FgcmOutputProductsTask

class lsst.fgcmcal.FgcmOutputProductsTask(**kwargs)

Bases: lsst.pipe.base.PipelineTask

Output products from FGCM global calibration.

Attributes Summary

canMultiprocess

Methods Summary

emptyMetadata()	Empty (clear) the metadata for this Task and all sub-Tasks.
generateTractOutputProducts(handleDict, …)	Generate the output products for a given tract, as specified in the config.
getAllSchemaCatalogs()	Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
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.ConfigurableField for this task.
makeSubtask(name, **keyArgs)	Create a subtask as a new instance as the name attribute of this task.
run(handleDict, physicalFilterMap)	Run the output products task.
runQuantum(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

canMultiprocess = True

Methods Documentation

emptyMetadata() → None

Empty (clear) the metadata for this Task and all sub-Tasks.

generateTractOutputProducts(handleDict, tract, visitCat, zptCat, atmCat, stdCat, fgcmBuildStarsConfig)

Generate the output products for a given tract, as specified in the config.

This method is here to have an alternate entry-point for FgcmCalibrateTract.

Parameters:

handleDict : dict

All handles are lsst.daf.butler.DeferredDatasetHandle handle dictionary with keys:

"camera"

Camera object (lsst.afw.cameraGeom.Camera)

"fgcmLookUpTable"

handle for the FGCM look-up table.

tract : int

Tract number

visitCat : lsst.afw.table.BaseCatalog

FGCM visitCat from FgcmBuildStarsTask

zptCat : lsst.afw.table.BaseCatalog

FGCM zeropoint catalog from FgcmFitCycleTask

atmCat : lsst.afw.table.BaseCatalog

FGCM atmosphere parameter catalog from FgcmFitCycleTask

stdCat : lsst.afw.table.SimpleCatalog

FGCM standard star catalog from FgcmFitCycleTask

fgcmBuildStarsConfig : lsst.fgcmcal.FgcmBuildStarsConfig

Configuration object from FgcmBuildStarsTask

Returns:

retStruct : lsst.pipe.base.Struct

Output structure with keys:

offsets : np.ndarray

Final reference offsets, per band.

atmospheres : generator [(int, lsst.afw.image.TransmissionCurve)]

Generator that returns (visit, transmissionCurve) tuples.

photoCalibCatalogs : generator [(int, lsst.afw.table.ExposureCatalog)]

Generator that returns (visit, exposureCatalog) tuples.

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.table Catalog 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.

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.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:

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”.

getName() → str

Get the name of the task.

Returns:

taskName : str

Name of the task.

See also

getFullName

getResourceConfig() → Optional[ResourceConfig]

Return resource configuration for this task.

Returns:

Object of type ResourceConfig or None if resource

configuration is not defined for this task.

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.table Catalog 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.

getTaskDict() → Dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]]

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.

classmethod makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:

doc : str

Help text for the field.

Returns:

configurableField : lsst.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) → None

Create a subtask as a new instance as the name attribute 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 of ConfigurableField or RegistryField.

run(handleDict, physicalFilterMap)

Run the output products task.

Parameters:

handleDict : dict

All handles are lsst.daf.butler.DeferredDatasetHandle handle dictionary with keys:

"camera"

Camera object (lsst.afw.cameraGeom.Camera)

"fgcmLookUpTable"

handle for the FGCM look-up table.

"fgcmVisitCatalog"

handle for visit summary catalog.

"fgcmStandardStars"

handle for the output standard star catalog.

"fgcmZeropoints"

handle for the zeropoint data catalog.

"fgcmAtmosphereParameters"

handle for the atmosphere parameter catalog.

"fgcmBuildStarsTableConfig"

Config for lsst.fgcmcal.fgcmBuildStarsTableTask.

physicalFilterMap : dict

Dictionary of mappings from physical filter to FGCM band.

Returns:

retStruct : lsst.pipe.base.Struct

Output structure with keys:

offsets : np.ndarray

Final reference offsets, per band.

atmospheres : generator [(int, lsst.afw.image.TransmissionCurve)]

Generator that returns (visit, transmissionCurve) tuples.

photoCalibCatalogs : generator [(int, lsst.afw.table.ExposureCatalog)]

Generator that returns (visit, exposureCatalog) tuples.

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 PipelineTaskConnections class. The values of these attributes are the lsst.daf.butler.DatasetRef objects associated with the defined input/prerequisite connections.

outputRefs : OutputQuantizedConnection

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:

name : str

Name of code being timed; data will be logged using item name: Start and End.

logLevel

A logging level constant.

See also

timer.logInfo

Examples

Creating a timer context:

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