CpCtiSolveTask

class lsst.cp.pipe.CpCtiSolveTask(**kwargs)

Bases: lsst.pipe.base.PipelineTask

Combine CTI measurements to a final calibration.

This task uses the extended pixel edge response (EPER) method as described by Snyder et al. 2021, Journal of Astronimcal Telescopes, Instruments, and Systems, 7, 048002. doi:10.1117/1.JATIS.7.4.048002

Attributes Summary

canMultiprocess

Methods Summary

debugView(ampName, signal, test) Debug method for global CTI test value.
emptyMetadata() Empty (clear) the metadata for this Task and all sub-Tasks.
findTraps(inputMeasurements, calib, detector) Solve for serial trap parameters.
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.
run(inputMeasurements, camera, inputDims) Solve for charge transfer inefficiency from overscan measurements.
runQuantum(butlerQC, inputRefs, outputRefs) Method to do butler IO and or transforms to provide in memory objects for tasks run method
solveGlobalCti(inputMeasurements, calib, …) Solve for global CTI constant.
solveLocalOffsets(inputMeasurements, calib, …) Solve for local (pixel-to-pixel) electronic offsets.
timer(name, logLevel) Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess = True

Methods Documentation

debugView(ampName, signal, test)

Debug method for global CTI test value.

Parameters:
ampName : str

Name of the amp for plot title.

signal : list [float]

Image means for the input exposures.

test : list [float]

CTI test value to plot.
emptyMetadata() → None

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

findTraps(inputMeasurements, calib, detector)

Solve for serial trap parameters.

Parameters:
inputMeasurements : list [dict]

List of overscan measurements from each input exposure. Each dictionary is nested within a top level ‘CTI’ key, with measurements organized by amplifier name, containing keys:

"FIRST_MEAN"

Mean value of first image column (float).

"LAST_MEAN"

Mean value of last image column (float).

"IMAGE_MEAN"

Mean value of the entire image region (float).

"OVERSCAN_COLUMNS"

List of overscan column indicies (list [int]).

"OVERSCAN_VALUES"

List of overscan column means (list [float]).

calib : lsst.ip.isr.DeferredChargeCalib

Calibration to populate with values.

detector : lsst.afw.cameraGeom.Detector

Detector object containing the geometry information for the amplifiers.
Returns:
calib : lsst.ip.isr.DeferredChargeCalib

Populated calibration.
Raises:
RuntimeError

Raised if no data remains after flux filtering.

Notes

The original CTISIM code uses a data model in which the “overscan” consists of the standard serial overscan bbox with the values for the last imaging data column prepended to that list. This version of the code keeps the overscan and imaging sections separate, and so a -1 offset is needed to ensure that the same columns are used for fitting between this code and CTISIM. This offset removes that last imaging data column from the count.

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.

run(inputMeasurements, camera, inputDims)

Solve for charge transfer inefficiency from overscan measurements.

Parameters:
inputMeasurements : list [dict]

List of overscan measurements from each input exposure. Each dictionary is nested within a top level ‘CTI’ key, with measurements organized by amplifier name, containing keys:

"FIRST_MEAN"

Mean value of first image column (float).

"LAST_MEAN"

Mean value of last image column (float).

"IMAGE_MEAN"

Mean value of the entire image region (float).

"OVERSCAN_COLUMNS"

List of overscan column indicies (list [int]).

"OVERSCAN_VALUES"

List of overscan column means (list [float]).

camera : lsst.afw.cameraGeom.Camera

Camera geometry to use to find detectors.

inputDims : list [dict]

List of input dimensions from each input exposure.
Returns:
results : lsst.pipe.base.Struct

Result struct containing:

outputCalib

Final CTI calibration data (lsst.ip.isr.DeferredChargeCalib).
Raises:
RuntimeError

Raised if data from multiple detectors are passed in.
runQuantum(butlerQC, inputRefs, outputRefs)

Method to do butler IO and or transforms to provide in memory objects for tasks run method

Parameters:
butlerQC : ButlerQuantumContext

A butler which is specialized to operate in the context of a lsst.daf.butler.Quantum.

inputRefs : InputQuantizedConnection

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.

outputRefs : OutputQuantizedConnection

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.
solveGlobalCti(inputMeasurements, calib, detector)

Solve for global CTI constant.

This method solves for the mean global CTI, b.

Parameters:
inputMeasurements : list [dict]

List of overscan measurements from each input exposure. Each dictionary is nested within a top level ‘CTI’ key, with measurements organized by amplifier name, containing keys:

"FIRST_MEAN"

Mean value of first image column (float).

"LAST_MEAN"

Mean value of last image column (float).

"IMAGE_MEAN"

Mean value of the entire image region (float).

"OVERSCAN_COLUMNS"

List of overscan column indicies (list [int]).

"OVERSCAN_VALUES"

List of overscan column means (list [float]).

calib : lsst.ip.isr.DeferredChargeCalib

Calibration to populate with values.

detector : lsst.afw.cameraGeom.Detector

Detector object containing the geometry information for the amplifiers.
Returns:
calib : lsst.ip.isr.DeferredChargeCalib

Populated calibration.
Raises:
RuntimeError

Raised if no data remains after flux filtering.

Notes

The original CTISIM code uses a data model in which the “overscan” consists of the standard serial overscan bbox with the values for the last imaging data column prepended to that list. This version of the code keeps the overscan and imaging sections separate, and so a -1 offset is needed to ensure that the same columns are used for fitting between this code and CTISIM. This offset removes that last imaging data column from the count.

solveLocalOffsets(inputMeasurements, calib, detector)

Solve for local (pixel-to-pixel) electronic offsets.

This method fits for au_L, the local electronic offset decay time constant, and A_L, the local electronic offset constant of proportionality.

Parameters:
inputMeasurements : list [dict]

List of overscan measurements from each input exposure. Each dictionary is nested within a top level ‘CTI’ key, with measurements organized by amplifier name, containing keys:

"FIRST_MEAN"

Mean value of first image column (float).

"LAST_MEAN"

Mean value of last image column (float).

"IMAGE_MEAN"

Mean value of the entire image region (float).

"OVERSCAN_COLUMNS"

List of overscan column indicies (list [int]).

"OVERSCAN_VALUES"

List of overscan column means (list [float]).

calib : lsst.ip.isr.DeferredChargeCalib

Calibration to populate with values.

detector : lsst.afw.cameraGeom.Detector

Detector object containing the geometry information for the amplifiers.
Returns:
calib : lsst.ip.isr.DeferredChargeCalib

Populated calibration.
Raises:
RuntimeError

Raised if no data remains after flux filtering.

Notes

The original CTISIM code (https://github.com/Snyder005/ctisim) uses a data model in which the “overscan” consists of the standard serial overscan bbox with the values for the last imaging data column prepended to that list. This version of the code keeps the overscan and imaging sections separate, and so a -1 offset is needed to ensure that the same columns are used for fitting between this code and CTISIM. This offset removes that last imaging data column from the count.

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