WriteRecalibratedSourceTableTask¶

class lsst.pipe.tasks.postprocess.WriteRecalibratedSourceTableTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)¶

Bases: WriteSourceTableTask

Write source table to DataFrame Parquet format.

Attributes Summary

canMultiprocess

Methods Summary

`addCalibColumns`(catalog, exposure, ...)	Add replace columns with calibs evaluated at each centroid
`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.
`prepareCalibratedExposure`(exposure, detectorId)	Prepare a calibrated exposure and apply external calibrations if so configured.
`run`(catalog[, ccdVisitId])	Convert `src` catalog to DataFrame
`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

addCalibColumns(catalog, exposure, idGenerator, **kwargs)¶

Add replace columns with calibs evaluated at each centroid

Add or replace ‘base_LocalWcs’ `base_LocalPhotoCalib’ columns in a a source catalog, by rerunning the plugins.

Parameters:

cataloglsst.afw.table.SourceCatalog: catalog to which calib columns will be added
exposurelsst.afw.image.exposure.Exposure: Exposure with attached PhotoCalibs and SkyWcs attributes to be reevaluated at local centroids. Pixels are not required.
idGeneratorlsst.meas.base.IdGenerator: Object that generates Source IDs and random seeds.
**kwargs: Additional keyword arguments are ignored to facilitate passing the same arguments to several methods.

Returns:

newCat: lsst.afw.table.SourceCatalog: Source Catalog with requested local calib columns

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.

prepareCalibratedExposure(exposure, detectorId, visitSummary=None)¶

Prepare a calibrated exposure and apply external calibrations if so configured.

Parameters:

exposurelsst.afw.image.exposure.Exposure: Input exposure to adjust calibrations. May be empty.
detectorIdint: Detector ID associated with the exposure.
visitSummarylsst.afw.table.ExposureCatalog, optional: Exposure catalog with all calibration objects. WCS and PhotoCalib are always applied if visitSummary is provided and those components are not None.

Returns:

exposurelsst.afw.image.exposure.Exposure: Exposure with adjusted calibrations.

run(catalog, ccdVisitId=None, **kwargs)¶

Convert src catalog to DataFrame

Parameters:

catalog: `afwTable.SourceCatalog`: catalog to be converted
ccdVisitId: `int`: ccdVisitId to be added as a column
**kwargs: Additional keyword arguments are ignored as a convenience for subclasses that pass the same arguments to several different methods.

Returns:

resultStruct

table: DataFrame version of the input catalog

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

WriteRecalibratedSourceTableTask¶