GetDcrTemplateTask

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

Bases: GetTemplateTask

Attributes Summary

canMultiprocess

Methods Summary

checkPatchList(patchList)

Check that all of the DcrModel subfilters are present for each patch.

emptyMetadata()

Empty (clear) the metadata for this Task and all sub-Tasks.

getDcrModel(patchList, coaddRefs, visitInfo)

Build DCR-matched coadds from a list of exposure references.

getFullMetadata()

Get metadata for all tasks.

getFullName()

Get the task name as a hierarchical name including parent task names.

getName()

Get the name of the task.

getOverlappingExposures(inputs)

Return lists of coadds and their corresponding dataIds that overlap the detector.

getTaskDict()

Get a dictionary of all tasks as a shallow copy.

makeField(doc)

Make a lsst.pex.config.ConfigurableField for this task.

makeSubtask(name, **keyArgs)

Create a subtask as a new instance as the name attribute of this task.

run(coaddExposures, bbox, wcs, dataIds, ...)

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.

timer(name[, logLevel])

Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess: ClassVar[bool] = True

Methods Documentation

checkPatchList(patchList)

Check that all of the DcrModel subfilters are present for each patch.

Parameters:
patchListdict

Dict of the patches containing valid data for each tract.

Raises:
RuntimeError

If the number of exposures found for a patch does not match the number of subfilters.

emptyMetadata() None

Empty (clear) the metadata for this Task and all sub-Tasks.

getDcrModel(patchList, coaddRefs, visitInfo)

Build DCR-matched coadds from a list of exposure references.

Parameters:
patchListdict

Dict of the patches containing valid data for each tract.

coaddRefslist [lsst.daf.butler.DeferredDatasetHandle]

Data references to Exposure representing DcrModels that overlap the detector.

visitInfolsst.afw.image.VisitInfo

Metadata for the science image.

Returns:
coaddExposureslist [lsst.afw.image.Exposure]

Coadd exposures that overlap the detector.

getFullMetadata() TaskMetadata

Get metadata for all tasks.

Returns:
metadataTaskMetadata

The keys are the full task name. Values are metadata for the top-level task and all subtasks, sub-subtasks, etc.

Notes

The returned metadata includes timing information (if @timer.timeMethod is used) and any metadata set by the task. The name of each item consists of the full task name with . replaced by :, followed by . and the name of the item, e.g.:

topLevelTaskName:subtaskName:subsubtaskName.itemName

using : in the full task name disambiguates the rare situation that a task has a subtask and a metadata item with the same name.

getFullName() str

Get the task name as a hierarchical name including parent task names.

Returns:
fullNamestr

The full name consists of the name of the parent task and each subtask separated by periods. For example:

  • The full name of top-level task “top” is simply “top”.

  • The full name of subtask “sub” of top-level task “top” is “top.sub”.

  • The full name of subtask “sub2” of subtask “sub” of top-level task “top” is “top.sub.sub2”.

getName() str

Get the name of the task.

Returns:
taskNamestr

Name of the task.

See also

getFullName

Get the full name of the task.

getOverlappingExposures(inputs)

Return lists of coadds and their corresponding dataIds that overlap the detector.

The spatial index in the registry has generous padding and often supplies patches near, but not directly overlapping the detector. Filters inputs so that we don’t have to read in all input coadds.

Parameters:
inputsdict of task Inputs, containing:
  • coaddExposureRefslist [lsst.daf.butler.DeferredDatasetHandle of lsst.afw.image.Exposure]

    Data references to exposures that might overlap the detector.

  • bboxlsst.geom.Box2I

    Template Bounding box of the detector geometry onto which to resample the coaddExposures.

  • skyMaplsst.skymap.SkyMap

    Input definition of geometry/bbox and projection/wcs for template exposures.

  • wcslsst.afw.geom.SkyWcs

    Template WCS onto which to resample the coaddExposures.

  • visitInfolsst.afw.image.VisitInfo

    Metadata for the science image.

Returns:
resultlsst.pipe.base.Struct

A struct with attibutes:

coaddExposures

Coadd exposures that overlap the detector (list [lsst.afw.image.Exposure]).

dataIds

Data IDs of the coadd exposures that overlap the detector (list [lsst.daf.butler.DataCoordinate]).

Raises:
NoWorkFound

Raised if no patches overlatp the input detector bbox.

getTaskDict() dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]]

Get a dictionary of all tasks as a shallow copy.

Returns:
taskDictdict

Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

classmethod makeField(doc: str) ConfigurableField

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:
docstr

Help text for the field.

Returns:
configurableFieldlsst.pex.config.ConfigurableField

A ConfigurableField for this task.

Examples

Provides a convenient way to specify this task is a subtask of another task.

Here is an example of use:

class OtherTaskConfig(lsst.pex.config.Config):
    aSubtask = ATaskClass.makeField("brief description of task")
makeSubtask(name: str, **keyArgs: Any) None

Create a subtask as a new instance as the name attribute of this task.

Parameters:
namestr

Brief name of the subtask.

**keyArgs

Extra keyword arguments used to construct the task. The following arguments are automatically provided and cannot be overridden:

  • config.

  • parentTask.

Notes

The subtask must be defined by Task.config.name, an instance of ConfigurableField or RegistryField.

run(coaddExposures, bbox, wcs, dataIds, physical_filter)

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 on the template is created by combining the CoaddPsf on each template image into a meta-CoaddPsf.

Parameters:
coaddExposuresdict [int, list [lsst.afw.image.Exposure]]

Coadds to be mosaicked, indexed on tract id.

bboxlsst.geom.Box2I

Template Bounding box of the detector geometry onto which to resample the coaddExposures. Modified in-place to include the template border.

wcslsst.afw.geom.SkyWcs

Template WCS onto which to resample the coaddExposures.

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.

Returns:
resultlsst.pipe.base.Struct

A struct with attributes:

template

A template coadd exposure assembled out of patches (lsst.afw.image.ExposureF).

Raises:
NoWorkFound

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

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.

timer(name: str, logLevel: int = 10) Iterator[None]

Context manager to log performance data for an arbitrary block of code.

Parameters:
namestr

Name of code being timed; data will be logged using item name: Start and End.

logLevelint

A logging level constant.

See also

lsst.utils.timer.logInfo

Implementation function.

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time