CfhtIsrTask¶
- class lsst.obs.cfht.cfhtIsrTask.CfhtIsrTask(**kwargs)¶
Bases:
IsrTask
Attributes Summary
Methods Summary
compareCameraKeywords
(exposureMetadata, ...)Compare header keywords to confirm camera states match.
convertIntToFloat
(exposure)Convert exposure image from uint16 to float.
darkCorrection
(exposure, darkExposure[, invert])Apply dark correction in place.
debugView
(exposure, stepname)Utility function to examine ISR exposure at different stages.
defineEffectivePtc
(ptcDataset, detector, ...)Define an effective Photon Transfer Curve dataset with nominal gains and noise.
doLinearize
(detector)Check if linearization is needed for the detector cameraGeom.
Empty (clear) the metadata for this Task and all sub-Tasks.
ensureExposure
(inputExp[, camera, detectorNum])Ensure that the data returned by Butler is a fully constructed exp.
extractCalibDate
(calib)Extract common calibration metadata values that will be written to output header.
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.
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.
makeBinnedImages
(exposure)Make visualizeVisit style binned exposures.
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.maskAmplifier
(ccdExposure, amp, defects)Identify bad amplifiers, saturated and suspect pixels.
maskAndInterpolateDefects
(exposure, ...)Mask and interpolate defects using mask plane "BAD", in place.
maskAndInterpolateNan
(exposure)"Mask and interpolate NaN/infs using mask plane "UNMASKEDNAN", in place.
maskDefect
(exposure, defectBaseList)Mask defects using mask plane "BAD", in place.
maskEdges
(exposure[, numEdgePixels, ...])Mask edge pixels with applicable mask plane.
maskNan
(exposure)Mask NaNs using mask plane "UNMASKEDNAN", in place.
maskNegativeVariance
(exposure)Identify and mask pixels with negative variance values.
measureBackground
(exposure[, IsrQaConfig])Measure the image background in subgrids, for quality control.
overscanCorrection
(ccdExposure, amp)Apply overscan correction in place.
roughZeroPoint
(exposure)Set an approximate magnitude zero point for the exposure.
run
(ccdExposure[, bias, linearizer, dark, ...])Perform instrument signature removal on an exposure
runQuantum
(butlerQC, inputRefs, outputRefs)Do butler IO and transform to provide in memory objects for tasks
run
method.saturationDetection
(exposure, amp)Detect and mask saturated pixels in config.saturatedMaskName.
saturationInterpolation
(exposure)Interpolate over saturated pixels, in place.
suspectDetection
(exposure, amp)Detect and mask suspect pixels in config.suspectMaskName.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
updateVariance
(ampExposure, amp, ptcDataset)Set the variance plane using the gain and read noise
Attributes Documentation
Methods Documentation
- compareCameraKeywords(exposureMetadata, calib, calibName)¶
Compare header keywords to confirm camera states match.
- Parameters:
- exposureMetadata
lsst.daf.base.PropertySet
Header for the exposure being processed.
- calib
lsst.afw.image.Exposure
orlsst.ip.isr.IsrCalib
Calibration to be applied.
- calibName
str
Calib type for log message.
- exposureMetadata
- convertIntToFloat(exposure)¶
Convert exposure image from uint16 to float.
If the exposure does not need to be converted, the input is immediately returned. For exposures that are converted to use floating point pixels, the variance is set to unity and the mask to zero.
- Parameters:
- exposure
lsst.afw.image.Exposure
The raw exposure to be converted.
- exposure
- Returns:
- newexposure
lsst.afw.image.Exposure
The input
exposure
, converted to floating point pixels.
- newexposure
- Raises:
- RuntimeError
Raised if the exposure type cannot be converted to float.
- darkCorrection(exposure, darkExposure, invert=False)¶
Apply dark correction in place.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- darkExposure
lsst.afw.image.Exposure
Dark exposure of the same size as
exposure
.- invert
Bool
, optional If True, re-add the dark to an already corrected image.
- exposure
- Raises:
- RuntimeError
Raised if either
exposure
ordarkExposure
do not have their dark time defined.
See also
lsst.ip.isr.isrFunctions.darkCorrection
- debugView(exposure, stepname)¶
Utility function to examine ISR exposure at different stages.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to view.
- stepname
str
State of processing to view.
- exposure
- defineEffectivePtc(ptcDataset, detector, bfGains, overScans, metadata)¶
Define an effective Photon Transfer Curve dataset with nominal gains and noise.
- Parameters:
- ptcDataset
lsst.ip.isr.PhotonTransferCurveDataset
Input Photon Transfer Curve dataset.
- detector
lsst.afw.cameraGeom.Detector
Detector object.
- bfGains
dict
Gains from running the brighter-fatter code. A dict keyed by amplifier name for the detector in question.
- ovserScans
list
[lsst.pipe.base.Struct
] List of overscanResults structures
- metadata
lsst.daf.base.PropertyList
Exposure metadata to update gain and noise provenance.
- ptcDataset
- Returns:
- effectivePtc
lsst.ip.isr.PhotonTransferCurveDataset
PTC dataset containing gains and readout noise values to be used throughout Instrument Signature Removal.
- effectivePtc
- doLinearize(detector)¶
Check if linearization is needed for the detector cameraGeom.
Checks config.doLinearize and the linearity type of the first amplifier.
- Parameters:
- detector
lsst.afw.cameraGeom.Detector
Detector to get linearity type from.
- detector
- Returns:
- doLinearize
Bool
If True, linearization should be performed.
- doLinearize
- ensureExposure(inputExp, camera=None, detectorNum=None)¶
Ensure that the data returned by Butler is a fully constructed exp.
ISR requires exposure-level image data for historical reasons, so if we did not recieve that from Butler, construct it from what we have, modifying the input in place.
- Parameters:
- inputExp
lsst.afw.image
image-type. The input data structure obtained from Butler. Can be
lsst.afw.image.Exposure
,lsst.afw.image.DecoratedImageU
, orlsst.afw.image.ImageF
- camera
lsst.afw.cameraGeom.camera
, optional The camera associated with the image. Used to find the appropriate detector if detector is not already set.
- detectorNum
int
, optional The detector in the camera to attach, if the detector is not already set.
- inputExp
- Returns:
- inputExp
lsst.afw.image.Exposure
The re-constructed exposure, with appropriate detector parameters.
- inputExp
- Raises:
- TypeError
Raised if the input data cannot be used to construct an exposure.
- static extractCalibDate(calib)¶
Extract common calibration metadata values that will be written to output header.
- Parameters:
- calib
lsst.afw.image.Exposure
orlsst.ip.isr.IsrCalib
Calibration to pull date information from.
- calib
- Returns:
- dateString
str
Calibration creation date string to add to header.
- dateString
- flatContext(exp, flat, dark=None)¶
Context manager that applies and removes flats and darks, if the task is configured to apply them.
- Parameters:
- exp
lsst.afw.image.Exposure
Exposure to process.
- flat
lsst.afw.image.Exposure
Flat exposure the same size as
exp
.- dark
lsst.afw.image.Exposure
, optional Dark exposure the same size as
exp
.
- exp
- Yields:
- exp
lsst.afw.image.Exposure
The flat and dark corrected exposure.
- exp
- flatCorrection(exposure, flatExposure, invert=False)¶
Apply flat correction in place.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- flatExposure
lsst.afw.image.Exposure
Flat exposure of the same size as
exposure
.- invert
Bool
, optional If True, unflatten an already flattened image.
- exposure
See also
lsst.ip.isr.isrFunctions.flatCorrection
- 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
- makeBinnedImages(exposure)¶
Make visualizeVisit style binned exposures.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to bin.
- exposure
- Returns:
- bin1
lsst.afw.image.Exposure
Binned exposure using binFactor1.
- bin2
lsst.afw.image.Exposure
Binned exposure using binFactor2.
- bin1
- 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
.
- maskAmplifier(ccdExposure, amp, defects)¶
Identify bad amplifiers, saturated and suspect pixels.
- Parameters:
- ccdExposure
lsst.afw.image.Exposure
Input exposure to be masked.
- amp
lsst.afw.cameraGeom.Amplifier
Catalog of parameters defining the amplifier on this exposure to mask.
- defects
lsst.ip.isr.Defects
List of defects. Used to determine if the entire amplifier is bad.
- ccdExposure
- Returns:
- badAmp
Bool
If this is true, the entire amplifier area is covered by defects and unusable.
- badAmp
- maskAndInterpolateDefects(exposure, defectBaseList)¶
Mask and interpolate defects using mask plane “BAD”, in place.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- defectBaseListdefects-like
List of defects to mask and interpolate. Can be
lsst.ip.isr.Defects
orlist
oflsst.afw.image.DefectBase
.
- exposure
See also
lsst.ip.isr.isrTask.maskDefect
- maskAndInterpolateNan(exposure)¶
“Mask and interpolate NaN/infs using mask plane “UNMASKEDNAN”, in place.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- exposure
See also
lsst.ip.isr.isrTask.maskNan
- maskDefect(exposure, defectBaseList)¶
Mask defects using mask plane “BAD”, in place.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- defectBaseListdefect-type
List of defects to mask. Can be of type
lsst.ip.isr.Defects
orlist
oflsst.afw.image.DefectBase
.
- exposure
Notes
Call this after CCD assembly, since defects may cross amplifier boundaries.
- maskEdges(exposure, numEdgePixels=0, maskPlane='SUSPECT', level='DETECTOR')¶
Mask edge pixels with applicable mask plane.
- maskNan(exposure)¶
Mask NaNs using mask plane “UNMASKEDNAN”, in place.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- exposure
Notes
We mask over all non-finite values (NaN, inf), including those that are masked with other bits (because those may or may not be interpolated over later, and we want to remove all NaN/infs). Despite this behaviour, the “UNMASKEDNAN” mask plane is used to preserve the historical name.
- maskNegativeVariance(exposure)¶
Identify and mask pixels with negative variance values.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- exposure
See also
lsst.ip.isr.isrFunctions.updateVariance
- measureBackground(exposure, IsrQaConfig=None)¶
Measure the image background in subgrids, for quality control.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- IsrQaConfig
lsst.ip.isr.isrQa.IsrQaConfig
Configuration object containing parameters on which background statistics and subgrids to use.
- exposure
- overscanCorrection(ccdExposure, amp)¶
Apply overscan correction in place.
This method does initial pixel rejection of the overscan region. The overscan can also be optionally segmented to allow for discontinuous overscan responses to be fit separately. The actual overscan subtraction is performed by the
lsst.ip.isr.overscan.OverscanTask
, which is called here after the amplifier is preprocessed.- Parameters:
- ccdExposure
lsst.afw.image.Exposure
Exposure to have overscan correction performed.
- amp
lsst.afw.cameraGeom.Amplifer
The amplifier to consider while correcting the overscan.
- ccdExposure
- Returns:
- overscanResults
lsst.pipe.base.Struct
Result struct with components:
imageFit
Value or fit subtracted from the amplifier image data. (scalar or
lsst.afw.image.Image
)overscanFit
Value or fit subtracted from the overscan image data. (scalar or
lsst.afw.image.Image
)overscanImage
Image of the overscan region with the overscan correction applied. This quantity is used to estimate the amplifier read noise empirically. (
lsst.afw.image.Image
)edgeMask
Mask of the suspect pixels. (
lsst.afw.image.Mask
)overscanMean
Median overscan fit value. (
float
)overscanSigma
Clipped standard deviation of the overscan after correction. (
float
)
- overscanResults
- Raises:
- RuntimeError
Raised if the
amp
does not contain raw pixel information.
See also
lsst.ip.isr.overscan.OverscanTask
- roughZeroPoint(exposure)¶
Set an approximate magnitude zero point for the exposure.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- exposure
- run(ccdExposure, bias=None, linearizer=None, dark=None, flat=None, defects=None, fringes=None, bfKernel=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 listlsst.afw.image.Exposure
exposure of fringe frame or list of fringe exposure
- bfKernelNone
kernel used for brighter-fatter correction; currently unsupported
- **kwds
dict
additional kwargs forwarded to IsrTask.run.
- ccdExposure
- Returns:
- struct
lsst.pipe.base.Struct
with fields: exposure: the exposure after application of ISR
- struct
- runQuantum(butlerQC, inputRefs, outputRefs)¶
Do butler IO and transform to provide in memory objects for tasks
run
method.- Parameters:
- butlerQC
QuantumContext
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 thelsst.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 thelsst.daf.butler.DatasetRef
objects associated with the defined output connections.
- butlerQC
- saturationDetection(exposure, amp)¶
Detect and mask saturated pixels in config.saturatedMaskName.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process. Only the amplifier DataSec is processed.
- amp
lsst.afw.cameraGeom.Amplifier
Amplifier detector data.
- exposure
See also
lsst.ip.isr.isrFunctions.makeThresholdMask
- saturationInterpolation(exposure)¶
Interpolate over saturated pixels, in place.
This method should be called after
saturationDetection
, to ensure that the saturated pixels have been identified in the SAT mask. It should also be called afterassembleCcd
, since saturated regions may cross amplifier boundaries.- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process.
- exposure
See also
lsst.ip.isr.isrTask.saturationDetection
lsst.ip.isr.isrFunctions.interpolateFromMask
- suspectDetection(exposure, amp)¶
Detect and mask suspect pixels in config.suspectMaskName.
- Parameters:
- exposure
lsst.afw.image.Exposure
Exposure to process. Only the amplifier DataSec is processed.
- amp
lsst.afw.cameraGeom.Amplifier
Amplifier detector data.
- exposure
See also
lsst.ip.isr.isrFunctions.makeThresholdMask
Notes
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.
- timer(name: str, logLevel: int = 10) Iterator[None] ¶
Context manager to log performance data for an arbitrary block of code.
- Parameters:
See also
lsst.utils.timer.logInfo
Implementation function.
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time
- updateVariance(ampExposure, amp, ptcDataset)¶
Set the variance plane using the gain and read noise
The read noise is calculated from the
overscanImage
if thedoEmpiricalReadNoise
option is set in the configuration; otherwise the value from the amplifier data is used.- Parameters:
- ampExposure
lsst.afw.image.Exposure
Exposure to process.
- amp
lsst.afw.cameraGeom.Amplifier
orFakeAmp
Amplifier detector data.
- ptcDataset
lsst.ip.isr.PhotonTransferCurveDataset
Effective PTC dataset containing the gains and read noise.
- ampExposure
See also
lsst.ip.isr.isrFunctions.updateVariance