LinearitySolveTask¶
- class lsst.cp.pipe.LinearitySolveTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)¶
Bases:
PipelineTask
Fit the linearity from the PTC dataset.
Attributes Summary
Methods Summary
debugFit
(stepname, xVector, yVector, yModel, ...)Debug method for linearity fitting.
Empty (clear) the metadata for this Task and all sub-Tasks.
fillBadAmp
(linearizer, fitOrder, inputPtc, amp)Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
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
(inputPtc, dummy, camera, inputDims[, ...])Fit non-linearity to PTC data, returning the correct Linearizer object.
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
Methods Documentation
- debugFit(stepname, xVector, yVector, yModel, mask, ampName)¶
Debug method for linearity fitting.
- Parameters:
- stepname
str
A label to use to check if we care to debug at a given line of code.
- xVector
numpy.array
, (N,) The values to use as the independent variable in the linearity fit.
- yVector
numpy.array
, (N,) The values to use as the dependent variable in the linearity fit.
- yModel
numpy.array
, (N,) The values to use as the linearized result.
- mask
numpy.array
[bool
], (N,) , optional A mask to indicate which entries of
xVector
andyVector
to keep.- ampName
str
Amplifier name to lookup linearity correction values.
- stepname
- fillBadAmp(linearizer, fitOrder, inputPtc, amp)¶
- getFullMetadata() 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.
- metadata
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”.
- fullName
- getName() str ¶
Get the name of the task.
- Returns:
- taskName
str
Name of the task.
- taskName
See also
getFullName
Get the full name of the task.
- getTaskDict() dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]] ¶
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.
- taskDict
- classmethod makeField(doc: str) ConfigurableField ¶
Make a
lsst.pex.config.ConfigurableField
for this task.- Parameters:
- doc
str
Help text for the field.
- doc
- Returns:
- configurableField
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
- configurableField
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:
- 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
.
- name
Notes
The subtask must be defined by
Task.config.name
, an instance ofConfigurableField
orRegistryField
.
- run(inputPtc, dummy, camera, inputDims, inputPhotodiodeCorrection=None)¶
Fit non-linearity to PTC data, returning the correct Linearizer object.
- Parameters:
- inputPtc
lsst.ip.isr.PtcDataset
Pre-measured PTC dataset.
- dummy
lsst.afw.image.Exposure
The exposure used to select the appropriate PTC dataset. In almost all circumstances, one of the input exposures used to generate the PTC dataset is the best option.
- inputPhotodiodeCorrection
lsst.ip.isr.PhotodiodeCorrection
Pre-measured photodiode correction used in the case when applyPhotodiodeCorrection=True.
- camera
lsst.afw.cameraGeom.Camera
Camera geometry.
- inputDims
lsst.daf.butler.DataCoordinate
ordict
DataIds to use to populate the output calibration.
- inputPtc
- Returns:
- results
lsst.pipe.base.Struct
The results struct containing:
outputLinearizer
Final linearizer calibration (
lsst.ip.isr.Linearizer
).outputProvenance
Provenance data for the new calibration (
lsst.ip.isr.IsrProvenance
).
- results
Notes
This task currently fits only polynomial-defined corrections, where the correction coefficients are defined such that: \(corrImage = uncorrImage + \sum_i c_i uncorrImage^(2 + i)\) These \(c_i\) are defined in terms of the direct polynomial fit: \(meanVector ~ P(x=timeVector) = \sum_j k_j x^j\) such that \(c_(j-2) = -k_j/(k_1^j)\) in units of DN^(1-j) (c.f., Eq. 37 of 2003.05978). The
config.polynomialOrder
orconfig.splineKnots
define the maximum order of \(x^j\) to fit. As \(k_0\) and \(k_1\) are degenerate with bias level and gain, they are not included in the non-linearity correction.
- runQuantum(butlerQC, inputRefs, outputRefs)¶
Ensure that the input and output dimensions are passed along.
- Parameters:
- butlerQC
lsst.daf.butler.QuantumContext
Butler to operate on.
- inputRefs
lsst.pipe.base.InputQuantizedConnection
Input data refs to load.
- ouptutRefs
lsst.pipe.base.OutputQuantizedConnection
Output data refs to persist.
- butlerQC