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.
`brightObjectMask`	Input Bright Object Mask mask produced with external catalogs to be applied to the mask plane BRIGHT_OBJECT.
`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.
`coaddExposure`	Output coadded exposure, produced by stacking input warps (`OutputDatasetConfig`, default `lsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{outputCoaddName}Coadd', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False)`)
`coaddName`	Coadd name: typically one of deep or goodSeeing.
`coaddPsf`	Configuration for CoaddPsf (`CoaddPsfConfig`, default `<class 'lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsfConfig'>`)
`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 `True`)
`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'>`)
`inputWarps`	Input list of warps to be assemebled i.e.
`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.
`nImage`	Output image of number of input images per pixel (`OutputDatasetConfig`, default `lsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ImageU', nameTemplate='{outputCoaddName}Coadd_nImage', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False)`)
`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`)
`psfMatchedWarps`	PSF-Matched Warps are required by CompareWarp regardless of the coadd type requested.
`quantum`	configuration for PipelineTask quantum (`QuantumConfig`, default `<class 'lsst.pipe.base.config.QuantumConfig'>`)
`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.
`skyMap`	Input definition of geometry/bbox and projection/wcs for coadded exposures (`InputDatasetConfig`, default `lsst.pipe.base.config.InputDatasetConfig(name='', storageClass='SkyMap', nameTemplate='{inputCoaddName}Coadd_skyMap', dimensions=['skymap'], scalar=True, manualLoad=False)`)
`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.
`formatTemplateNames`(templateParamsDict)
`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)

brightObjectMask¶: Input Bright Object Mask mask produced with external catalogs to be applied to the mask plane BRIGHT_OBJECT. (InputDatasetConfig, default lsst.pipe.base.config.InputDatasetConfig(name='brightObjectMask', storageClass='ObjectMaskCatalog', nameTemplate='', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))

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)

coaddExposure¶: Output coadded exposure, produced by stacking input warps (OutputDatasetConfig, default lsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{outputCoaddName}Coadd', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))

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'>)

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 True)

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'>)

inputWarps¶: Input list of warps to be assemebled i.e. stacked.WarpType (e.g. direct, psfMatched) is controlled by we warpType config parameter (InputDatasetConfig, default lsst.pipe.base.config.InputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{inputCoaddName}Coadd_{warpType}Warp', dimensions=['tract', 'patch', 'skymap', 'visit', 'instrument'], scalar=False, manualLoad=True))

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)

nImage¶: Output image of number of input images per pixel (OutputDatasetConfig, default lsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ImageU', nameTemplate='{outputCoaddName}Coadd_nImage', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))

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)

psfMatchedWarps¶: PSF-Matched Warps are required by CompareWarp regardless of the coadd type requested. Only PSF-Matched Warps make sense for image subtraction. Therefore, they must be in the InputDatasetField and made available to the task. (InputDatasetConfig, default lsst.pipe.base.config.InputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{inputCoaddName}Coadd_psfMatchedWarp', dimensions=['tract', 'patch', 'skymap', 'visit'], scalar=False, manualLoad=True))

quantum¶: configuration for PipelineTask quantum (QuantumConfig, default <class 'lsst.pipe.base.config.QuantumConfig'>)

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)

skyMap¶: Input definition of geometry/bbox and projection/wcs for coadded exposures (InputDatasetConfig, default lsst.pipe.base.config.InputDatasetConfig(name='', storageClass='SkyMap', nameTemplate='{inputCoaddName}Coadd_skyMap', dimensions=['skymap'], scalar=True, manualLoad=False))

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.

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:	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.

See also

lsst.pex.config.history.format

formatTemplateNames(templateParamsDict)¶

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: Field name. Field value.

See also

lsst.pex.config.Config.iteritems

iteritems()¶

Iterate over (field name, field value) pairs.

Yields:	item : `tuple` Tuple items are: Field name. Field value.

See also

lsst.pex.config.Config.items

iterkeys()¶

Iterate over field names

Yields:	key : `str` A field’s key (attribute name).

See also

lsst.pex.config.Config.values

itervalues()¶

Iterate over field values.

Yields:	value : obj A field value.

See also

lsst.pex.config.Config.values

keys()¶

Get field names.

Returns:	names : `list` 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:

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.

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:	values : `list` List of field values.

See also

lsst.pex.config.Config.itervalues

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DcrAssembleCoaddConfig¶