CfhtIsrTask¶

class lsst.obs.cfht.cfhtIsrTask.CfhtIsrTask(*args, **kwargs)¶

Bases: lsst.ip.isr.isrTask.IsrTask

Attributes Summary

canMultiprocess

Methods Summary

`addDistortionModel`(exposure, camera)	!Update the WCS in exposure with a distortion model based on camera geometry
`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.
`attachTransmissionCurve`(exposure[, …])	Attach a TransmissionCurve to an Exposure, given separate curves for different components.
`biasCorrection`(exposure, biasExposure)	!Apply bias correction in place
`brighterFatterCorrection`(exposure, kernel, …)	Apply brighter fatter correction in place for the image
`convertIntToFloat`(exposure)	Convert an exposure from uint16 to float, set variance plane to 1 and mask plane to 0
`darkCorrection`(exposure, darkExposure[, invert])	!Apply dark correction in place
`doLinearize`(detector)	!Is linearization wanted for this detector?
`emptyMetadata`()	Empty (clear) the metadata for this Task and all sub-Tasks.
`flatContext`(exp, flat[, dark])	Context manager that applies and removes flats and darks, if the task is configured to apply them.
`flatCorrection`(exposure, flatExposure[, invert])	!Apply flat correction in place
`gainContext`(exp, image, apply)	Context manager that applies and removes gain
`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.
`getIsrExposure`(dataRef, datasetType[, immediate])	!Retrieve a calibration dataset for removing instrument signature
`getName`()	Get the name of the 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.
`maskAndInterpDefect`(ccdExposure, defectBaseList)	!Mask defects using mask plane “BAD” and interpolate over them, in place
`maskAndInterpNan`(exposure)	!Mask NaNs using mask plane “UNMASKEDNAN” and interpolate over them, in place
`overscanCorrection`(exposure, amp)	Apply overscan correction, in-place
`parseAndRun`([args, config, log, doReturnResults])	Parse an argument list and run the command.
`readIsrData`(dataRef, rawExposure)	!Retrieve necessary frames for instrument signature removal @param[in] dataRef a daf.persistence.butlerSubset.ButlerDataRef of the detector data to be processed @param[in] rawExposure a reference raw exposure that will later be corrected with the retrieved calibration data; should not be modified in this method.
`run`(ccdExposure[, bias, linearizer, dark, …])	Perform instrument signature removal on an exposure
`runDataRef`(sensorRef)	Perform instrument signature removal on a ButlerDataRef of a Sensor
`saturationDetection`(exposure, amp)	!Detect saturated pixels and mask them using mask plane config.saturatedMaskName, in place
`saturationInterpolation`(ccdExposure)	!Interpolate over saturated pixels, in place
`setValidPolygonIntersect`(ccdExposure, fpPolygon)	!Set the valid polygon as the intersection of fpPolygon and the ccd corners
`suspectDetection`(exposure, amp)	!Detect suspect pixels and mask them using mask plane config.suspectMaskName, in place
`timer`(name[, logLevel])	Context manager to log performance data for an arbitrary block of code.
`updateVariance`(ampExposure, amp[, overscanImage])	Set the variance plane using the amplifier gain and read noise
`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 = True¶

Methods Documentation

addDistortionModel(exposure, camera)¶

!Update the WCS in exposure with a distortion model based on camera geometry

Add a model for optical distortion based on geometry found in camera and the exposure’s detector. The raw input exposure is assumed have a TAN WCS that has no compensation for optical distortion. Two other possibilities are: - The raw input exposure already has a model for optical distortion,

as is the case for raw DECam data. In that case you should set config.doAddDistortionModel False.

The raw input exposure has a model for distortion, but it has known

deficiencies severe enough to be worth fixing (e.g. because they cause problems for fitting a better WCS). In that case you should override this method with a version suitable for your raw data.

@param[in,out] exposure exposure to process; must include a Detector and a WCS;: the WCS of the exposure is modified in place

@param[in] camera camera geometry; an lsst.afw.cameraGeom.Camera

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:	config : instance 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.

attachTransmissionCurve(exposure, opticsTransmission=None, filterTransmission=None, sensorTransmission=None, atmosphereTransmission=None)¶

Attach a TransmissionCurve to an Exposure, given separate curves for different components.

Parameters:

exposure : lsst.afw.image.Exposure: Exposure object to modify by attaching the product of all given TransmissionCurves in post-assembly trimmed detector coordinates. Must have a valid Detector attached that matches the detector associated with sensorTransmission.
opticsTransmission : lsst.afw.image.TransmissionCurve: A TransmissionCurve that represents the throughput of the optics, to be evaluated in focal-plane coordinates.
filterTransmission : lsst.afw.image.TransmissionCurve: A TransmissionCurve that represents the throughput of the filter itself, to be evaluated in focal-plane coordinates.
sensorTransmission : lsst.afw.image.TransmissionCurve: A TransmissionCurve that represents the throughput of the sensor itself, to be evaluated in post-assembly trimmed detector coordinates.
atmosphereTransmission : lsst.afw.image.TransmissionCurve: A TransmissionCurve that represents the throughput of the atmosphere, assumed to be spatially constant.
All ``TransmissionCurve`` arguments are optional; if none are provided,
the attached ``TransmissionCurve`` will have unit transmission
everywhere.

Returns:

combined : lsst.afw.image.TransmissionCurve: The TransmissionCurve attached to the exposure.

biasCorrection(exposure, biasExposure)¶

!Apply bias correction in place

@param[in,out] exposure exposure to process @param[in] biasExposure bias exposure of same size as exposure

brighterFatterCorrection(exposure, kernel, maxIter, threshold, applyGain)¶

Apply brighter fatter correction in place for the image

This correction takes a kernel that has been derived from flat field images to redistribute the charge. The gradient of the kernel is the deflection field due to the accumulated charge.

Given the original image I(x) and the kernel K(x) we can compute the corrected image Ic(x) using the following equation:

Ic(x) = I(x) + 0.5*d/dx(I(x)*d/dx(int( dy*K(x-y)*I(y))))

To evaluate the derivative term we expand it as follows:

0.5 * ( d/dx(I(x))*d/dx(int(dy*K(x-y)*I(y))) + I(x)*d^2/dx^2(int(dy* K(x-y)*I(y))) )

Because we use the measured counts instead of the incident counts we apply the correction iteratively to reconstruct the original counts and the correction. We stop iterating when the summed difference between the current corrected image and the one from the previous iteration is below the threshold. We do not require convergence because the number of iterations is too large a computational cost. How we define the threshold still needs to be evaluated, the current default was shown to work reasonably well on a small set of images. For more information on the method see DocuShare Document-19407.

The edges as defined by the kernel are not corrected because they have spurious values due to the convolution.

convertIntToFloat(exposure)¶: Convert an exposure from uint16 to float, set variance plane to 1 and mask plane to 0

darkCorrection(exposure, darkExposure, invert=False)¶

!Apply dark correction in place

@param[in,out] exposure exposure to process @param[in] darkExposure dark exposure of same size as exposure @param[in] invert if True, remove the dark from an already-corrected image

doLinearize(detector)¶

!Is linearization wanted for this detector?

Checks config.doLinearize and the linearity type of the first amplifier.

@param[in] detector detector information (an lsst.afw.cameraGeom.Detector)

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

flatContext(exp, flat, dark=None)¶: Context manager that applies and removes flats and darks, if the task is configured to apply them.

flatCorrection(exposure, flatExposure, invert=False)¶

!Apply flat correction in place

@param[in,out] exposure exposure to process @param[in] flatExposure flatfield exposure same size as exposure @param[in] invert if True, unflatten an already-flattened image instead.

gainContext(exp, image, apply)¶: Context manager that applies and removes gain

getAllSchemaCatalogs()¶

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()¶

Get metadata for all tasks.

Returns:	metadata : `lsst.daf.base.PropertySet` The `PropertySet` 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()¶

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”.

getIsrExposure(dataRef, datasetType, immediate=True)¶

!Retrieve a calibration dataset for removing instrument signature

@param[in] dataRef data reference for exposure @param[in] datasetType type of dataset to retrieve (e.g. ‘bias’, ‘flat’) @param[in] immediate if True, disable butler proxies to enable error

handling within this routine

@return exposure

getName()¶

Get the name of the task.

Returns:	taskName : `str` Name of the task.

See also

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implemenation 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()¶

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)¶

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("a brief description of what this task does")

makeSubtask(name, **keyArgs)¶

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 pex_config ConfigurableField or RegistryField.

maskAndInterpDefect(ccdExposure, defectBaseList)¶

!Mask defects using mask plane “BAD” and interpolate over them, in place

@param[in,out] ccdExposure exposure to process @param[in] defectBaseList a list of defects to mask and interpolate

@warning: call this after CCD assembly, since defects may cross amplifier boundaries

maskAndInterpNan(exposure)¶

!Mask NaNs using mask plane “UNMASKEDNAN” and interpolate over them, in place

We mask and interpolate over all NaNs, including those that are masked with other bits (because those may or may not be interpolated over later, and we want to remove all NaNs). Despite this behaviour, the “UNMASKEDNAN” mask plane is used to preserve the historical name.

@param[in,out] exposure exposure to process

overscanCorrection(exposure, amp)¶

Apply overscan correction, in-place

Parameters:	exposure : `lsst.afw.image.Exposure` Exposure to process; must include both data and bias regions. amp : `lsst.afw.table.AmpInfoRecord` Amplifier device data.

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

Parse an argument list and run the command.

Parameters:

args : list, optional: List of command-line arguments; if None use sys.argv.
config : lsst.pex.config.Config-type, optional: Config for task. If None use Task.ConfigClass.
log : lsst.log.Log-type, optional: Log. If None use the default log.
doReturnResults : bool, 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:

struct : lsst.pipe.base.Struct

Fields are:

argumentParser: the argument parser.
parsedCmd: the parsed command returned by the argument parser’s lsst.pipe.base.ArgumentParser.parse_args method.
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.

This will typically be a list of None unless doReturnResults is True; see Task.RunnerClass (TaskRunner by default) for more information.

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.

readIsrData(dataRef, rawExposure)¶

!Retrieve necessary frames for instrument signature removal @param[in] dataRef a daf.persistence.butlerSubset.ButlerDataRef

of the detector data to be processed

@param[in] rawExposure a reference raw exposure that will later be

corrected with the retrieved calibration data; should not be modified in this method.

@return a pipeBase.Struct with fields containing kwargs expected by run()

bias: exposure of bias frame
dark: exposure of dark frame
flat: exposure of flat field
defects: list of detects
fringeStruct: a pipeBase.Struct with field fringes containing

exposure of fringe frame or list of fringe exposure

run(ccdExposure, bias=None, linearizer=None, dark=None, flat=None, defects=None, fringes=None, bfKernel=None, camera=None, **kwds)¶

Perform instrument signature removal on an exposure

Steps include: - Detect saturation, apply overscan correction, bias, dark and flat - Perform CCD assembly - Interpolate over defects, saturated pixels and all NaNs - Persist the ISR-corrected exposure as “postISRCCD” if

config.doWrite is True

Parameters:

ccdExposure : lsst.afw.image.Exposure: Detector data.
bias : lsst.afw.image.exposure: Exposure of bias frame.
linearizer : lsst.ip.isr.LinearizeBase callable: Linearizing functor; a subclass of lsst.ip.isr.LinearizeBase.
dark : lsst.afw.image.exposure: Exposure of dark frame.
flat : lsst.afw.image.exposure: Exposure of flatfield.
defects : list: list of detects
fringes : lsst.afw.image.exposure or list of lsst.afw.image.exposure: exposure of fringe frame or list of fringe exposure
bfKernel : None: kernel used for brighter-fatter correction; currently unsupported
camera : lsst.afw.cameraGeom.Camera: Camera geometry, used by addDistortionModel.
**kwds : dict: additional kwargs forwarded to IsrTask.run.

Returns:

struct : lsst.pipe.base.Struct with fields:

exposure: the exposure after application of ISR

runDataRef(sensorRef)¶

Perform instrument signature removal on a ButlerDataRef of a Sensor

Read in necessary detrending/isr/calibration data
Process raw exposure in run()
Persist the ISR-corrected exposure as “postISRCCD” if config.doWrite is True

Parameters:	sensorRef : `daf.persistence.butlerSubset.ButlerDataRef` DataRef of the detector data to be processed
Returns:	result : `pipeBase.Struct` Struct contains field “exposure,” which is the exposure after application of ISR

saturationDetection(exposure, amp)¶

!Detect saturated pixels and mask them using mask plane config.saturatedMaskName, in place

@param[in,out] exposure exposure to process; only the amp DataSec is processed @param[in] amp amplifier device data

saturationInterpolation(ccdExposure)¶

!Interpolate over saturated pixels, in place

@param[in,out] ccdExposure exposure to process

@warning: - Call saturationDetection first, so that saturated pixels have been identified in the “SAT” mask. - Call this after CCD assembly, since saturated regions may cross amplifier boundaries

setValidPolygonIntersect(ccdExposure, fpPolygon)¶

!Set the valid polygon as the intersection of fpPolygon and the ccd corners

@param[in,out] ccdExposure exposure to process @param[in] fpPolygon Polygon in focal plane coordinates

suspectDetection(exposure, amp)¶

!Detect suspect pixels and mask them using mask plane config.suspectMaskName, in place

Suspect pixels are pixels whose value is greater than amp.getSuspectLevel(). This is intended to indicate pixels that may be affected by unknown systematics; for example if non-linearity corrections above a certain level are unstable then that would be a useful value for suspectLevel. A value of nan indicates that no such level exists and no pixels are to be masked as suspicious.

@param[in,out] exposure exposure to process; only the amp DataSec is processed @param[in] amp amplifier device data

timer(name, logLevel=10000)¶

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 `lsst.log` level constant.

Navigation

CfhtIsrTask¶