GbdesGlobalAstrometricFitTask¶

class lsst.drp.tasks.gbdesAstrometricFit.GbdesGlobalAstrometricFitTask(**kwargs)¶

Bases: GbdesAstrometricFitTask

Calibrate the WCS across multiple visits and multiple fields using the GBDES package.

This class assumes that the input visits can be separated into contiguous groups, for which an individual group covers an area of less than a hemisphere.

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.
`make_yaml`(inputVisitSummary[, inputFile, ...])	Make a YAML-type object that describes the parameters of the fit model.
`run`(inputVisitSummaries, ...[, ...])	Run the WCS fit for a given set of visits
`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.

make_yaml(inputVisitSummary, inputFile=None, inputCameraModel=None)¶

Make a YAML-type object that describes the parameters of the fit model.

Parameters:

inputVisitSummarylsst.afw.table.ExposureCatalog: Catalog with per-detector summary information.
inputFilestr: Path to a file that contains a basic model.
inputCameraModeldict [str, np.ndarray], optional: Parameters to use for the device part of the model.

Returns:

inputYamlwcsfit.YAMLCollector: YAML object containing the model description.
inputDictdict [str, str]: Dictionary containing the model description.

run(inputVisitSummaries, isolatedStarSources, isolatedStarCatalogs, instrumentName='', refEpoch=None, refObjectLoader=None, inputCameraModel=None)¶

Run the WCS fit for a given set of visits

Parameters:

inputVisitSummarieslist [lsst.afw.table.ExposureCatalog]: List of catalogs with per-detector summary information.
isolatedStarSourceslist [DeferredDatasetHandle]: List of handles pointing to isolated star sources.
isolatedStarCatalog: `list` [`DeferredDatasetHandle`]: List of handles pointing to isolated star catalogs.
instrumentNamestr, optional: Name of the instrument used. This is only used for labelling.
refEpochfloat, optional: Epoch of the reference objects in MJD.
refObjectLoaderinstance of: lsst.meas.algorithms.loadReferenceObjects.ReferenceObjectLoader, optional Reference object loader instance.
inputCameraModeldict [str, np.ndarray], optional: Parameters to use for the device part of the model.

Returns:

resultlsst.pipe.base.Struct

outputWcsslist [lsst.afw.table.ExposureCatalog]: List of exposure catalogs (one per visit) with the WCS for each detector set by the new fitted WCS.
fitModelwcsfit.WCSFit: Model-fitting object with final model parameters.
outputCatalogpyarrow.Table: Catalog with fit residuals of all sources used.
starCatalogpyarrow.Table: Catalog with best-fit positions of the objects fit.
modelParamsdict: Parameters and covariance of the best-fit WCS model.
cameraModelParamsdict [str, np.ndarray]: Parameters of the device part of the model, in the format needed as input for future runs.

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.

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GbdesGlobalAstrometricFitTask¶