CalibrateImageTask¶

class lsst.pipe.tasks.calibrateImage.CalibrateImageTask(initial_stars_schema=None, **kwargs)¶

Bases: PipelineTask

Compute the PSF, aperture corrections, astrometric and photometric calibrations, and summary statistics for a single science exposure, and produce a catalog of brighter stars that were used to calibrate it.

Parameters:

initial_stars_schemalsst.afw.table.Schema: Schema of the initial_stars output catalog.

Attributes Summary

canMultiprocess

Methods Summary

`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`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`(*, exposures[, id_generator])	Find stars and perform psf measurement, then do a deeper detection and measurement and calibrate astrometry and photometry from that.
`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

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

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.

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(*, exposures, id_generator=None)¶

Find stars and perform psf measurement, then do a deeper detection and measurement and calibrate astrometry and photometry from that.

Parameters:

exposureslsst.afw.image.Exposure or list [lsst.afw.image.Exposure]: Post-ISR exposure(s), with an initial WCS, VisitInfo, and Filter. Modified in-place during processing if only one is passed. If two exposures are passed, treat them as snaps and combine before doing further processing.
id_generatorlsst.meas.base.IdGenerator, optional: Object that generates source IDs and provides random seeds.

Returns:

resultlsst.pipe.base.Struct

Results as a struct with attributes:

output_exposure: Calibrated exposure, with pixels in nJy units. (lsst.afw.image.Exposure)
stars: Stars that were used to calibrate the exposure, with calibrated fluxes and magnitudes. (astropy.table.Table)
stars_footprints: Footprints of stars that were used to calibrate the exposure. (lsst.afw.table.SourceCatalog)
psf_stars: Stars that were used to determine the image PSF. (astropy.table.Table)
psf_stars_footprints: Footprints of stars that were used to determine the image PSF. (lsst.afw.table.SourceCatalog)
background: Background that was fit to the exposure when detecting stars. (lsst.afw.math.BackgroundList)
applied_photo_calib: Photometric calibration that was fit to the star catalog and applied to the exposure. (lsst.afw.image.PhotoCalib)
astrometry_matches: Reference catalog stars matches used in the astrometric fit. (list [lsst.afw.table.ReferenceMatch] or lsst.afw.table.BaseCatalog)
photometry_matches: Reference catalog stars matches used in the photometric fit. (list [lsst.afw.table.ReferenceMatch] or lsst.afw.table.BaseCatalog)

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.

Navigation

CalibrateImageTask¶