CalibCombineTask¶

class lsst.cp.pipe.CalibCombineTask(**kwargs)¶

Bases: PipelineTask

Task to combine calib exposures.

Attributes Summary

canMultiprocess

Methods Summary

`applyScale`(exposure[, bbox, scale])	Apply scale to input exposure.
`calibStats`(exp, calibrationType)	Measure bulk statistics for the calibration.
`combine`(target, expHandleList, expScaleList, ...)	Combine multiple images.
`combineHeaders`(expHandleList[, calib, ...])	Combine input headers to determine the set of common headers, supplemented by calibration inputs.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`getDimensions`(expHandleList)	Get dimensions of the inputs.
`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.
`getSize`(dimList)	Determine a consistent size, given a list of image sizes.
`getTaskDict`()	Get a dictionary of all tasks as a shallow copy.
`interpolateNans`(exp[, maskPlane])	Interpolate over NANs in the combined image.
`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`(inputExpHandles[, inputScales, inputDims])	Combine calib exposures for a single detector.
`runQuantum`(butlerQC, inputRefs, outputRefs)	Do butler IO and transform to provide in memory objects for tasks `run` method.
`setFilter`(exp, filterLabel)	Dummy function that will not assign a filter.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess: ClassVar[bool] = True¶

Methods Documentation

applyScale(exposure, bbox=None, scale=None)¶

Apply scale to input exposure.

This implementation applies a flux scaling: the input exposure is divided by the provided scale.

Parameters:

exposurelsst.afw.image.Exposure: Exposure to scale.
bboxlsst.geom.Box2I: BBox matching the segment of the exposure passed in.
scalefloat or list [float], optional: Constant scale to divide the exposure by.

calibStats(exp, calibrationType)¶

Measure bulk statistics for the calibration.

Parameters:

explsst.afw.image.Exposure: Exposure to calculate statistics for.
calibrationTypestr: Type of calibration to record in header.

combine(target, expHandleList, expScaleList, stats)¶

Combine multiple images.

Parameters:

targetlsst.afw.image.Exposure: Output exposure to construct.
expHandleListlist [lsst.daf.butler.DeferredDatasetHandle]: Input exposure handles to combine.
expScaleListlist [float]: List of scales to apply to each input image.
statslsst.afw.math.StatisticsControl: Control explaining how to combine the input images.

combineHeaders(expHandleList, calib=None, calibType='CALIB', scales=None, metadata=None)¶

Combine input headers to determine the set of common headers, supplemented by calibration inputs. The calibration header is set in-place.

Parameters:

expHandleListlist [lsst.daf.butler.DeferredDatasetHandle]: Input list of exposure handles to combine.
caliblsst.afw.image.Exposure, optional: Output calibration to construct headers for.
calibTypestr, optional: OBSTYPE the output should claim.
scaleslist [float], optional: Scale values applied to each input to record.
metadatalsst.daf.base.PropertyList, optional: Output metadata to add headers to.

Returns:

headerlsst.daf.base.PropertyList: Constructed header.

Raises:

RuntimeError: Raised if neither a calib nor a metadata was supplied.

emptyMetadata() → None¶: Empty (clear) the metadata for this Task and all sub-Tasks.

getDimensions(expHandleList)¶

Get dimensions of the inputs.

Parameters:

expHandleListlist [lsst.daf.butler.DeferredDatasetHandle]: Exposure handles to check the sizes of.

Returns:

width, heightint: Unique set of input dimensions.

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.

getSize(dimList)¶

Determine a consistent size, given a list of image sizes.

Parameters:

dimListlist [tuple [int, int]]: List of dimensions.

Returns:

width, heightint: Common dimensions.

Raises:

RuntimeError: If input dimensions are inconsistent.

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.

interpolateNans(exp, maskPlane='BAD')¶

Interpolate over NANs in the combined image.

NANs can result from masked areas on the CCD. We don’t want them getting into our science images, so we replace them with the median of the image.

Parameters:

explsst.afw.image.Exposure: Exp to check for NaNs.
maskPlanestr, optional: Mask plane to set where we have replaced a NAN.

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(inputExpHandles, inputScales=None, inputDims=None)¶

Combine calib exposures for a single detector.

Parameters:

inputExpHandleslist [lsst.daf.butler.DeferredDatasetHandle]

Input list of exposure handles to combine.

inputScalesdict [dict [dict [float]]], optional

Dictionary of scales, indexed by detector (int), amplifier (int), and exposure (int). Used for ‘inputExps’ scaling.

inputDimslist [dict]

List of dictionaries of input data dimensions/values. Each list entry should contain:

"exposure": exposure id value (int)
"detector": detector id value (int)

Returns:

resultslsst.pipe.base.Struct

The results struct containing:

outputData: Final combined exposure generated from the inputs (lsst.afw.image.Exposure).

Raises:

RuntimeError: Raised if no input data is found. Also raised if config.exposureScaling == InputList, and a necessary scale was not found.

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.

static setFilter(exp, filterLabel)¶

Dummy function that will not assign a filter.

Parameters:

explsst.afw.image.Exposure: Exposure to assign filter to.
filterLabellsst.afw.image.FilterLabel: Filter to assign.

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.

Navigation

CalibCombineTask¶