DcrAssembleCoaddConfig

class lsst.pipe.tasks.dcrAssembleCoadd.DcrAssembleCoaddConfig

Bases: lsst.pipe.tasks.assembleCoadd.CompareWarpAssembleCoaddConfig

Attributes Summary

accelerateModel Factor to amplify the differences between model planes by to speed convergence.
assembleStaticSkyModel Task to assemble an artifact-free, PSF-matched Coadd to serve as a naive/first-iteration model of the static sky.
badMaskPlanes Mask planes that, if set, the associated pixel should not be included in the coaddTempExp.
baseGain Relative weight to give the new solution vs.
brightObjectMaskName Name of mask bit used for bright objects (str, default 'BRIGHT_OBJECT')
calcErrorFromInputVariance Calculate coadd variance from input variance by stacking statistic.Passed to StatisticsControl.setCalcErrorFromInputVariance() (bool, default True)
clipIter Number of iterations of outlier rejection; ignored if non-clipping statistic selected.
coaddName Coadd name: typically one of deep or goodSeeing.
coaddPsf Configuration for CoaddPsf (CoaddPsfConfig, default <class 'lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsfConfig'>)
connections Configurations describing the connections of the PipelineTask to datatypes (Connections, default <class 'lsst.pipe.base.config.Connections'>)
convergenceMaskPlanes Mask planes to use to calculate convergence.
convergenceThreshold Target relative change in convergence between iterations of forward modeling.
dcrNumSubfilters Number of sub-filters to forward model chromatic effects to fit the supplied exposures.
detect Detect outlier sources on difference between each psfMatched warp and static sky model (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)
detectPsfSources Task to detect sources for PSF measurement, if doCalculatePsf is set.
detectTemplate Detect sources on static sky model.
doAirmassWeight Weight exposures by airmass? Useful if there are relatively few high-airmass observations.
doApplyUberCal Apply jointcal WCS and PhotoCalib results to input calexps? (bool, default False)
doAttachTransmissionCurve Attach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves).
doCalculatePsf Set to detect stars and recalculate the PSF from the final coadd.Otherwise the PSF is estimated from a selection of the best input exposures (bool, default False)
doInterp Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly.
doMaskBrightObjects Set mask and flag bits for bright objects? (bool, default False)
doNImage Create image of number of contributing exposures for each pixel (bool, default False)
doPrefilterArtifacts Ignore artifact candidates that are mostly covered by the bad pixel mask, because they will be excluded anyway.
doPreserveContainedBySource Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd.
doPsfMatch Match to modelPsf? Deprecated.
doScaleWarpVariance Rescale Warp variance plane using empirical noise? (bool, default True)
doSigmaClip Perform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED) (bool, default False)
doUsePsfMatchedPolygons Use ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only.
doWrite Persist coadd? (bool, default True)
hasFakes Should be set to True if fake sources have been inserted into the input data.
history
imageInterpOrder The order of the spline interpolation used to shift the image plane.
includeCalibVar Add photometric calibration variance to warp variance plane.
inputRecorder Subtask that helps fill CoaddInputs catalogs added to the final Exposure (ConfigurableInstance, default <class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)
interpImage Task to interpolate (and extrapolate) over NaN pixels (ConfigurableInstance, default <class 'lsst.pipe.tasks.interpImage.InterpImageConfig'>)
maskPropagationThresholds Threshold (in fractional weight) of rejection at which we propagate a mask plane to the coadd; that is, we set the mask bit on the coadd if the fraction the rejected frames would have contributed exceeds this value.
matchingKernelSize Size in pixels of matching kernel.
maxFractionEpochsHigh Fraction of local number of epochs (N) to use as effective maxNumEpochs for high N.
maxFractionEpochsLow Fraction of local number of epochs (N) to use as effective maxNumEpochs for low N.
maxNumEpochs Charactistic maximum local number of epochs/visits in which an artifact candidate can appear and still be masked.
maxNumIter Maximum number of iterations of forward modeling.
measurePsf Task to measure the PSF of the coadd, if doCalculatePsf is set.
measurePsfSources Task to measure sources for PSF measurement, if doCalculatePsf is set.
minNumIter Minimum number of iterations of forward modeling.
modelPsf Model Psf factory (ConfigurableInstance, default <class 'lsst.meas.algorithms.gaussianPsfFactory.GaussianPsfFactory'>)
modelWeightsWidth Width of the region around detected sources to include in the DcrModel.
prefilterArtifactsMaskPlanes Prefilter artifact candidates that are mostly covered by these bad mask planes.
prefilterArtifactsRatio Prefilter artifact candidates with less than this fraction overlapping good pixels (float, default 0.05)
regularizationWidth Minimum radius of a region to include in regularization, in pixels.
regularizeModelFrequency Maximum relative change of the model allowed between subfilters.Set to zero to disable.
regularizeModelIterations Maximum relative change of the model allowed between iterations.Set to zero to disable.
removeMaskPlanes Mask planes to remove before coadding (List, default ['NOT_DEBLENDED'])
scaleWarpVariance Rescale variance on warps (ConfigurableInstance, default <class 'lsst.pipe.tasks.scaleVariance.ScaleVarianceConfig'>)
scaleZeroPoint Task to adjust the photometric zero point of the coadd temp exposures (ConfigurableInstance, default <class 'lsst.pipe.tasks.scaleZeroPoint.ScaleZeroPointConfig'>)
select Image selection subtask.
sigmaClip Sigma for outlier rejection; ignored if non-clipping statistic selected.
spatialThreshold Unitless fraction of pixels defining how much of the outlier region has to meet the temporal criteria.
splitSubfilters Calculate DCR for two evenly-spaced wavelengths in each subfilter.Instead of at the midpoint (bool, default True)
splitThreshold Minimum DCR difference within a subfilter to use splitSubfilters, in pixels.Set to 0 to always split the subfilters.
statistic Main stacking statistic for aggregating over the epochs.
subregionSize Width, height of stack subregion size; make small enough that a full stack of images will fit into memory at once.
useConvergence Use convergence test as a forward modeling end condition?If not set, skips calculating convergence and runs for maxNumIter iterations (bool, default True)
useMeasMosaic Use meas_mosaic’s applyMosaicResultsExposure() to do the photometric calibration/wcs update (deprecated).
useModelWeights Width of the region around detected sources to include in the DcrModel.
useProgressiveGain Use a gain that slowly increases above baseGain to accelerate convergence? When calculating the next gain, we use up to 5 previous gains and convergence values.Can be set to False to force the model to change at the rate of baseGain.
warpType Warp name: one of ‘direct’ or ‘psfMatched’ (str, default 'direct')

Methods Summary

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.
iteritems() Iterate over (field name, field value) pairs.
iterkeys() Iterate over field names
itervalues() Iterate over field values.
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.
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]) Save a configuration file to a stream, which, when loaded, reproduces this config.
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

accelerateModel

Factor to amplify the differences between model planes by to speed convergence. (float, default 3)

assembleStaticSkyModel

Task to assemble an artifact-free, PSF-matched Coadd to serve as a naive/first-iteration model of the static sky. (ConfigurableInstance, default <class 'lsst.pipe.tasks.assembleCoadd.AssembleCoaddConfig'>)

badMaskPlanes

Mask planes that, if set, the associated pixel should not be included in the coaddTempExp. (List, default ('NO_DATA',))

baseGain

Relative weight to give the new solution vs. the last solution when updating the model.A value of 1.0 gives equal weight to both solutions.Small values imply slower convergence of the solution, but can help prevent overshooting and failures in the fit.If baseGain is None, a conservative gain will be calculated from the number of subfilters. (float, default None)

brightObjectMaskName

Name of mask bit used for bright objects (str, default 'BRIGHT_OBJECT')

calcErrorFromInputVariance

Calculate coadd variance from input variance by stacking statistic.Passed to StatisticsControl.setCalcErrorFromInputVariance() (bool, default True)

clipIter

Number of iterations of outlier rejection; ignored if non-clipping statistic selected. (int, default 2)

coaddName

Coadd name: typically one of deep or goodSeeing. (str, default 'deep')

coaddPsf

Configuration for CoaddPsf (CoaddPsfConfig, default <class 'lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsfConfig'>)

connections

Configurations describing the connections of the PipelineTask to datatypes (Connections, default <class 'lsst.pipe.base.config.Connections'>)

convergenceMaskPlanes

Mask planes to use to calculate convergence. (List, default ['DETECTED'])

convergenceThreshold

Target relative change in convergence between iterations of forward modeling. (float, default 0.001)

dcrNumSubfilters

Number of sub-filters to forward model chromatic effects to fit the supplied exposures. (int, default 3)

detect

Detect outlier sources on difference between each psfMatched warp and static sky model (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

detectPsfSources

Task to detect sources for PSF measurement, if doCalculatePsf is set. (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

detectTemplate

Detect sources on static sky model. Only used if doPreserveContainedBySource is True (ConfigurableInstance, default <class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)

doAirmassWeight

Weight exposures by airmass? Useful if there are relatively few high-airmass observations. (bool, default False)

doApplyUberCal

Apply jointcal WCS and PhotoCalib results to input calexps? (bool, default False)

doAttachTransmissionCurve

Attach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves). (bool, default False)

doCalculatePsf

Set to detect stars and recalculate the PSF from the final coadd.Otherwise the PSF is estimated from a selection of the best input exposures (bool, default False)

doInterp

Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly. (bool, default True)

doMaskBrightObjects

Set mask and flag bits for bright objects? (bool, default False)

doNImage

Create image of number of contributing exposures for each pixel (bool, default False)

doPrefilterArtifacts

Ignore artifact candidates that are mostly covered by the bad pixel mask, because they will be excluded anyway. This prevents them from contributing to the outlier epoch count image and potentially being labeled as persistant.’Mostly’ is defined by the config ‘prefilterArtifactsRatio’. (bool, default True)

doPreserveContainedBySource

Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd. Replicates a behavior of SafeClip. (bool, default True)

doPsfMatch

Match to modelPsf? Deprecated. Sets makePsfMatched=True, makeDirect=False (bool, default False)

doScaleWarpVariance

Rescale Warp variance plane using empirical noise? (bool, default True)

doSigmaClip

Perform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED) (bool, default False)

doUsePsfMatchedPolygons

Use ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only. (bool, default False)

doWrite

Persist coadd? (bool, default True)

hasFakes

Should be set to True if fake sources have been inserted into the input data. (bool, default False)

history
imageInterpOrder

The order of the spline interpolation used to shift the image plane. (int, default 3)

includeCalibVar

Add photometric calibration variance to warp variance plane. (bool, default False)

inputRecorder

Subtask that helps fill CoaddInputs catalogs added to the final Exposure (ConfigurableInstance, default <class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)

interpImage

Task to interpolate (and extrapolate) over NaN pixels (ConfigurableInstance, default <class 'lsst.pipe.tasks.interpImage.InterpImageConfig'>)

maskPropagationThresholds

Threshold (in fractional weight) of rejection at which we propagate a mask plane to the coadd; that is, we set the mask bit on the coadd if the fraction the rejected frames would have contributed exceeds this value. (Dict, default {'SAT': 0.1})

matchingKernelSize

Size in pixels of matching kernel. Must be odd. (int, default 21)

maxFractionEpochsHigh

Fraction of local number of epochs (N) to use as effective maxNumEpochs for high N. Effective maxNumEpochs = min(maxFractionEpochsLow * N, maxNumEpochs + maxFractionEpochsHigh * N) (float, default 0.03)

Valid Range = [0.0,1.0)

maxFractionEpochsLow

Fraction of local number of epochs (N) to use as effective maxNumEpochs for low N. Effective maxNumEpochs = min(maxFractionEpochsLow * N, maxNumEpochs + maxFractionEpochsHigh * N) (float, default 0.4)

Valid Range = [0.0,1.0)

maxNumEpochs

Charactistic maximum local number of epochs/visits in which an artifact candidate can appear and still be masked. The effective maxNumEpochs is a broken linear function of local number of epochs (N): min(maxFractionEpochsLow*N, maxNumEpochs + maxFractionEpochsHigh*N). For each footprint detected on the image difference between the psfMatched warp and static sky model, if a significant fraction of pixels (defined by spatialThreshold) are residuals in more than the computed effective maxNumEpochs, the artifact candidate is deemed persistant rather than transient and not masked. (int, default 2)

maxNumIter

Maximum number of iterations of forward modeling. (int, default None)

measurePsf

Task to measure the PSF of the coadd, if doCalculatePsf is set. (ConfigurableInstance, default <class 'lsst.pipe.tasks.measurePsf.MeasurePsfConfig'>)

measurePsfSources

Task to measure sources for PSF measurement, if doCalculatePsf is set. (ConfigurableInstance, default <class 'lsst.meas.base.sfm.SingleFrameMeasurementConfig'>)

minNumIter

Minimum number of iterations of forward modeling. (int, default None)

modelPsf

Model Psf factory (ConfigurableInstance, default <class 'lsst.meas.algorithms.gaussianPsfFactory.GaussianPsfFactory'>)

modelWeightsWidth

Width of the region around detected sources to include in the DcrModel. (float, default 3)

prefilterArtifactsMaskPlanes

Prefilter artifact candidates that are mostly covered by these bad mask planes. (List, default ('NO_DATA', 'BAD', 'SAT', 'SUSPECT'))

prefilterArtifactsRatio

Prefilter artifact candidates with less than this fraction overlapping good pixels (float, default 0.05)

regularizationWidth

Minimum radius of a region to include in regularization, in pixels. (int, default 2)

regularizeModelFrequency

Maximum relative change of the model allowed between subfilters.Set to zero to disable. (float, default 4.0)

regularizeModelIterations

Maximum relative change of the model allowed between iterations.Set to zero to disable. (float, default 2.0)

removeMaskPlanes

Mask planes to remove before coadding (List, default ['NOT_DEBLENDED'])

scaleWarpVariance

Rescale variance on warps (ConfigurableInstance, default <class 'lsst.pipe.tasks.scaleVariance.ScaleVarianceConfig'>)

scaleZeroPoint

Task to adjust the photometric zero point of the coadd temp exposures (ConfigurableInstance, default <class 'lsst.pipe.tasks.scaleZeroPoint.ScaleZeroPointConfig'>)

select

Image selection subtask. (ConfigurableInstance, default <class 'lsst.pex.config.config.Config'>)

sigmaClip

Sigma for outlier rejection; ignored if non-clipping statistic selected. (float, default 3.0)

spatialThreshold

Unitless fraction of pixels defining how much of the outlier region has to meet the temporal criteria. If 0, clip all. If 1, clip none. (float, default 0.5)

Valid Range = [0.0,1.0]

splitSubfilters

Calculate DCR for two evenly-spaced wavelengths in each subfilter.Instead of at the midpoint (bool, default True)

splitThreshold

Minimum DCR difference within a subfilter to use splitSubfilters, in pixels.Set to 0 to always split the subfilters. (float, default 0.1)

statistic

Main stacking statistic for aggregating over the epochs. (str, default 'MEANCLIP')

subregionSize

Width, height of stack subregion size; make small enough that a full stack of images will fit into memory at once. (List, default (2000, 2000))

useConvergence

Use convergence test as a forward modeling end condition?If not set, skips calculating convergence and runs for maxNumIter iterations (bool, default True)

useMeasMosaic

Use meas_mosaic’s applyMosaicResultsExposure() to do the photometric calibration/wcs update (deprecated). (bool, default False)

useModelWeights

Width of the region around detected sources to include in the DcrModel. (bool, default True)

useProgressiveGain

Use a gain that slowly increases above baseGain to accelerate convergence? When calculating the next gain, we use up to 5 previous gains and convergence values.Can be set to False to force the model to change at the rate of baseGain. (bool, default True)

warpType

Warp name: one of ‘direct’ or ‘psfMatched’ (str, default 'direct')

Methods Documentation

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

Compare this configuration to another Config for equality.

Parameters:
other : lsst.pex.config.Config

Other Config object to compare against this config.

shortcut : bool, optional

If True, return as soon as an inequality is found. Default is True.

rtol : float, optional

Relative tolerance for floating point comparisons.

atol : float, optional

Absolute tolerance for floating point comparisons.

output : callable, optional

A callable that takes a string, used (possibly repeatedly) to report inequalities.

Returns:
isEqual : bool

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

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:
name : str

Name of a Field in this config.

kwargs

Keyword arguments passed to lsst.pex.config.history.format.

Returns:
history : str

A string containing the formatted history.

freeze()

Make this config, and all subconfigs, read-only.

items()

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

Returns:
items : list

List of tuples for each configuration. Tuple items are:

  1. Field name.
  2. Field value.
iteritems()

Iterate over (field name, field value) pairs.

Yields:
item : tuple

Tuple items are:

  1. Field name.
  2. Field value.
iterkeys()

Iterate over field names

Yields:
key : str

A field’s key (attribute name).

itervalues()

Iterate over field values.

Yields:
value : obj

A field value.

keys()

Get field names.

Returns:
names : list

List of lsst.pex.config.Field names.

load(filename, root='config')

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

Parameters:
filename : str

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

root : str, 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.

Deprecated: For backwards compatibility, older config files that use root="root" instead of root="config" will be loaded with a warning printed to sys.stderr. This feature will be removed at some point.

See also

lsst.pex.config.Config.loadFromStream, lsst.pex.config.Config.save, lsst.pex.config.Config.saveFromStream

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

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

Parameters:
stream : file-like object, str, or compiled string

Stream containing configuration override code.

root : str, 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.

Deprecated: For backwards compatibility, older config files that use root="root" instead of root="config" will be loaded with a warning printed to sys.stderr. This feature will be removed at some point.

filename : str, 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.save, lsst.pex.config.Config.saveFromStream

names()

Get all the field names in the config, recursively.

Returns:
names : list of str

Field names.

save(filename, root='config')

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

Parameters:
filename : str

Desination filename of this configuration.

root : str, optional

Name to use for the root config variable. The same value must be used when loading (see lsst.pex.config.Config.load).

saveToStream(outfile, root='config')

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

Parameters:
outfile : file-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).

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.

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:
values : list

List of field values.