CrosstalkSolveTask

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

Bases: lsst.pipe.base.PipelineTask

Task to solve crosstalk from pixel ratios.

Attributes Summary

canMultiprocess

Methods Summary

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.
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.

Attributes Documentation

canMultiprocess = True

Methods Documentation

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

Utility function to examine the final CT ratio set.

Parameters:
stepname : str

State of processing to view.

ratios : dict [dict [numpy.ndarray]]

Array of measured CT ratios, indexed by source/victim amplifier. These arrays are one-dimensional.

i : str

Index of the source amplifier.

j : str

Index of the target amplifier.

coeff : float, optional

Coefficient calculated to plot along with the simple mean.

valid : bool, 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:
inCalib : lsst.ip.isr.CrosstalkCalib

Input calibration to filter.

Returns:
outCalib : lsst.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:
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() → lsst.pipe.base._task_metadata.TaskMetadata

Get metadata for all tasks.

Returns:
metadata : TaskMetadata

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:
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() → str

Get the name of the task.

Returns:
taskName : str

Name of the task.

See also

getFullName
getResourceConfig() → Optional[ResourceConfig]

Return resource configuration for this task.

Returns:
Object of type ResourceConfig or None if resource
configuration is not defined for this task.
getSchemaCatalogs() → Dict[str, Any]

Get the schemas generated by this task.

Returns:
schemaCatalogs : dict

Keys are butler dataset type, values are an empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for this 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, weakref]

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: str) → lsst.pex.config.configurableField.ConfigurableField

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: str, **keyArgs) → None

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.

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:
ratios : dict [dict [numpy.ndarray]]

Catalog of arrays of ratios. The ratio arrays are one-dimensional

ordering : list [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.

rejIter : int

Number of rejection iterations.

rejSigma : float

Rejection threshold (sigma).

Returns:
calib : lsst.ip.isr.CrosstalkCalib

The output crosstalk calibration.

run(inputRatios, inputFluxes=None, camera=None, inputDims=None, outputDims=None)

Combine ratios to produce crosstalk coefficients.

Parameters:
inputRatios : list [dict [dict [dict [dict [list]]]]]

A list of nested dictionaries of ratios indexed by target and source chip, then by target and source amplifier.

inputFluxes : list [dict [dict [list]]]

A list of nested dictionaries of source pixel fluxes, indexed by source chip and amplifier.

camera : lsst.afw.cameraGeom.Camera

Input camera.

inputDims : list [lsst.daf.butler.DataCoordinate]

DataIds to use to construct provenance.

outputDims : list [lsst.daf.butler.DataCoordinate]

DataIds to use to populate the output calibration.

Returns:
results : lsst.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:
butlerQC : lsst.daf.butler.butlerQuantumContext.ButlerQuantumContext

Butler to operate on.

inputRefs : lsst.pipe.base.InputQuantizedConnection

Input data refs to load.

ouptutRefs : lsst.pipe.base.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:
name : str

Name of code being timed; data will be logged using item name: Start and End.

logLevel

A logging level constant.

See also

timer.logInfo

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time