ProcessBrightStarsTask¶

class lsst.pipe.tasks.processBrightStars.ProcessBrightStarsTask(initInputs=None, *args, **kwargs)¶

Bases: PipelineTask

The description of the parameters for this Task are detailed in PipelineTask.

Parameters:

initInputsUnknown
*args: Additional positional arguments.
**kwargs: Additional keyword arguments.

Notes

ProcessBrightStarsTask is used to extract, process, and store small image cut-outs (or “postage stamps”) around bright stars. It relies on three methods, called in succession:

extractStamps: Find bright stars within the exposure using a reference catalog and extract a stamp centered on each.
warpStamps: Shift and warp each stamp to remove optical distortions and sample all stars on the same pixel grid.
measureAndNormalize: Compute the flux of an object in an annulus and normalize it. This is required to normalize each bright star stamp as their central pixels are likely saturated and/or contain ghosts, and cannot be used.

Attributes Summary

canMultiprocess

Methods Summary

`applySkyCorr`(calexp, skyCorr)	Apply correction to the sky background level.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`extractStamps`(inputExposure[, refObjLoader])	Read the position of bright stars within an input exposure using a refCat and extract them.
`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.
`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`(inputExposure[, refObjLoader, dataId, ...])	Identify bright stars within an exposure using a reference catalog, extract stamps around each, then preprocess them.
`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.
`warpStamps`(stamps, pixCenters)	Warps and shifts all given stamps so they are sampled on the same pixel grid and centered on the central pixel.

Attributes Documentation

canMultiprocess: ClassVar[bool] = True¶

Methods Documentation

applySkyCorr(calexp, skyCorr)¶

Apply correction to the sky background level.

Sky corrections can be generated using the SkyCorrectionTask. As the sky model generated there extends over the full focal plane, this should produce a more optimal sky subtraction solution.

Parameters:

calexpExposure or MaskedImage: Calibrated exposure.
skyCorrBackgroundList, optional: Full focal plane sky correction from SkyCorrectionTask.

Notes

This method modifies the input calexp in-place.

emptyMetadata() → None¶: Empty (clear) the metadata for this Task and all sub-Tasks.

extractStamps(inputExposure, refObjLoader=None)¶

Read the position of bright stars within an input exposure using a refCat and extract them.

Parameters:

inputExposureExposureF: The image from which bright star stamps should be extracted.
refObjLoaderReferenceObjectLoader, optional: Loader to find objects within a reference catalog.

Returns:

resultStruct

Results as a struct with attributes:

starIms: Postage stamps (list).
pixCenters: Corresponding coords to each star’s center, in pixels (list).
GMags: Corresponding (Gaia) G magnitudes (list).
gaiaIds: Corresponding unique Gaia identifiers (np.ndarray).

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

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(inputExposure, refObjLoader=None, dataId=None, skyCorr=None)¶

Identify bright stars within an exposure using a reference catalog, extract stamps around each, then preprocess them. The preprocessing steps are: shifting, warping and potentially rotating them to the same pixel grid; computing their annular flux and normalizing them.

Parameters:

inputExposureExposureF: The image from which bright star stamps should be extracted.
refObjLoaderReferenceObjectLoader, optional: Loader to find objects within a reference catalog.
dataIddict or DataCoordinate: The dataId of the exposure (and detector) bright stars should be extracted from.
skyCorrBackgroundList, optional: Full focal plane sky correction obtained by SkyCorrectionTask.

Returns:

resultStruct

Results as a struct with attributes:

brightStarStamps: (BrightStarStamps)

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.
logLevel: A logging level constant.

Navigation

ProcessBrightStarsTask¶