GetTemplateTask

class lsst.ip.diffim.GetTemplateTask(*args, **kwargs)

Bases: PipelineTask

Methods Summary

checkHighVariance(template)	Set a mask plane for regions with unusually high variance.
convert_outputs_to_future(template, ...)	Convert a template image to DifferenceImage format.
getExposures(coaddExposureHandles, bbox, ...)	Return a data structure containing the coadds that overlap the specified bbox projected onto the sky, and a corresponding data structure of their dataIds.
run(*, coaddExposureHandles, bbox, wcs, ...)	Warp coadds from multiple tracts and patches to form a template to subtract from a science image.
runQuantum(butlerQC, inputRefs, outputRefs)	Do butler IO and transform to provide in memory objects for tasks run method.

Methods Documentation

checkHighVariance(template)

Set a mask plane for regions with unusually high variance.

Parameters

templatelsst.afw.image.Exposure

The warped template exposure, which will be modified in place.

convert_outputs_to_future(template, coadd_refs, detector, exposureRecord)

Convert a template image to DifferenceImage format.

This replaces template with an lsst.images.DifferenceImage instance and records the coadds contributed to it, along with the instrument they were made from. The Gaussian PSF set by run is converted to an lsst.images.psfs.GaussianPointSpreadFunction.

Parameters

templatelsst.afw.image.Exposure

Template to convert. Its detector is replaced with detector and its mask is modified in place.

coadd_refslist [lsst.daf.butler.DatasetRef]

References to the coadds that may have gone into the template. May be a superset of the coadds that were used; supplies the dataset id and RUN collection recorded for each coadd that was.

detectorlsst.afw.cameraGeom.Detector

Detector of the science image that the template was built for.

exposureRecordlsst.daf.butler.DimensionRecord

The exposure record of the observation the template was built for, which supplies the observation metadata recorded on the output.

Returns

convertedTemplatelsst.images.DifferenceImage

The converted image.

Raises

RuntimeError

Raised if the template has pixels set in a mask plane that lsst.images.get_legacy_template_mask_planes does not map and config.raiseOnUndefinedMaskMap is True, or if coadd_refs spans more than one skymap.

getExposures(coaddExposureHandles, bbox, skymap, wcs)

Return a data structure containing the coadds that overlap the specified bbox projected onto the sky, and a corresponding data structure of their dataIds. These are the appropriate inputs to this task’s run method.

The spatial index in the butler registry has generous padding and often supplies patches near, but not directly overlapping the desired region. This method filters the inputs so that run does not have to read in all possibly-matching coadd exposures.

Parameters

coaddExposureHandlesiterable [lsst.daf.butler.DeferredDatasetHandle of lsst.afw.image.Exposure]

Dataset handles to exposures that might overlap the desired region.

bboxlsst.geom.Box2I

Template bounding box of the pixel geometry onto which the coaddExposures will be resampled.

skymaplsst.skymap.SkyMap

Geometry of the tracts and patches the coadds are defined on.

wcslsst.afw.geom.SkyWcs

Template WCS onto which the coadds will be resampled.

Returns

resultlsst.pipe.base.Struct

A struct with attributes:

coaddExposures

Dict of coadd exposures that overlap the projected bbox, indexed on tract id (dict [int, list [lsst.daf.butler.DeferredDatasetHandle of

lsst.afw.image.Exposure] ]).

dataIds

Dict of data IDs of the coadd exposures that overlap the projected bbox, indexed on tract id (dict [int, list [`lsst.daf.butler.DataCoordinate] ]).

Raises

NoWorkFound

Raised if no patches overlap the input detector bbox, or the input WCS is None.

run(*, coaddExposureHandles, bbox, wcs, dataIds, physical_filter, visit=None, instrument=None)

Warp coadds from multiple tracts and patches to form a template to subtract from a science image.

Tract and patch overlap regions are combined by a variance-weighted average, and the variance planes are combined with the same weights, not added in quadrature; the overlap regions are not statistically independent, because they’re derived from the same original data. The PSF of the template is a Gaussian with the same width as the CoaddPsf evaluated at the center of the detector.

The template is built from coadds of one instrument: the science image’s instrument if any coadd was made from it, and otherwise the one that most of the coadds were made from. Coadds made from another instrument are dropped, and so are coadds that record no instrument unless none of the coadds records one.

Parameters

coaddExposureHandlesdict [int, list of [lsst.daf.butler.DeferredDatasetHandle of lsst.afw.image.Exposure]]

Coadds to be mosaicked, indexed on tract id.

bboxlsst.geom.Box2I

Input Bounding box of the detector geometry onto which to resample the coaddExposureHandles. The output template bbox will be grown by templateBorderSize.

wcslsst.afw.geom.SkyWcs

Template WCS onto which to resample the coaddExposureHandles.

dataIdsdict [int, list [lsst.daf.butler.DataCoordinate]]

Record of the tract and patch of each coaddExposure, indexed on tract id.

physical_filterstr

Physical filter of the science image.

visitint, optional

If supplied, over-write the visit ID in the template’s visitInfo so that downstream source injection tasks can link the template and science image for the visit.

instrumentstr, optional

Instrument of the science image. Coadds made from it are used in preference to coadds from any other instrument.

Returns

resultlsst.pipe.base.Struct

A struct with attributes:

template

A template coadd exposure assembled out of patches, with pixels in nJy. Its PSF is a Gaussian approximation to the CoaddPsf of its inputs (lsst.afw.image.ExposureF).

Raises

NoWorkFound

If no coadds are found with sufficient un-masked pixels.

RuntimeError

If the template is not known to be from the science image’s instrument and no coadd records the plate scale of its input images, so the template variance cannot be corrected.

runQuantum(butlerQC, inputRefs, outputRefs)

Do butler IO and transform to provide in memory objects for tasks run method.

Parameters

butlerQCQuantumContext

A butler which is specialized to operate in the context of a lsst.daf.butler.Quantum.

inputRefsInputQuantizedConnection

Datastructure whose attribute names are the names that identify connections defined in corresponding PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined input/prerequisite connections.

outputRefsOutputQuantizedConnection

Datastructure whose attribute names are the names that identify connections defined in corresponding PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined output connections.