PlotPhotonTransferCurveTask¶

class lsst.cp.pipe.PlotPhotonTransferCurveTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)¶

Bases: PipelineTask

A class to plot the dataset from MeasurePhotonTransferCurveTask.

Parameters:

outDirstr, optional: Path to the output directory where the final PDF will be placed.
signalElectronsRelativeAfloat, optional: Signal value for relative systematic bias between different methods of estimating a_ij (Fig. 15 of Astier+19).
plotNormalizedCovariancesNumberOfBinsfloat, optional: Number of bins in plotNormalizedCovariancesNumber function (Fig. 8, 10., of Astier+19).

Notes

See DM-36388 for usage exammple.

Attributes Summary

canMultiprocess

Methods Summary

`ab_vs_dist`(aDict, bDict[, bRange])	Fig.
`binData`(x, y, binIndex[, wy])	Bin data (usually for display purposes).
`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.
`getTaskDict`()	Get a dictionary of all tasks as a shallow copy.
`indexForBins`(x, nBins)	Builds an index with regular binning.
`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.
`plotAcoeffsSum`(aDict, bDict)	Fig.
`plotCovariances`(mu, covs, covsModel, ...)	Plot covariances and models: Cov00, Cov10, Cov01.
`plotNormalizedCovariances`(i, j, inputMu, ...)	Plot C_ij/mu vs mu.
`plotRelativeBiasACoeffs`(aDict, aDictNoB, ...)	Fig.
`plot_a_b`(aDict, bDict[, bRange])	Fig.
`run`(inputPtcDataset[, camera])	Make the plots for the PTC task.
`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

static ab_vs_dist(aDict, bDict, bRange=4)¶

Fig. 13 of Astier+19.

Values of a and b arrays fits, averaged over amplifiers, as a function of distance.

Parameters:

aDictdict [numpy.array]: Dictionary keyed by amp names containing the fitted ‘a’ coefficients from the model in Eq. 20 of Astier+19 (if ptcFitType is FULLCOVARIANCE).
bDictdict [numpy.array]: Dictionary keyed by amp names containing the fitted ‘b’ coefficients from the model in Eq. 20 of Astier+19 (if ptcFitType is FULLCOVARIANCE).
bRangeint: Maximum lag for b arrays.

static binData(x, y, binIndex, wy=None)¶

Bin data (usually for display purposes).

Parameters:

xnumpy.array: Data to bin.
ynumpy.array: Data to bin.
binIdexlist: Bin number of each datum.
wynumpy.array: Inverse rms of each datum to use when averaging (the actual weight is wy**2).

Returns:

xbinnumpy.array: Binned data in x.
ybinnumpy.array: Binned data in y.
wybinnumpy.array: Binned weights in y, computed from wy’s in each bin.
sybinnumpy.array: Uncertainty on the bin average, considering actual scatter, and ignoring weights.

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

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.

static indexForBins(x, nBins)¶

Builds an index with regular binning. The result can be fed into binData.

Parameters:

xnumpy.array: Data to bin.
nBinsint: Number of bin.

Returns:

np.digitize(x, bins): numpy.array: Bin indices.

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.

static plotAcoeffsSum(aDict, bDict)¶

Fig. 14. of Astier+19

Cumulative sum of a_ij as a function of maximum separation. This plot displays the average over channels.

Parameters:

aDictdict [numpy.array]: Dictionary keyed by amp names containing the fitted ‘a’ coefficients from the model in Eq. 20 of Astier+19 (if ptcFitType is FULLCOVARIANCE).
bDictdict [numpy.array]: Dictionary keyed by amp names containing the fitted ‘b’ coefficients from the model in Eq. 20 of Astier+19 (if ptcFitType is FULLCOVARIANCE).

static plotCovariances(mu, covs, covsModel, covsWeights, covsNoB, covsModelNoB, covsWeightsNoB, gainDict, noiseDict, aDict, bDict)¶

Plot covariances and models: Cov00, Cov10, Cov01.

Figs. 6 and 7 of Astier+19

Parameters:

mudict [str, list]: Dictionary keyed by amp name with mean signal values.
covsdict [str, list]: Dictionary keyed by amp names containing a list of measued covariances per mean flux.
covsModeldict [str, list]: Dictionary keyed by amp names containinging covariances model (Eq. 20 of Astier+19) per mean flux.
covsWeightsdict [str, list]: Dictionary keyed by amp names containinging sqrt. of covariances weights.
covsNoBdict [str, list]: Dictionary keyed by amp names containing a list of measued covariances per mean flux (‘b’=0 in Astier+19).
covsModelNoBdict [str, list]: Dictionary keyed by amp names containing covariances model (with ‘b’=0 in Eq. 20 of Astier+19) per mean flux.
covsWeightsNoBdict [str, list]: Dictionary keyed by amp names containing sqrt. of covariances weights (‘b’ = 0 in Eq. 20 of Astier+19).
gainDictdict [str, float]: Dictionary keyed by amp names containing the gains in e-/ADU.
noiseDictdict [str, float]: Dictionary keyed by amp names containing the rms redout noise in e-.
aDictdict [str, numpy.array]: Dictionary keyed by amp names containing ‘a’ coefficients (Eq. 20 of Astier+19).
bDictdict [str, numpy.array]: Dictionary keyed by amp names containing ‘b’ coefficients (Eq. 20 of Astier+19).

plotNormalizedCovariances(i, j, inputMu, covs, covsModel, covsWeights, covsNoB, covsModelNoB, covsWeightsNoB, offset=0.004, numberOfBins=10, plotData=True, topPlot=False)¶

Plot C_ij/mu vs mu.

Figs. 8, 10, and 11 of Astier+19

Parameters:

iint: Covariance lag.
jint: Covariance lag.
inputMudict [str, list]: Dictionary keyed by amp name with mean signal values.
covsdict [str, list]: Dictionary keyed by amp names containing a list of measued covariances per mean flux.
covsModeldict [str, list]: Dictionary keyed by amp names containinging covariances model (Eq. 20 of Astier+19) per mean flux.
covsWeightsdict [str, list]: Dictionary keyed by amp names containinging sqrt. of covariances weights.
covsNoBdict [str, list]: Dictionary keyed by amp names containing a list of measued covariances per mean flux (‘b’=0 in Astier+19).
covsModelNoBdict [str, list]: Dictionary keyed by amp names containing covariances model (with ‘b’=0 in Eq. 20 of Astier+19) per mean flux.
covsWeightsNoBdict [str, list]: Dictionary keyed by amp names containing sqrt. of covariances weights (‘b’ = 0 in Eq. 20 of Astier+19).
expIdMaskdict [str, list]: Dictionary keyed by amp names containing the masked exposure pairs.
offsetfloat, optional: Constant offset factor to plot covariances in same panel (so they don’t overlap).
numberOfBinsint, optional: Number of bins for top and bottom plot.
plotDatabool, optional: Plot the data points?
topPlotbool, optional: Plot the top plot with the covariances, and the bottom plot with the model residuals?

static plotRelativeBiasACoeffs(aDict, aDictNoB, fullCovsModel, fullCovsModelNoB, signalElectrons, gainDict, maxr=None)¶

Fig. 15 in Astier+19.

Illustrates systematic bias from estimating ‘a’ coefficients from the slope of correlations as opposed to the full model in Astier+19.

Parameters:

aDictdict: Dictionary of ‘a’ matrices (Eq. 20, Astier+19), with amp names as keys.
aDictNoBdict: Dictionary of ‘a’ matrices (‘b’= 0 in Eq. 20, Astier+19), with amp names as keys.
fullCovsModeldict [str, list]: Dictionary keyed by amp names containing covariances model per mean flux.
fullCovsModelNoBdict [str, list]: Dictionary keyed by amp names containing covariances model (with ‘b’=0 in Eq. 20 of Astier+19) per mean flux.
signalElectronsfloat: Signal at which to evaluate the a_ij coefficients.
gainDictdict [str, float]: Dicgionary keyed by amp names with the gains in e-/ADU.
maxrint, optional: Maximum lag.

static plot_a_b(aDict, bDict, bRange=3)¶

Fig. 12 of Astier+19

Color display of a and b arrays fits, averaged over channels.

Parameters:

aDictdict [numpy.array]: Dictionary keyed by amp names containing the fitted ‘a’ coefficients from the model in Eq. 20 of Astier+19 (if ptcFitType is FULLCOVARIANCE).
bDictdict [numpy.array]: Dictionary keyed by amp names containing the fitted ‘b’ coefficients from the model in Eq. 20 of Astier+19 (if ptcFitType is FULLCOVARIANCE).
bRangeint: Maximum lag for b arrays.

run(inputPtcDataset, camera=None)¶

Make the plots for the PTC task.

Parameters:

inputPtcDatasetlsst.ip.isr.PhotonTransferCurveDataset: Output dataset from Photon Transfer Curve task.
cameralsst.afw.cameraGeom.Camera: Camera to use for camera geometry information.

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.

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.

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PlotPhotonTransferCurveTask¶