WriteRecalibratedSourceTableTask¶
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class
lsst.pipe.tasks.postprocess.WriteRecalibratedSourceTableTask(*, config: Optional[PipelineTaskConfig] = None, log: Optional[Union[logging.Logger, LsstLogAdapter]] = None, initInputs: Optional[Dict[str, Any]] = None, **kwargs)¶ Bases:
lsst.pipe.tasks.postprocess.WriteSourceTableTaskWrite source table to parquet
Attributes Summary
canMultiprocessMethods Summary
addCalibColumns(catalog, exposure, …)Add replace columns with calibs evaluated at each centroid attachCalibs(inputRefs, skyMap, exposure[, …])Apply external calibrations to exposure per configuration emptyMetadata()Empty (clear) the metadata for this Task and all sub-Tasks. getAllSchemaCatalogs()Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict. getClosestTract(tracts, skyMap, bbox, wcs)Find the index of the tract closest to detector from list of tractIds 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. getResourceConfig()Return resource configuration for this task. getSchemaCatalogs()Get the schemas generated by this task. getTaskDict()Get a dictionary of all tasks as a shallow copy. makeField(doc)Make a lsst.pex.config.ConfigurableFieldfor this task.makeSubtask(name, **keyArgs)Create a subtask as a new instance as the nameattribute of this task.prepareCalibratedExposure(exposure[, …])Prepare a calibrated exposure and apply external calibrations if so configured. run(catalog[, ccdVisitId])Convert srccatalog to parquetrunQuantum(butlerQC, inputRefs, outputRefs)Method to do butler IO and or transforms 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
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canMultiprocess= True¶
Methods Documentation
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addCalibColumns(catalog, exposure, exposureIdInfo, **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: - catalog :
lsst.afw.table.SourceCatalog catalog to which calib columns will be added
- exposure :
lsst.afw.image.exposure.Exposure Exposure with attached PhotoCalibs and SkyWcs attributes to be reevaluated at local centroids. Pixels are not required.
- exposureIdInfo :
lsst.obs.base.ExposureIdInfo
Returns: - newCat:
lsst.afw.table.SourceCatalog Source Catalog with requested local calib columns
- catalog :
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attachCalibs(inputRefs, skyMap, exposure, externalSkyWcsGlobalCatalog=None, externalSkyWcsTractCatalog=None, externalPhotoCalibGlobalCatalog=None, externalPhotoCalibTractCatalog=None, **kwargs)¶ Apply external calibrations to exposure per configuration
When multiple tract-level calibrations overlap, select the one with the center closest to detector.
Parameters: - inputRefs :
lsst.pipe.base.InputQuantizedConnection, for dataIds of tract-level calibs.
- skyMap :
lsst.skymap.SkyMap - exposure :
lsst.afw.image.exposure.Exposure Input exposure to adjust calibrations.
- externalSkyWcsGlobalCatalog :
lsst.afw.table.ExposureCatalog, optional Exposure catalog with external skyWcs to be applied per config
- externalSkyWcsTractCatalog :
lsst.afw.table.ExposureCatalog, optional Exposure catalog with external skyWcs to be applied per config
- externalPhotoCalibGlobalCatalog :
lsst.afw.table.ExposureCatalog, optional Exposure catalog with external photoCalib to be applied per config
- externalPhotoCalibTractCatalog :
lsst.afw.table.ExposureCatalog, optional
Returns: - exposure :
lsst.afw.image.exposure.Exposure Exposure with adjusted calibrations.
- inputRefs :
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emptyMetadata() → None¶ Empty (clear) the metadata for this Task and all sub-Tasks.
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getAllSchemaCatalogs() → Dict[str, Any]¶ Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
Returns: - schemacatalogs :
dict Keys are butler dataset type, values are a empty catalog (an instance of the appropriate
lsst.afw.tableCatalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.
Notes
This method may be called on any task in the hierarchy; it will return the same answer, regardless.
The default implementation should always suffice. If your subtask uses schemas the override
Task.getSchemaCatalogs, not this method.- schemacatalogs :
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getClosestTract(tracts, skyMap, bbox, wcs)¶ Find the index of the tract closest to detector from list of tractIds
Parameters: - tracts: `list` [`int`]
Iterable of integer tractIds
- skyMap :
lsst.skymap.SkyMap skyMap to lookup tract geometry and wcs
- bbox :
lsst.geom.Box2I Detector bbox, center of which will compared to tract centers
- wcs :
lsst.afw.geom.SkyWcs Detector Wcs object to map the detector center to SkyCoord
Returns: - index :
int
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getFullMetadata() → lsst.pipe.base._task_metadata.TaskMetadata¶ Get metadata for all tasks.
Returns: - metadata :
TaskMetadata 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.timeMethodis 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.- metadata :
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getFullName() → str¶ Get the task name as a hierarchical name including parent task names.
Returns: - fullName :
str 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”.
- fullName :
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getResourceConfig() → Optional[ResourceConfig]¶ Return resource configuration for this task.
Returns: - Object of type
ResourceConfigorNoneif resource - configuration is not defined for this task.
- Object of type
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getSchemaCatalogs() → Dict[str, Any]¶ Get the schemas generated by this task.
Returns: - schemaCatalogs :
dict Keys are butler dataset type, values are an empty catalog (an instance of the appropriate
lsst.afw.tableCatalog type) for this task.
See also
Task.getAllSchemaCatalogs
Notes
Warning
Subclasses that use schemas must override this method. The default implementation returns an empty dict.
This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.
Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.
- schemaCatalogs :
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getTaskDict() → Dict[str, weakref]¶ Get a dictionary of all tasks as a shallow copy.
Returns: - taskDict :
dict Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.
- taskDict :
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classmethod
makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField¶ Make a
lsst.pex.config.ConfigurableFieldfor this task.Parameters: - doc :
str Help text for the field.
Returns: - configurableField :
lsst.pex.config.ConfigurableField A
ConfigurableFieldfor 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")
- doc :
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makeSubtask(name: str, **keyArgs) → None¶ Create a subtask as a new instance as the
nameattribute of this task.Parameters: - name :
str 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 ofConfigurableFieldorRegistryField.- name :
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prepareCalibratedExposure(exposure, externalSkyWcsCatalog=None, externalPhotoCalibCatalog=None)¶ Prepare a calibrated exposure and apply external calibrations if so configured.
Parameters: - exposure :
lsst.afw.image.exposure.Exposure Input exposure to adjust calibrations.
- externalSkyWcsCatalog :
lsst.afw.table.ExposureCatalog, optional Exposure catalog with external skyWcs to be applied if config.doApplyExternalSkyWcs=True. Catalog uses the detector id for the catalog id, sorted on id for fast lookup.
- externalPhotoCalibCatalog :
lsst.afw.table.ExposureCatalog, optional Exposure catalog with external photoCalib to be applied if config.doApplyExternalPhotoCalib=True. Catalog uses the detector id for the catalog id, sorted on id for fast lookup.
Returns: - exposure :
lsst.afw.image.exposure.Exposure Exposure with adjusted calibrations.
- exposure :
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run(catalog, ccdVisitId=None, **kwargs)¶ Convert
srccatalog to parquetParameters: - catalog: `afwTable.SourceCatalog`
catalog to be converted
- ccdVisitId: `int`
ccdVisitId to be added as a column
Returns: - result :
lsst.pipe.base.Struct tableParquetTableversion of the input catalog
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runQuantum(butlerQC, inputRefs, outputRefs)¶ Method to do butler IO and or transforms to provide in memory objects for tasks run method
Parameters: - butlerQC :
ButlerQuantumContext A butler which is specialized to operate in the context of a
lsst.daf.butler.Quantum.- inputRefs :
InputQuantizedConnection Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnectionsclass. The values of these attributes are thelsst.daf.butler.DatasetRefobjects associated with the defined input/prerequisite connections.- outputRefs :
OutputQuantizedConnection Datastructure whose attribute names are the names that identify connections defined in corresponding
PipelineTaskConnectionsclass. The values of these attributes are thelsst.daf.butler.DatasetRefobjects associated with the defined output connections.
- butlerQC :
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timer(name: str, logLevel: int = 10) → Iterator[None]¶ Context manager to log performance data for an arbitrary block of code.
Parameters: See also
timer.logInfo
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
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