CrosstalkSolveTask¶

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

Bases: PipelineTask, CmdLineTask

Task to solve crosstalk from pixel ratios.

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.
`debugRatios`(stepname, ratios, i, j[, coeff, ...])	Utility function to examine the final CT ratio set.
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`filterCrosstalkCalib`(inCalib)	Apply valid constraints to the measured values.
`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.
`measureCrosstalkCoefficients`(ratios, ...)	Measure crosstalk coefficients from the ratios.
`parseAndRun`([args, config, log, doReturnResults])	Parse an argument list and run the command.
`run`(inputRatios[, inputFluxes, camera, ...])	Combine ratios to produce crosstalk coefficients.
`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: ClassVar[bool] = 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:

configinstance 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.

debugRatios(stepname, ratios, i, j, coeff=0.0, valid=False)¶

Utility function to examine the final CT ratio set.

Parameters:

stepnamestr: State of processing to view.
ratiosdict [dict [numpy.ndarray]]: Array of measured CT ratios, indexed by source/victim amplifier. These arrays are one-dimensional.
istr: Index of the source amplifier.
jstr: Index of the target amplifier.
coefffloat, optional: Coefficient calculated to plot along with the simple mean.
validbool, optional: Validity to be added to the plot title.

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

static filterCrosstalkCalib(inCalib)¶

Apply valid constraints to the measured values.

Any measured coefficient that is determined to be invalid is set to zero, and has the error set to nan. The validation is determined by checking that the measured coefficient is larger than the calculated standard error of the mean.

Parameters:

inCaliblsst.ip.isr.CrosstalkCalib: Input calibration to filter.

Returns:

outCaliblsst.ip.isr.CrosstalkCalib: Filtered calibration.

getAllSchemaCatalogs() → Dict[str, Any]¶

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

Returns:

schemacatalogsdict: 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() → 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

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() → Dict[str, ReferenceType[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.

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.

measureCrosstalkCoefficients(ratios, ordering, rejIter, rejSigma)¶

Measure crosstalk coefficients from the ratios.

Given a list of ratios for each target/source amp combination, we measure a sigma clipped mean and error.

The coefficient errors returned are the standard deviation of the final set of clipped input ratios.

Parameters:

ratiosdict [dict [numpy.ndarray]]: Catalog of arrays of ratios. The ratio arrays are one-dimensional
orderinglist [str] or None: List to use as a mapping between amplifier names (the elements of the list) and their position in the output calibration (the matching index of the list). If no ordering is supplied, the order of the keys in the ratio catalog is used.
rejIterint: Number of rejection iterations.
rejSigmafloat: Rejection threshold (sigma).

Returns:

caliblsst.ip.isr.CrosstalkCalib: The output crosstalk calibration.

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

Parse an argument list and run the command.

Parameters:

argslist, optional: List of command-line arguments; if None use sys.argv.
configlsst.pex.config.Config-type, optional: Config for task. If None use Task.ConfigClass.
loglogging.Logger-type, optional: Log. If None use the default log.
doReturnResultsbool, 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:

structlsst.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(inputRatios, inputFluxes=None, camera=None, inputDims=None, outputDims=None)¶

Combine ratios to produce crosstalk coefficients.

Parameters:

inputRatioslist [dict [dict [dict [dict [list]]]]]: A list of nested dictionaries of ratios indexed by target and source chip, then by target and source amplifier.
inputFluxeslist [dict [dict [list]]]: A list of nested dictionaries of source pixel fluxes, indexed by source chip and amplifier.
cameralsst.afw.cameraGeom.Camera: Input camera.
inputDimslist [lsst.daf.butler.DataCoordinate]: DataIds to use to construct provenance.
outputDimslist [lsst.daf.butler.DataCoordinate]: DataIds to use to populate the output calibration.

Returns:

resultslsst.pipe.base.Struct

The results struct containing:

outputCrosstalk: Final crosstalk calibration (lsst.ip.isr.CrosstalkCalib).
outputProvenance: Provenance data for the new calibration (lsst.ip.isr.IsrProvenance).

Raises:

RuntimeError: Raised if the input data contains multiple target detectors.

runQuantum(butlerQC, inputRefs, outputRefs)¶

Ensure that the input and output dimensions are passed along.

Parameters:

butlerQClsst.daf.butler.butlerQuantumContext.ButlerQuantumContext: Butler to operate on.
inputRefslsst.pipe.base.connections.InputQuantizedConnection: Input data refs to load.
ouptutRefslsst.pipe.base.connections.OutputQuantizedConnection: Output data refs to persist.

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.

Navigation

CrosstalkSolveTask¶