CpFilterScanTask¶

class lsst.cp.pipe.CpFilterScanTask(**kwargs)¶

Bases: PipelineTask

Create filter scan from appropriate data.

This task constructs a filter scan from a sequence of flat exposures taken in the following manner:

A monochromator is set to a target wavelength.
An optional spectrum may be taken with the fiber spectrograph to provide an independent measure of the peak wavelength and bandpass.
A flat exposure is taken with a “reference filter,” usually a white-band or empty filter, that provides a baseline source brightness at the monochromator’s target wavelength.
A flat exposure is taken with the filter to be scanned.
Optional electrometer/photodiode data may also be taken during the two flat exposures to correct for source brightness variations.

From these pairs of exposures, we can determine the filter throughput by calculating the flux per second with the filter: \(F_filter(\lambda0) = median(f_amplifiers) / t_exposure\) And without: \(F_reference(\lambda0) = median(f_amplifiers) / t_exposure\) where the f_amplifiers are the per-amplifier statistics calculated by IsrTask. If the illumination source was perfectly stable, the filter throughput at that wavelength would simply be: \(throughput_raw(\lambda0) = F_filter / F_reference\)

We can correct for any illumination changes with the optional the electrometer measurements, E, which provide an independent measure of the incident flux for the two exposures, such that: \(throughput(\lambda0) = throughput_raw * E_reference / E_filter\)

Repeating this procedure at multiple monochromator settings builds up a catalog of throughput measurements across the filter bandpass. Additional differences can exist between the monochromator setting (retrieved here from the EFD) and the actual wavelengths of light that are permitted, so a matching CpMonochromatorScan can be generated to determine what the actual values of \(\lambda0\) observed were.

Attributes Summary

canMultiprocess

Methods Summary

`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`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.
`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`(inputExpHandles[, inputElectrometerHandles])	Construct filter scan from the header and visit info of processed exposures.
`runQuantum`(butlerQC, inputRefs, outputRefs)	Do butler IO and transform to provide in memory objects for tasks `run` method.
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.

Attributes Documentation

canMultiprocess: ClassVar[bool] = True¶

Methods Documentation

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

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

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:

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.

run(inputExpHandles, inputElectrometerHandles=None)¶

Construct filter scan from the header and visit info of processed exposures.

Parameters:

inputExpHandleslist [lsst.daf.butler.DeferredDatasetHandle]: Input list of exposure handles to combine.
inputElectrometerHandleslist [lsst.daf.butler.DeferredDatasetHandle], optional # noqa W505: Input list of electrometer/photodiode measurement handles to combine.

Returns:

resultslsst.pipe.base.Struct

The results struct containing:

outputData: Final combined filter scan, with a single table containing the measured throughput for all input filters at the various wavelength values indicated in the exposure’s observationReason (astropy.table.Table).

runQuantum(butlerQC: QuantumContext, inputRefs: InputQuantizedConnection, outputRefs: OutputQuantizedConnection) → None¶

Do butler IO and transform to provide in memory objects for tasks run method.

Parameters:

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

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.
logLevelint: A logging level constant.

Navigation

CpFilterScanTask¶