CalibCombineTask

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

Bases: PipelineTask

Task to combine calib exposures.

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.
getDimensions(expHandleList)	Get dimensions of the inputs.
getSize(dimList)	Determine a consistent size, given a list of image sizes.
interpolateNans(exp[, maskPlane])	Interpolate over NANs in the combined image.
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.
setFlatSource(exp)	Set the flat source metadata.

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.

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.

getSize(dimList)

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

Parameters

dimListlist [tuple [int, int]]

List of dimensions.

Raises

RuntimeError

If input dimensions are inconsistent.

Returns

width, heightint

Common dimensions.

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 data.

Parameters

explsst.afw.image.Exposure

Exp to check for NaNs.

maskPlanestr, optional

Mask plane to set where we have replaced a NAN.

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.

setFlatSource(exp)

Set the flat source metadata.

Parameters

explsst.afw.image.Exposure

Exposure to set the flat source.