PhotonTransferCurveExtractTask¶

PhotonTransferCurveExtractTask constructs a photon transfer curve (PTC) dataset from a single pair of flat field exposures.

Processing summary¶

PhotonTransferCurveExtractTask runs these operations:

Pairs exposures together by either exposure time (the default) or by exposure id (in the case where the exposure time does not track with the observed flux).
Measures the mean, variances, and covariances from the difference of the pair of exposures.
Persists these results in a set of partial PTC datasets.

Python API summary¶

from lsst.cp.pipe.ptc.cpExtractPtcTask import PhotonTransferCurveExtractTask

classPhotonTransferCurveExtractTask(*, config=None, log=None, initInputs=None, **kwargs): Task to measure covariances from flat fields...

attributeconfig: Access configuration fields and retargetable subtasks.

methodrun(inputExp, inputDims): Measure covariances from difference of flat pairs...

Retargetable subtasks¶

No subtasks.

Configuration fields¶

binSize¶

Default: 1
Field type: int Field

Bin the image by this factor in both dimensions.

connections¶

Data type: lsst.pipe.base.config.Connections
Field type: ConfigField

Configurations describing the connections of the PipelineTask to datatypes

detectorMeasurementRegion¶

Default

'AMP'

Field type

str ChoiceField (optional)

Choices

'AMP': Amplifier of the detector.
'FULL': Full image.
None: Field is optional

Region of each exposure where to perform the calculations (amplifier or full image).

edgeMaskLevel¶

Default

'DETECTOR'

Field type

str ChoiceField (optional)

Choices

'DETECTOR': Mask only the edges of the full detector.
'AMP': Mask edges of each amplifier.
None: Field is optional

Mask edge pixels in which coordinate frame: DETECTOR or AMP?

maskNameList¶

Default: ['SUSPECT', 'BAD', 'NO_DATA', 'SAT']
Field type: str ListField

Mask list to exclude from statistics calculations.

matchByExposureId¶

Default: False
Field type: bool Field

Should exposures be matched by ID rather than exposure time?

maxMeanSignal¶

Default: {'ALL_AMPS': 1000000.0}
Field type: DictField
Key type: str
Value type: float

Maximum values (inclusive) of mean signal (in ADU) below which to consider, per amp. The same cut is applied to all amps if this dictionary is of the form {‘ALL_AMPS’: value}

maximumRangeCovariancesAstier¶

Default: 8
Field type: int Field

Maximum range of covariances as in Astier+19

minMeanSignal¶

Default: {'ALL_AMPS': 0.0}
Field type: DictField
Key type: str
Value type: float

Minimum values (inclusive) of mean signal (in ADU) per amp to use. The same cut is applied to all amps if this parameter [dict] is passed as {‘ALL_AMPS’: value}

minNumberGoodPixelsForCovariance¶

Default: 10000
Field type: int Field

Minimum number of acceptable good pixels per amp to calculate the covariances (via FFT or direclty).

nIterSigmaClipPtc¶

Default: 3
Field type: int Field

Number of sigma-clipping iterations for afwMath.StatisticsControl()

nSigmaClipPtc¶

Default: 5.5
Field type: float Field

Sigma cut for afwMath.StatisticsControl()

numEdgeSuspect¶

Default: 0
Field type: int Field

Number of edge pixels to be flagged as untrustworthy.

saveLogOutput¶

Default: True
Field type: bool Field

Flag to enable/disable saving of log output for a task, enabled by default.

saveMetadata¶

Default: True
Field type: bool Field

Flag to enable/disable metadata saving for a task, enabled by default.

thresholdDiffAfwVarVsCov00¶

Default: 1.0
Field type: float Field

If the absolute fractional differece between afwMath.VARIANCECLIP and Cov00 for a region of a difference image is greater than this threshold (percentage), a warning will be issued.

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