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, result])

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, result=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.

resultlsst.pipe.base.Struct, optional

Result struct that is modified to allow saving of partial outputs for some failure conditions. If the task completes successfully, this is also returned.

Returns:
resultlsst.pipe.base.Struct

Results as a struct with attributes:

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.

See also

lsst.utils.timer.logInfo

Implementation function.

Examples

Creating a timer context:

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