input science and template images.

Python API summary¶

from lsst.ip.diffim.subtractImages import AlardLuptonSubtractTask

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

attributeconfig: Access configuration fields and retargetable subtasks.

methodrun(template, science, sources, visitSummary=None): PSF match, subtract, and decorrelate two images...

Retargetable subtasks¶

decorrelate¶

Default: lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelTask
Field type: ConfigurableField

Task to decorrelate the image difference.

makeKernel¶

Default: lsst.ip.diffim.makeKernel.MakeKernelTask
Field type: ConfigurableField

Task to construct a matching kernel for convolution.

scaleVariance¶

Default: lsst.meas.algorithms.scaleVariance.ScaleVarianceTask
Field type: ConfigurableField

Subtask to rescale the variance of the template to the statistically expected level.

Configuration fields¶

allowKernelSourceDetection¶

Default: False
Field type: bool Field

Re-run source detection for kernel candidates if an error is encountered while calculating the matching kernel.

badMaskPlanes¶

Default: ('NO_DATA', 'BAD', 'SAT', 'EDGE')
Field type: str ListField

Mask planes to interpolate over.

badSourceFlags¶

Default: ('sky_source', 'slot_Centroid_flag', 'slot_ApFlux_flag', 'slot_PsfFlux_flag', 'base_PixelFlags_flag_interpolated', 'base_PixelFlags_flag_saturated', 'base_PixelFlags_flag_bad')
Field type: str ListField

Flags that, if set, the associated source should not be used to determine the PSF matching kernel.

connections¶

Data type: lsst.pipe.base.config.AlardLuptonSubtractConfigConnections
Field type: ConfigField

Configurations describing the connections of the PipelineTask to datatypes

detectionThreshold¶

Default: 10
Field type: float Field

Minimum signal to noise ratio of detected sources to use for calculating the PSF matching kernel.

detectionThresholdMax¶

Default: 500
Field type: float Field

Maximum signal to noise ratio of detected sources to use for calculating the PSF matching kernel.

doApplyExternalCalibrations¶

Default: False
Field type: bool Field

Replace science Exposure’s calibration objects with those in visitSummary. Ignored if `doApplyFinalizedPsf is True.

doDecorrelation¶

Default: True
Field type: bool Field

Perform diffim decorrelation to undo pixel correlation due to A&L kernel convolution? If True, also update the diffim PSF.

doScaleVariance¶

Default: True
Field type: bool Field

Scale variance of the image difference?

doSubtractBackground¶

Default: True
Field type: bool Field

Subtract the background fit when solving the kernel?

excludeMaskPlanes¶

Default: ('NO_DATA', 'BAD', 'SAT', 'EDGE', 'FAKE')
Field type: str ListField

Mask planes to exclude when selecting sources for PSF matching.

maxKernelSources¶

Default: 1000
Field type: int Field

Maximum number of sources to use for calculating the PSF matching kernel.Set to -1 to disable.

minKernelSources¶

Default: 3
Field type: int Field

Minimum number of sources needed for calculating the PSF matching kernel.

minTemplateFractionForExpectedSuccess¶

Default: 0.2
Field type: float Field

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.

mode¶

Default

'convolveTemplate'

Field type

str ChoiceField (optional)

Choices

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

Choose which image to convolve at runtime, or require that a specific image is convolved.

preserveTemplateMask¶

Default: ('NO_DATA', 'BAD')
Field type: str ListField

Mask planes from the template to propagate to the image difference.

renameTemplateMask¶

Default: ('SAT', 'INJECTED', 'INJECTED_CORE')
Field type: str ListField

Mask planes from the template to propagate to the image differencewith ‘_TEMPLATE’ appended to the name.

requiredTemplateFraction¶

Default: 0.1
Field type: float Field

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.

saveLogOutput¶

Default: True
Field type: bool Field

Flag to enable/disable saving of log output for a task, enabled by default.

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