MakeWarpTask¶

class lsst.pipe.tasks.makeWarp.MakeWarpTask(**kwargs)¶

Bases: CoaddBaseTask

Warp and optionally PSF-Match calexps onto an a common projection.

Warp and optionally PSF-Match calexps onto a common projection, by performing the following operations: - Group calexps by visit/run - For each visit, generate a Warp by calling method @ref run.

run loops over the visit’s calexps calling WarpAndPsfMatchTask on each visit

Attributes Summary

canMultiprocess

Methods Summary

`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`filterInputs`(indices, inputs)	Filter task inputs by their indices.
`getBadPixelMask`()	Convenience method to provide the bitmask from the mask plane names
`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.
`getTempExpDatasetName`([warpType])	Return warp name for given warpType and task config
`getWarpTypeList`()	Return list of requested warp types per the config.
`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`(calExpList, ccdIdList, skyInfo[, ...])	Create a Warp from inputs.
`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.

filterInputs(indices, inputs)¶

Filter task inputs by their indices.

Parameters:

indiceslist [int]
inputsdict [list]: A dictionary of input connections to be passed to run.

Returns:

inputsdict [list]: Task inputs with their lists filtered by indices.

getBadPixelMask()¶: Convenience method to provide the bitmask from the mask plane names

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

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.

getTempExpDatasetName(warpType='direct')¶

Return warp name for given warpType and task config

Parameters:

warpTypestr: Either ‘direct’ or ‘psfMatched’.

Returns:

WarpDatasetNamestr

getWarpTypeList()¶: Return list of requested warp types per the config.

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.

run(calExpList, ccdIdList, skyInfo, visitId=0, dataIdList=None, **kwargs)¶

Create a Warp from inputs.

We iterate over the multiple calexps in a single exposure to construct the warp (previously called a coaddTempExp) of that exposure to the supplied tract/patch.

Pixels that receive no pixels are set to NAN; this is not correct (violates LSST algorithms group policy), but will be fixed up by interpolating after the coaddition.

calexpRefListlist: List of data references for calexps that (may) overlap the patch of interest.
skyInfolsst.pipe.base.Struct: Struct from makeSkyInfo() with geometric information about the patch.
visitIdint: Integer identifier for visit, for the table that will produce the CoaddPsf.

Returns:

resultlsst.pipe.base.Struct

Results as a struct with attributes:

exposures: A dictionary containing the warps requested: “direct”: direct warp if config.makeDirect “psfMatched”: PSF-matched warp if config.makePsfMatched (dict).

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.

Notes

Obtain the list of input detectors from calExpList. Sort them by detector order (to ensure reproducibility). Then ensure all input lists are in the same sorted detector order.

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.
logLevel: A logging level constant.

Navigation

MakeWarpTask¶