UpdateVisitSummaryTask

class lsst.drp.tasks.update_visit_summary.UpdateVisitSummaryTask(*, initInputs: dict[str, Any] | None = None, **kwargs: Any)

Bases: PipelineTask

A pipeline task that creates a new visit-summary table after all lsst.afw.image.Exposure components have been finalized.

Notes

This task is designed to be run just prior to making warps for coaddition, as it aggregates all inputs other than the images and backgrounds into a single ExposureCatalog dataset and recomputes summary statistics that are useful in selecting which images should go into a coadd. Its output can also be used to reconstruct a final processed visit image when combined with a post-ISR image, the background model, and the final mask.

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(input_summary_catalog, input_exposures)	Build an updated version of a visit summary catalog.
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

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(input_summary_catalog: ExposureCatalog, input_exposures: Mapping[int, DeferredDatasetHandle], psf_overrides: ExposureCatalog | None = None, psf_star_catalog: Table | None = None, ap_corr_overrides: ExposureCatalog | None = None, photo_calib_overrides: PossiblyMultipleInput | None = None, wcs_overrides: PossiblyMultipleInput | None = None, background_originals: Mapping[int, DeferredDatasetHandle] | None = None, background_overrides: Mapping[int, DeferredDatasetHandle] | None = None)

Build an updated version of a visit summary catalog.

Parameters:

input_summary_cataloglsst.afw.table.ExposureCatalog

Input catalog. Each row in this catalog will be used to produce a row in the output catalog. Any override parameter that is None will leave the corresponding values unchanged from those in this input catalog.

input_exposurescollections.abc.Mapping [int,

lsst.daf.butler.DeferredDatasetHandle]

Deferred-load objects that fetch lsst.afw.image.Exposure instances. Only the image, mask, and variance are used; all other components are assumed to be superceded by at least input_summary_catalog and probably some _overrides arguments as well. This usually corresponds to the calexp dataset.

psf_overrideslsst.afw.table.ExposureCatalog, optional

Catalog with attached lsst.afw.detection.Psf objects that supersede the input catalog’s PSFs.

psf_star_catalogastropy.table.Table, optional

Table containing PSF stars for use in computing PSF summary statistics. Must be provided if psf_overrides is.

ap_corr_overrideslsst.afw.table.ExposureCatalog, optional

Catalog with attached lsst.afw.image.ApCorrMap objects that supersede the input catalog’s aperture corrections.

photo_calib_overridesPossiblyMultipleInput, optional

Catalog wrappers with attached lsst.afw.image.PhotoCalib objects that supersede the input catalog’s photometric calibrations.

wcs_overridesPossiblyMultipleInput, optional

Catalog wrappers with attached lsst.afw.geom.SkyWcs objects that supersede the input catalog’s astrometric calibrations.

background_originalscollections.abc.Mapping [int,

lsst.daf.butler.DeferredDatasetHandle], optional

Deferred-load objects that fetch lsst.afw.math.BackgroundList instances. These should correspond to the background already subtracted from input_exposures. If not provided and background_overrides is, it is assumed that the background in input_exposures has not been subtracted. If provided, all keys in background_overrides must also be present in background_originals.

background_overridescollections.abc.Mapping [int,

lsst.daf.butler.DeferredDatasetHandle], optional

Deferred-load objects that fetch lsst.afw.math.BackgroundList instances. These should correspond to the background that should now be subtracted from``input_exposures`` to yield the final background-subtracted image.

Returns:

output_summary_cataloglsst.afw.table.ExposureCatalog

Output visit summary catalog.

Notes

If any override parameter is provided but does not have a value for a particular detector, that component will be set to None in the returned catalog for that detector and all summary statistics derived from that component will be reset (usually to NaN) as well. Not passing an override parameter at all will instead pass through the original component and values from the input catalog unchanged.

runQuantum(butlerQC: ButlerQuantumContext, inputRefs: InputQuantizedConnection, outputRefs: OutputQuantizedConnection) → None

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.

See also

lsst.utils.timer.logInfo

Examples

Creating a timer context:

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