PhotonTransferCurveExtractTask¶

class lsst.cp.pipe.PhotonTransferCurveExtractTask(*, config=None, log=None, initInputs=None, **kwargs)¶

Bases: lsst.pipe.base.PipelineTask, lsst.pipe.base.CmdLineTask

Task to measure covariances from flat fields.

This task receives as input a list of flat-field images (flats), and sorts these flats in pairs taken at the same time (if there’s a different number of flats, those flats are discarded). The mean, variance, and covariances are measured from the difference of the flat pairs at a given time. The variance is calculated via afwMath, and the covariance via the methods in Astier+19 (appendix A). In theory, var = covariance[0,0]. This should be validated, and in the future, we may decide to just keep one (covariance).

The measured covariances at a particular time (along with other quantities such as the mean) are stored in a PTC dataset object (PhotonTransferCurveDataset), which gets partially filled. The number of partially-filled PTC dataset objects will be less than the number of input exposures, but gen3 requires/assumes that the number of input dimensions matches bijectively the number of output dimensions. Therefore, a number of “dummy” PTC dataset are inserted in the output list that has the partially-filled PTC datasets with the covariances. This output list will be used as input of PhotonTransferCurveSolveTask, which will assemble the multiple PhotonTransferCurveDataset into a single one in order to fit the measured covariances as a function of flux to a particular model.

Astier+19: “The Shape of the Photon Transfer Curve of CCD sensors”, arXiv:1905.08677.

Attributes Summary

canMultiprocess

Methods Summary

`applyOverrides`(config)	A hook to allow a task to change the values of its config after the camera-specific overrides are loaded but before any command-line overrides are applied.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`getAllSchemaCatalogs`()	Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
`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.
`getResourceConfig`()	Return resource configuration for this task.
`getSchemaCatalogs`()	Get the schemas generated by this task.
`getTaskDict`()	Get a dictionary of all tasks as a shallow copy.
`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.
`measureMeanVarCov`(exposure1, exposure2[, …])	Calculate the mean of each of two exposures and the variance and covariance of their difference.
`parseAndRun`([args, config, log, doReturnResults])	Parse an argument list and run the command.
`run`(inputExp, inputDims)	Measure covariances from difference of flat pairs
`runQuantum`(butlerQC, inputRefs, outputRefs)	Ensure that the input and output dimensions are passed along.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.
`writeConfig`(butler[, clobber, doBackup])	Write the configuration used for processing the data, or check that an existing one is equal to the new one if present.
`writeMetadata`(dataRef)	Write the metadata produced from processing the data.
`writePackageVersions`(butler[, clobber, …])	Compare and write package versions.
`writeSchemas`(butler[, clobber, doBackup])	Write the schemas returned by `lsst.pipe.base.Task.getAllSchemaCatalogs`.

Attributes Documentation

canMultiprocess = True¶

Methods Documentation

classmethod applyOverrides(config)¶

A hook to allow a task to change the values of its config after the camera-specific overrides are loaded but before any command-line overrides are applied.

Parameters:	config : instance of task’s `ConfigClass` Task configuration.

Notes

This is necessary in some cases because the camera-specific overrides may retarget subtasks, wiping out changes made in ConfigClass.setDefaults. See LSST Trac ticket #2282 for more discussion.

Warning

This is called by CmdLineTask.parseAndRun; other ways of constructing a config will not apply these overrides.

emptyMetadata()¶: Empty (clear) the metadata for this Task and all sub-Tasks.

getAllSchemaCatalogs()¶

Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.

Returns:	schemacatalogs : `dict` Keys are butler dataset type, values are a empty catalog (an instance of the appropriate `lsst.afw.table` Catalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.

Notes

This method may be called on any task in the hierarchy; it will return the same answer, regardless.

The default implementation should always suffice. If your subtask uses schemas the override Task.getSchemaCatalogs, not this method.

getFullMetadata()¶

Get metadata for all tasks.

Returns:	metadata : `lsst.daf.base.PropertySet` The `PropertySet` 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()¶

Get the task name as a hierarchical name including parent task names.

Returns:	fullName : `str` 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()¶

Get the name of the task.

Returns:	taskName : `str` Name of the task.

See also

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implementation returns an empty dict.

This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.

Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.

getTaskDict()¶

Get a dictionary of all tasks as a shallow copy.

Returns:	taskDict : `dict` Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

classmethod makeField(doc)¶

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:	doc : `str` Help text for the field.
Returns:	configurableField : `lsst.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, **keyArgs)¶

Create a subtask as a new instance as the name attribute of this task.

Parameters:	name : `str` 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.

measureMeanVarCov(exposure1, exposure2, region=None, covAstierRealSpace=False)¶

Calculate the mean of each of two exposures and the variance and covariance of their difference. The variance is calculated via afwMath, and the covariance via the methods in Astier+19 (appendix A). In theory, var = covariance[0,0]. This should be validated, and in the future, we may decide to just keep one (covariance).

Parameters:

exposure1 : lsst.afw.image.exposure.ExposureF: First exposure of flat field pair.
exposure2 : lsst.afw.image.exposure.ExposureF: Second exposure of flat field pair.
region : lsst.geom.Box2I, optional: Region of each exposure where to perform the calculations (e.g, an amplifier).
covAstierRealSpace : bool, optional: Should the covariannces in Astier+19 be calculated in real space or via FFT? See Appendix A of Astier+19.

Returns:

mu : float or NaN

0.5*(mu1 + mu2), where mu1, and mu2 are the clipped means of the regions in both exposures. If either mu1 or m2 are NaN’s, the returned value is NaN.

varDiff : float or NaN

Half of the clipped variance of the difference of the regions inthe two input exposures. If either mu1 or m2 are NaN’s, the returned value is NaN.

covDiffAstier : list or NaN

List with tuples of the form (dx, dy, var, cov, npix), where:

dx : int: Lag in x
dy : int: Lag in y
var : float: Variance at (dx, dy).
cov : float: Covariance at (dx, dy).
nPix : int: Number of pixel pairs used to evaluate var and cov.

If either mu1 or m2 are NaN’s, the returned value is NaN.

classmethod parseAndRun(args=None, config=None, log=None, doReturnResults=False)¶

Parse an argument list and run the command.

Parameters:

args : list, optional: List of command-line arguments; if None use sys.argv.
config : lsst.pex.config.Config-type, optional: Config for task. If None use Task.ConfigClass.
log : logging.Logger-type, optional: Log. If None use the default log.
doReturnResults : bool, optional: If True, return the results of this task. Default is False. This is only intended for unit tests and similar use. It can easily exhaust memory (if the task returns enough data and you call it enough times) and it will fail when using multiprocessing if the returned data cannot be pickled.

Returns:

struct : lsst.pipe.base.Struct

Fields are:

argumentParser: the argument parser (lsst.pipe.base.ArgumentParser).
parsedCmd: the parsed command returned by the argument parser’s parse_args method (argparse.Namespace).
taskRunner: the task runner used to run the task (an instance of Task.RunnerClass).
resultList: results returned by the task runner’s run method, one entry per invocation (list). This will typically be a list of Struct, each containing at least an exitStatus integer (0 or 1); see Task.RunnerClass (TaskRunner by default) for more details.

Notes

Calling this method with no arguments specified is the standard way to run a command-line task from the command-line. For an example see pipe_tasks bin/makeSkyMap.py or almost any other file in that directory.

If one or more of the dataIds fails then this routine will exit (with a status giving the number of failed dataIds) rather than returning this struct; this behaviour can be overridden by specifying the --noExit command-line option.

run(inputExp, inputDims)¶

Measure covariances from difference of flat pairs

Parameters:	inputExp : `dict` [`float`, `list` [`ExposureF`]] Dictionary that groups flat-field exposures that have the same exposure time (seconds). inputDims : `list` List of exposure IDs.
Returns:	results : `lsst.pipe.base.Struct` The results struct containing: `outputCovariances` A list containing the per-pair PTC measurements (`list` [`lsst.ip.isr.PhotonTransferCurveDataset`])

runQuantum(butlerQC, inputRefs, outputRefs)¶

Ensure that the input and output dimensions are passed along.

Parameters:	butlerQC : `ButlerQuantumContext` Butler to operate on. inputRefs : `InputQuantizedConnection` Input data refs to load. ouptutRefs : `OutputQuantizedConnection` Output data refs to persist.

timer(name, logLevel=10)¶

Context manager to log performance data for an arbitrary block of code.

Parameters:	name : `str` Name of code being timed; data will be logged using item name: `Start` and `End`. logLevel A `logging` level constant.

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PhotonTransferCurveExtractTask¶