BestSeeingSelectVisitsTask

class lsst.pipe.tasks.selectImages.BestSeeingSelectVisitsTask(*, config: Optional[PipelineTaskConfig] = None, log: Optional[Union[logging.Logger, LsstLogAdapter]] = None, initInputs: Optional[Dict[str, Any]] = None, **kwargs)

Bases: lsst.pipe.base.PipelineTask

Select up to a maximum number of the best-seeing visits.

Don’t exceed the FWHM range specified by configs min(max)PsfFwhm. This Task is a port of the Gen2 image-selector used in the AP pipeline: BestSeeingSelectImagesTask. This Task selects full visits based on the average PSF of the entire visit.

Attributes Summary

canMultiprocess

Methods Summary

doesIntersectPolygon(visitSummary, polygon) Return True if sky polygon overlaps visit.
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.
getResourceConfig() Return resource configuration for this task.
getTaskDict() Get a dictionary of all tasks as a shallow copy.
makeField(doc) Make a lsst.pex.config.ConfigurableField for this task.
makePatchPolygon(skyMap, dataId) Return True if sky polygon overlaps visit.
makeSubtask(name, **keyArgs) Create a subtask as a new instance as the name attribute of this task.
run(visitSummaries, skyMap, dataId) Run 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

doesIntersectPolygon(visitSummary, polygon)

Return True if sky polygon overlaps visit.

Parameters:
visitSummary : lsst.afw.table.ExposureCatalog

Exposure catalog with per-detector geometry.

polygon : ` lsst.sphgeom.ConvexPolygon.convexHull`

Polygon to check overlap.

Returns:
doesIntersect : bool

True if the visit overlaps the polygon.

emptyMetadata() → None

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

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.
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")
makePatchPolygon(skyMap, dataId)

Return True if sky polygon overlaps visit.

Parameters:
skyMap : lsst.afw.table.ExposureCatalog

Exposure catalog with per-detector geometry.

dataId : dict of dataId keys

For retrieving patch info.

Returns:
result : lsst.sphgeom.ConvexPolygon.convexHull

Polygon of patch’s outer bbox.

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(visitSummaries, skyMap, dataId)

Run task.

Parameters:
visitSummary : list [lsst.pipe.base.DeferredDatasetRef]

List of lsst.pipe.base.DeferredDatasetRef of visitSummary tables of type lsst.afw.table.ExposureCatalog.

skyMap : lsst.skyMap.SkyMap

SkyMap for checking visits overlap patch.

dataId : dict of dataId keys

For retrieving patch info for checking visits overlap patch.

Returns:
result : lsst.pipe.base.Struct

Results as a struct with attributes:

goodVisits

A dict with selected visit ids as keys, so that it can be be saved as a StructuredDataDict. StructuredDataList’s are currently limited.

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