ImageDifferenceConfig¶

class lsst.pipe.tasks.imageDifference.ImageDifferenceConfig(*args, **kw)¶

Bases: PipelineTaskConfig

Config for ImageDifferenceTask.

Attributes Summary

`applyApCorr`	Subtask to apply aperture corrections (`ConfigurableInstance`, default `<class 'lsst.meas.base.applyApCorr.ApplyApCorrConfig'>`)
`astrometer`	astrometry task; used to match sources to reference objects, but not to fit a WCS (`ConfigurableInstance`, default `<class 'lsst.meas.astrom.astrometry.AstrometryConfig'>`)
`coaddName`	coadd name: typically one of deep, goodSeeing, or dcr (`str`, default `'deep'`)
`connections`	Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.
`controlRandomSeed`	Random seed for shuffing the control sample (`int`, default `10`)
`controlStepSize`	What step size (every Nth one) to select a control sample from the kernelSources (`int`, default `5`)
`convolveTemplate`	Which image gets convolved (default = template) (`bool`, default `True`)
`decorrelate`	Decorrelate effects of A&L kernel convolution on image difference, only if doSubtract is True.
`detection`	Low-threshold detection for final measurement (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>`)
`diaSourceMatchRadius`	Match radius (in arcseconds) for DiaSource to Source association (`float`, default `0.5`)
`doAddCalexpBackground`	Add background to calexp before processing it.
`doAddMetrics`	Add columns to the source table to hold analysis metrics? (`bool`, default `False`)
`doApCorr`	Run subtask to apply aperture corrections (`bool`, default `True`)
`doApplyFinalizedPsf`	Whether to apply finalized psf models and aperture correction map.
`doDebugRegister`	Writing debugging data for doUseRegister (`bool`, default `False`)
`doDecorrelation`	Perform diffim decorrelation to undo pixel correlation due to A&L kernel convolution (AL only)? If True, also update the diffim PSF.
`doDetection`	Detect sources? (`bool`, default `True`)
`doDipoleFitting`	Measure dipoles using new algorithm? (`bool`, default `True`)
`doForcedMeasurement`	Force photometer diaSource locations on PVI? (`bool`, default `True`)
`doMatchSources`	Match diaSources with input calexp sources and ref catalog sources (`bool`, default `False`)
`doMeasurement`	Measure diaSources? (`bool`, default `True`)
`doMerge`	Merge positive and negative diaSources with grow radius set by growFootprint (`bool`, default `True`)
`doPreConvolve`	Not in use.
`doScaleDiffimVariance`	Scale variance of the diffim before PSF matching.
`doScaleTemplateVariance`	Scale variance of the template before PSF matching (`bool`, default `False`)
`doSelectDcrCatalog`	Select stars of extreme color as part of the control sample (AL only) (`bool`, default `False`)
`doSelectSources`	Select stars to use for kernel fitting (AL only) (`bool`, default `False`)
`doSelectVariableCatalog`	Select stars that are variable to be part of the control sample (AL only) (`bool`, default `False`)
`doSkySources`	Generate sky sources? (`bool`, default `False`)
`doSpatiallyVarying`	Perform A&L decorrelation on a grid across the image in order to allow for spatial variations.
`doSubtract`	Compute subtracted exposure? (`bool`, default `True`)
`doUseRegister`	Re-compute astrometry on the template.
`doWriteMatchedExp`	Write warped and PSF-matched template coadd exposure? (`bool`, default `False`)
`doWriteScoreExp`	Write AL likelihood or Zogy score exposure? (`bool`, default `False`)
`doWriteSources`	Write sources? (`bool`, default `True`)
`doWriteSubtractedExp`	Write difference exposure (AL and Zogy) ? (`bool`, default `True`)
`doWriteWarpedExp`	Write WCS, warped template coadd exposure? (`bool`, default `False`)
`forcedMeasurement`	Subtask to force photometer PVI at diaSource location.
`getTemplate`	Subtask to retrieve template exposure and sources (`ConfigurableInstance`, default `<class 'lsst.ip.diffim.getTemplate.GetCoaddAsTemplateConfig'>`)
`growFootprint`	Grow positive and negative footprints by this amount before merging (`int`, default `2`)
`history`
`kernelSourcesFromRef`	Select sources to measure kernel from reference catalog if True, template if false (`bool`, default `False`)
`measurement`	Enable updated dipole fitting method (`ConfigurableInstance`, default `<class 'lsst.ip.diffim.dipoleFitTask.DipoleFitTaskConfig'>`)
`refObjLoader`	reference object loader (`LoadReferenceObjectsConfig`, default `<class 'lsst.meas.algorithms.loadReferenceObjects.LoadReferenceObjectsConfig'>`)
`register`	Task to enable image-to-image image registration (warping) (`ConfigurableInstance`, default `<class 'lsst.pipe.tasks.registerImage.RegisterConfig'>`)
`requiredTemplateFraction`	Do not attempt to run task if template covers less than this fraction of pixels.Setting to 0 will always attempt image subtraction (`float`, default `0.1`)
`saveLogOutput`	Flag to enable/disable saving of log output for a task, enabled by default.
`saveMetadata`	Flag to enable/disable metadata saving for a task, enabled by default.
`scaleVariance`	Subtask to rescale the variance of the template to the statistically expected level (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.scaleVariance.ScaleVarianceConfig'>`)
`skySources`	Generate sky sources (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.skyObjects.SkyObjectsConfig'>`)
`sourceSelector`	Source selection algorithm (`ConfigurableInstance`, default `<class 'lsst.meas.algorithms.objectSizeStarSelector.ObjectSizeStarSelectorConfig'>`)
`subtract`	Subtraction Algorithm (`RegistryInstanceDict`, default `'al'`)
`templateSipOrder`	Sip Order for fitting the Template Wcs (default is too high, overfitting) (`int`, default `2`)
`useGaussianForPreConvolution`	Use a simple gaussian PSF model for pre-convolution (oherwise use exposure PSF)? (AL and if useScoreImageDetection=True only) (`bool`, default `False`)
`useScoreImageDetection`	Calculate the pre-convolved AL likelihood or the Zogy score image.

Methods Summary

`applyConfigOverrides`(instrument, ...)	Apply config overrides to this config instance.
`compare`(other[, shortcut, rtol, atol, output])	Compare this configuration to another `Config` for equality.
`formatHistory`(name, **kwargs)	Format a configuration field's history to a human-readable format.
`freeze`()	Make this config, and all subconfigs, read-only.
`items`()	Get configurations as `(field name, field value)` pairs.
`keys`()	Get field names.
`load`(filename[, root])	Modify this config in place by executing the Python code in a configuration file.
`loadFromStream`(stream[, root, filename])	Modify this Config in place by executing the Python code in the provided stream.
`loadFromString`(code[, root, filename])	Modify this Config in place by executing the Python code in the provided string.
`names`()	Get all the field names in the config, recursively.
`save`(filename[, root])	Save a Python script to the named file, which, when loaded, reproduces this config.
`saveToStream`(outfile[, root, skipImports])	Save a configuration file to a stream, which, when loaded, reproduces this config.
`saveToString`([skipImports])	Return the Python script form of this configuration as an executable string.
`setDefaults`()	Subclass hook for computing defaults.
`toDict`()	Make a dictionary of field names and their values.
`update`(**kw)	Update values of fields specified by the keyword arguments.
`validate`()	Validate the Config, raising an exception if invalid.
`values`()	Get field values.

Attributes Documentation

applyApCorr¶: Subtask to apply aperture corrections (ConfigurableInstance, default <class 'lsst.meas.base.applyApCorr.ApplyApCorrConfig'>)

astrometer¶: astrometry task; used to match sources to reference objects, but not to fit a WCS (ConfigurableInstance, default <class 'lsst.meas.astrom.astrometry.AstrometryConfig'>)

coaddName¶: coadd name: typically one of deep, goodSeeing, or dcr (str, default 'deep')

connections: pexConfig.ConfigField¶: Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.

controlRandomSeed¶: Random seed for shuffing the control sample (int, default 10)

controlStepSize¶: What step size (every Nth one) to select a control sample from the kernelSources (int, default 5)

convolveTemplate¶: Which image gets convolved (default = template) (bool, default True)

decorrelate¶: Decorrelate effects of A&L kernel convolution on image difference, only if doSubtract is True. If this option is enabled, then detection.thresholdValue should be set to 5.0 (rather than the default of 5.5). (ConfigurableInstance, default <class 'lsst.ip.diffim.imageDecorrelation.DecorrelateALKernelSpatialConfig'>)

detection¶: Low-threshold detection for final measurement (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

diaSourceMatchRadius¶: Match radius (in arcseconds) for DiaSource to Source association (float, default 0.5)

doAddCalexpBackground¶: Add background to calexp before processing it. Useful as ipDiffim does background matching. (bool, default False)

doAddMetrics¶: Add columns to the source table to hold analysis metrics? (bool, default False)

doApCorr¶: Run subtask to apply aperture corrections (bool, default True)

doApplyFinalizedPsf¶: Whether to apply finalized psf models and aperture correction map. (bool, default False)

doDebugRegister¶: Writing debugging data for doUseRegister (bool, default False)

doDecorrelation¶: Perform diffim decorrelation to undo pixel correlation due to A&L kernel convolution (AL only)? If True, also update the diffim PSF. (bool, default True)

doDetection¶: Detect sources? (bool, default True)

doDipoleFitting¶: Measure dipoles using new algorithm? (bool, default True)

doForcedMeasurement¶: Force photometer diaSource locations on PVI? (bool, default True)

doMatchSources¶: Match diaSources with input calexp sources and ref catalog sources (bool, default False)

doMeasurement¶: Measure diaSources? (bool, default True)

doMerge¶: Merge positive and negative diaSources with grow radius set by growFootprint (bool, default True)

doPreConvolve¶: Not in use. Superseded by useScoreImageDetection. Deprecated: This option superseded by useScoreImageDetection. Will be removed after v22. (bool, default False)

doScaleDiffimVariance¶: Scale variance of the diffim before PSF matching. You may do either this or template variance scaling, or neither. (Doing both is a waste of CPU.) (bool, default True)

doScaleTemplateVariance¶: Scale variance of the template before PSF matching (bool, default False)

doSelectDcrCatalog¶: Select stars of extreme color as part of the control sample (AL only) (bool, default False)

doSelectSources¶: Select stars to use for kernel fitting (AL only) (bool, default False)

doSelectVariableCatalog¶: Select stars that are variable to be part of the control sample (AL only) (bool, default False)

doSkySources¶: Generate sky sources? (bool, default False)

doSpatiallyVarying¶: Perform A&L decorrelation on a grid across the image in order to allow for spatial variations. Zogy does not use this option. (bool, default False)

doSubtract¶: Compute subtracted exposure? (bool, default True)

doUseRegister¶: Re-compute astrometry on the template. Use image-to-image registration to align template with science image (AL only). (bool, default False)

doWriteMatchedExp¶: Write warped and PSF-matched template coadd exposure? (bool, default False)

doWriteScoreExp¶: Write AL likelihood or Zogy score exposure? (bool, default False)

doWriteSources¶: Write sources? (bool, default True)

doWriteSubtractedExp¶: Write difference exposure (AL and Zogy) ? (bool, default True)

doWriteWarpedExp¶: Write WCS, warped template coadd exposure? (bool, default False)

forcedMeasurement¶: Subtask to force photometer PVI at diaSource location. (ConfigurableInstance, default <class 'lsst.meas.base.forcedMeasurement.ForcedMeasurementConfig'>)

getTemplate¶: Subtask to retrieve template exposure and sources (ConfigurableInstance, default <class 'lsst.ip.diffim.getTemplate.GetCoaddAsTemplateConfig'>)

growFootprint¶: Grow positive and negative footprints by this amount before merging (int, default 2)

history¶: Read-only history.

kernelSourcesFromRef¶: Select sources to measure kernel from reference catalog if True, template if false (bool, default False)

measurement¶: Enable updated dipole fitting method (ConfigurableInstance, default <class 'lsst.ip.diffim.dipoleFitTask.DipoleFitTaskConfig'>)

refObjLoader¶: reference object loader (LoadReferenceObjectsConfig, default <class 'lsst.meas.algorithms.loadReferenceObjects.LoadReferenceObjectsConfig'>)

register¶: Task to enable image-to-image image registration (warping) (ConfigurableInstance, default <class 'lsst.pipe.tasks.registerImage.RegisterConfig'>)

requiredTemplateFraction¶: Do not attempt to run task if template covers less than this fraction of pixels.Setting to 0 will always attempt image subtraction (float, default 0.1)

saveLogOutput¶: Flag to enable/disable saving of log output for a task, enabled by default. (bool, default True)

saveMetadata¶: Flag to enable/disable metadata saving for a task, enabled by default. (bool, default True)

scaleVariance¶: Subtask to rescale the variance of the template to the statistically expected level (ConfigurableInstance, default <class 'lsst.meas.algorithms.scaleVariance.ScaleVarianceConfig'>)

skySources¶: Generate sky sources (ConfigurableInstance, default <class 'lsst.meas.algorithms.skyObjects.SkyObjectsConfig'>)

sourceSelector¶: Source selection algorithm (ConfigurableInstance, default <class 'lsst.meas.algorithms.objectSizeStarSelector.ObjectSizeStarSelectorConfig'>)

subtract¶: Subtraction Algorithm (RegistryInstanceDict, default 'al')

templateSipOrder¶: Sip Order for fitting the Template Wcs (default is too high, overfitting) (int, default 2)

useGaussianForPreConvolution¶: Use a simple gaussian PSF model for pre-convolution (oherwise use exposure PSF)? (AL and if useScoreImageDetection=True only) (bool, default False)

useScoreImageDetection¶: Calculate the pre-convolved AL likelihood or the Zogy score image. Use it for source detection (if doDetection=True). (bool, default False)

Methods Documentation

applyConfigOverrides(instrument: Instrument | None, taskDefaultName: str, pipelineConfigs: Iterable[ConfigIR] | None, parameters: ParametersIR, label: str) → None¶

Apply config overrides to this config instance.

Parameters¶

instrumentInstrument or None: An instance of the Instrument specified in a pipeline. If None then the pipeline did not specify and instrument.
taskDefaultNamestr: The default name associated with the Task class. This may be used with instrumental overrides.
pipelineConfigsIterable of ConfigIR: An iterable of ConfigIR objects that contain overrides to apply to this config instance.
parametersParametersIR: Parameters defined in a Pipeline which are used in formatting of config values across multiple Tasks in a pipeline.
labelstr: The label associated with this class’s Task in a pipeline.

compare(other, shortcut=True, rtol=1e-08, atol=1e-08, output=None)¶

Compare this configuration to another Config for equality.

Parameters:

otherlsst.pex.config.Config: Other Config object to compare against this config.
shortcutbool, optional: If True, return as soon as an inequality is found. Default is True.
rtolfloat, optional: Relative tolerance for floating point comparisons.
atolfloat, optional: Absolute tolerance for floating point comparisons.
outputcallable, optional: A callable that takes a string, used (possibly repeatedly) to report inequalities.

Returns:

isEqualbool: True when the two lsst.pex.config.Config instances are equal. False if there is an inequality.

See also

lsst.pex.config.compareConfigs

Notes

Unselected targets of RegistryField fields and unselected choices of ConfigChoiceField fields are not considered by this method.

Floating point comparisons are performed by numpy.allclose.

formatHistory(name, **kwargs)¶

Format a configuration field’s history to a human-readable format.

Parameters:

namestr: Name of a Field in this config.
kwargs: Keyword arguments passed to lsst.pex.config.history.format.

Returns:

historystr: A string containing the formatted history.

See also

lsst.pex.config.history.format

freeze()¶: Make this config, and all subconfigs, read-only.

items()¶

Get configurations as (field name, field value) pairs.

Returns:

itemsdict_items

Iterator of tuples for each configuration. Tuple items are:

Field name.
Field value.

keys()¶

Get field names.

Returns:

namesdict_keys: List of lsst.pex.config.Field names.

See also

lsst.pex.config.Config.iterkeys

load(filename, root='config')¶

Modify this config in place by executing the Python code in a configuration file.

Parameters:

filenamestr

Name of the configuration file. A configuration file is Python module.

rootstr, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

See also

lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString
lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString

loadFromStream(stream, root='config', filename=None)¶

Modify this Config in place by executing the Python code in the provided stream.

Parameters:

streamfile-like object, str, bytes, or compiled string

Stream containing configuration override code. If this is a code object, it should be compiled with mode="exec".

rootstr, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

filenamestr, optional

Name of the configuration file, or None if unknown or contained in the stream. Used for error reporting.

See also

lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromString
lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString

Notes

For backwards compatibility reasons, this method accepts strings, bytes and code objects as well as file-like objects. New code should use loadFromString instead for most of these types.

loadFromString(code, root='config', filename=None)¶

Modify this Config in place by executing the Python code in the provided string.

Parameters:

codestr, bytes, or compiled string

Stream containing configuration override code.

rootstr, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

filenamestr, optional

Name of the configuration file, or None if unknown or contained in the stream. Used for error reporting.

See also

lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString

names()¶

Get all the field names in the config, recursively.

Returns:

nameslist of str: Field names.

save(filename, root='config')¶

Save a Python script to the named file, which, when loaded, reproduces this config.

Parameters:

filenamestr: Desination filename of this configuration.
rootstr, optional: Name to use for the root config variable. The same value must be used when loading (see lsst.pex.config.Config.load).

See also

lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.saveToString
lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString

saveToStream(outfile, root='config', skipImports=False)¶

Save a configuration file to a stream, which, when loaded, reproduces this config.

Parameters:

outfilefile-like object: Destination file object write the config into. Accepts strings not bytes.
root: Name to use for the root config variable. The same value must be used when loading (see lsst.pex.config.Config.load).
skipImportsbool, optional: If True then do not include import statements in output, this is to support human-oriented output from pipetask where additional clutter is not useful.

See also

lsst.pex.config.Config.save
lsst.pex.config.Config.saveToString
lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString

saveToString(skipImports=False)¶

Return the Python script form of this configuration as an executable string.

Parameters:

skipImportsbool, optional: If True then do not include import statements in output, this is to support human-oriented output from pipetask where additional clutter is not useful.

Returns:

codestr: A code string readable by loadFromString.

See also

lsst.pex.config.Config.save
lsst.pex.config.Config.saveToStream
lsst.pex.config.Config.load
lsst.pex.config.Config.loadFromStream
lsst.pex.config.Config.loadFromString

setDefaults()¶

Subclass hook for computing defaults.

Notes

Derived Config classes that must compute defaults rather than using the Field instances’s defaults should do so here. To correctly use inherited defaults, implementations of setDefaults must call their base class’s setDefaults.

toDict()¶

Make a dictionary of field names and their values.

Returns:

dict_dict: Dictionary with keys that are Field names. Values are Field values.

See also

lsst.pex.config.Field.toDict

Notes

This method uses the toDict method of individual fields. Subclasses of Field may need to implement a toDict method for this method to work.

update(**kw)¶

Update values of fields specified by the keyword arguments.

Parameters:

kw: Keywords are configuration field names. Values are configuration field values.

Notes

The __at and __label keyword arguments are special internal keywords. They are used to strip out any internal steps from the history tracebacks of the config. Do not modify these keywords to subvert a Config instance’s history.

Examples

This is a config with three fields:

>>> from lsst.pex.config import Config, Field
>>> class DemoConfig(Config):
...     fieldA = Field(doc='Field A', dtype=int, default=42)
...     fieldB = Field(doc='Field B', dtype=bool, default=True)
...     fieldC = Field(doc='Field C', dtype=str, default='Hello world')
...
>>> config = DemoConfig()

These are the default values of each field:

>>> for name, value in config.iteritems():
...     print(f"{name}: {value}")
...
fieldA: 42
fieldB: True
fieldC: 'Hello world'

Using this method to update fieldA and fieldC:

>>> config.update(fieldA=13, fieldC='Updated!')

Now the values of each field are:

>>> for name, value in config.iteritems():
...     print(f"{name}: {value}")
...
fieldA: 13
fieldB: True
fieldC: 'Updated!'

validate()¶

Validate the Config, raising an exception if invalid.

Raises:

lsst.pex.config.FieldValidationError: Raised if verification fails.

Notes

The base class implementation performs type checks on all fields by calling their validate methods.

Complex single-field validation can be defined by deriving new Field types. For convenience, some derived lsst.pex.config.Field-types (ConfigField and ConfigChoiceField) are defined in lsst.pex.config that handle recursing into subconfigs.

Inter-field relationships should only be checked in derived Config classes after calling this method, and base validation is complete.

values()¶

Get field values.

Returns:

valuesdict_values: Iterator of field values.

Navigation

ImageDifferenceConfig¶

Parameters¶