CompareWarpAssembleCoaddConfig¶
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class
lsst.pipe.tasks.assembleCoadd.CompareWarpAssembleCoaddConfig¶ Bases:
lsst.pipe.tasks.assembleCoadd.AssembleCoaddConfigAttributes Summary
assembleStaticSkyModelTask to assemble an artifact-free, PSF-matched Coadd to serve as a naive/first-iteration model of the static sky. badMaskPlanesMask planes that, if set, the associated pixel should not be included in the coaddTempExp. brightObjectMaskInput Bright Object Mask mask produced with external catalogs to be applied to the mask plane BRIGHT_OBJECT. brightObjectMaskNameName of mask bit used for bright objects ( str, default'BRIGHT_OBJECT')calcErrorFromInputVarianceCalculate coadd variance from input variance by stacking statistic.Passed to StatisticsControl.setCalcErrorFromInputVariance() ( bool, defaultTrue)clipIterNumber of iterations of outlier rejection; ignored if non-clipping statistic selected. coaddExposureOutput coadded exposure, produced by stacking input warps ( OutputDatasetConfig, defaultlsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{outputCoaddName}Coadd', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))coaddNameCoadd name: typically one of deep or goodSeeing. coaddPsfConfiguration for CoaddPsf ( CoaddPsfConfig, default<class 'lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsfConfig'>)detectDetect outlier sources on difference between each psfMatched warp and static sky model ( ConfigurableInstance, default<class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)detectTemplateDetect sources on static sky model. doApplyUberCalApply jointcal WCS and PhotoCalib results to input calexps? ( bool, defaultFalse)doAttachTransmissionCurveAttach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves). doInterpInterpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly. doMaskBrightObjectsSet mask and flag bits for bright objects? ( bool, defaultFalse)doNImageCreate image of number of contributing exposures for each pixel ( bool, defaultFalse)doPrefilterArtifactsIgnore artifact candidates that are mostly covered by the bad pixel mask, because they will be excluded anyway. doPreserveContainedBySourceRescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd. doPsfMatchMatch to modelPsf? Deprecated. doScaleWarpVarianceRescale Warp variance plane using empirical noise? ( bool, defaultTrue)doSigmaClipPerform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED) ( bool, defaultFalse)doUsePsfMatchedPolygonsUse ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only. doWritePersist coadd? ( bool, defaultTrue)hasFakesShould be set to True if fake sources have been inserted into the input data. historyincludeCalibVarAdd photometric calibration variance to warp variance plane. inputRecorderSubtask that helps fill CoaddInputs catalogs added to the final Exposure ( ConfigurableInstance, default<class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)inputWarpsInput list of warps to be assemebled i.e. interpImageTask to interpolate (and extrapolate) over NaN pixels ( ConfigurableInstance, default<class 'lsst.pipe.tasks.interpImage.InterpImageConfig'>)maskPropagationThresholdsThreshold (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. matchingKernelSizeSize in pixels of matching kernel. maxFractionEpochsHighFraction of local number of epochs (N) to use as effective maxNumEpochs for high N. maxFractionEpochsLowFraction of local number of epochs (N) to use as effective maxNumEpochs for low N. maxNumEpochsCharactistic maximum local number of epochs/visits in which an artifact candidate can appear and still be masked. modelPsfModel Psf factory ( ConfigurableInstance, default<class 'lsst.meas.algorithms.gaussianPsfFactory.GaussianPsfFactory'>)nImageOutput image of number of input images per pixel ( OutputDatasetConfig, defaultlsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ImageU', nameTemplate='{outputCoaddName}Coadd_nImage', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))prefilterArtifactsMaskPlanesPrefilter artifact candidates that are mostly covered by these bad mask planes. prefilterArtifactsRatioPrefilter artifact candidates with less than this fraction overlapping good pixels ( float, default0.05)psfMatchedWarpsPSF-Matched Warps are required by CompareWarp regardless of the coadd type requested. quantumconfiguration for PipelineTask quantum ( QuantumConfig, default<class 'lsst.pipe.base.config.QuantumConfig'>)removeMaskPlanesMask planes to remove before coadding ( List, default['NOT_DEBLENDED'])scaleWarpVarianceRescale variance on warps ( ConfigurableInstance, default<class 'lsst.pipe.tasks.scaleVariance.ScaleVarianceConfig'>)scaleZeroPointTask to adjust the photometric zero point of the coadd temp exposures ( ConfigurableInstance, default<class 'lsst.pipe.tasks.scaleZeroPoint.ScaleZeroPointConfig'>)selectImage selection subtask. sigmaClipSigma for outlier rejection; ignored if non-clipping statistic selected. skyMapInput definition of geometry/bbox and projection/wcs for coadded exposures ( InputDatasetConfig, defaultlsst.pipe.base.config.InputDatasetConfig(name='', storageClass='SkyMap', nameTemplate='{inputCoaddName}Coadd_skyMap', dimensions=['skymap'], scalar=True, manualLoad=False))spatialThresholdUnitless fraction of pixels defining how much of the outlier region has to meet the temporal criteria. statisticMain stacking statistic for aggregating over the epochs. subregionSizeWidth, height of stack subregion size; make small enough that a full stack of images will fit into memory at once. useMeasMosaicUse meas_mosaic’s applyMosaicResultsExposure() to do the photometric calibration/wcs update (deprecated). warpTypeWarp name: one of ‘direct’ or ‘psfMatched’ ( str, default'direct')Methods Summary
compare(other[, shortcut, rtol, atol, output])Compare this configuration to another Configfor 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
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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'>)
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badMaskPlanes¶ Mask planes that, if set, the associated pixel should not be included in the coaddTempExp. (
List, default('NO_DATA',))
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brightObjectMask¶ Input Bright Object Mask mask produced with external catalogs to be applied to the mask plane BRIGHT_OBJECT. (
InputDatasetConfig, defaultlsst.pipe.base.config.InputDatasetConfig(name='brightObjectMask', storageClass='ObjectMaskCatalog', nameTemplate='', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))
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calcErrorFromInputVariance¶ Calculate coadd variance from input variance by stacking statistic.Passed to StatisticsControl.setCalcErrorFromInputVariance() (
bool, defaultTrue)
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clipIter¶ Number of iterations of outlier rejection; ignored if non-clipping statistic selected. (
int, default2)
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coaddExposure¶ Output coadded exposure, produced by stacking input warps (
OutputDatasetConfig, defaultlsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{outputCoaddName}Coadd', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))
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coaddPsf¶ Configuration for CoaddPsf (
CoaddPsfConfig, default<class 'lsst.meas.algorithms.coaddPsf.coaddPsf.CoaddPsfConfig'>)
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detect¶ Detect outlier sources on difference between each psfMatched warp and static sky model (
ConfigurableInstance, default<class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)
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detectTemplate¶ Detect sources on static sky model. Only used if doPreserveContainedBySource is True (
ConfigurableInstance, default<class 'lsst.meas.algorithms.detection.SourceDetectionConfig'>)
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doAttachTransmissionCurve¶ Attach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves). (
bool, defaultFalse)
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doInterp¶ Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly. (
bool, defaultTrue)
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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, defaultTrue)
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doPreserveContainedBySource¶ Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd. Replicates a behavior of SafeClip. (
bool, defaultTrue)
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doPsfMatch¶ Match to modelPsf? Deprecated. Sets makePsfMatched=True, makeDirect=False (
bool, defaultFalse)
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doSigmaClip¶ Perform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED) (
bool, defaultFalse)
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doUsePsfMatchedPolygons¶ Use ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only. (
bool, defaultFalse)
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hasFakes¶ Should be set to True if fake sources have been inserted into the input data. (
bool, defaultFalse)
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history¶
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inputRecorder¶ Subtask that helps fill CoaddInputs catalogs added to the final Exposure (
ConfigurableInstance, default<class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)
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inputWarps¶ Input list of warps to be assemebled i.e. stacked.WarpType (e.g. direct, psfMatched) is controlled by we warpType config parameter (
InputDatasetConfig, defaultlsst.pipe.base.config.InputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{inputCoaddName}Coadd_{warpType}Warp', dimensions=['tract', 'patch', 'skymap', 'visit', 'instrument'], scalar=False, manualLoad=True))
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interpImage¶ Task to interpolate (and extrapolate) over NaN pixels (
ConfigurableInstance, default<class 'lsst.pipe.tasks.interpImage.InterpImageConfig'>)
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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})
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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, default0.03)Valid Range = [0.0,1.0)
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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, default0.4)Valid Range = [0.0,1.0)
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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, default2)
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modelPsf¶ Model Psf factory (
ConfigurableInstance, default<class 'lsst.meas.algorithms.gaussianPsfFactory.GaussianPsfFactory'>)
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nImage¶ Output image of number of input images per pixel (
OutputDatasetConfig, defaultlsst.pipe.base.config.OutputDatasetConfig(name='', storageClass='ImageU', nameTemplate='{outputCoaddName}Coadd_nImage', dimensions=['tract', 'patch', 'skymap', 'abstract_filter'], scalar=True, manualLoad=False))
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prefilterArtifactsMaskPlanes¶ Prefilter artifact candidates that are mostly covered by these bad mask planes. (
List, default('NO_DATA', 'BAD', 'SAT', 'SUSPECT'))
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prefilterArtifactsRatio¶ Prefilter artifact candidates with less than this fraction overlapping good pixels (
float, default0.05)
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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, defaultlsst.pipe.base.config.InputDatasetConfig(name='', storageClass='ExposureF', nameTemplate='{inputCoaddName}Coadd_psfMatchedWarp', dimensions=['tract', 'patch', 'skymap', 'visit'], scalar=False, manualLoad=True))
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quantum¶ configuration for PipelineTask quantum (
QuantumConfig, default<class 'lsst.pipe.base.config.QuantumConfig'>)
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removeMaskPlanes¶ Mask planes to remove before coadding (
List, default['NOT_DEBLENDED'])
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scaleWarpVariance¶ Rescale variance on warps (
ConfigurableInstance, default<class 'lsst.pipe.tasks.scaleVariance.ScaleVarianceConfig'>)
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scaleZeroPoint¶ Task to adjust the photometric zero point of the coadd temp exposures (
ConfigurableInstance, default<class 'lsst.pipe.tasks.scaleZeroPoint.ScaleZeroPointConfig'>)
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select¶ Image selection subtask. (
ConfigurableInstance, default<class 'lsst.pex.config.config.Config'>)
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sigmaClip¶ Sigma for outlier rejection; ignored if non-clipping statistic selected. (
float, default3.0)
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skyMap¶ Input definition of geometry/bbox and projection/wcs for coadded exposures (
InputDatasetConfig, defaultlsst.pipe.base.config.InputDatasetConfig(name='', storageClass='SkyMap', nameTemplate='{inputCoaddName}Coadd_skyMap', dimensions=['skymap'], scalar=True, manualLoad=False))
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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, default0.5)Valid Range = [0.0,1.0]
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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))
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useMeasMosaic¶ Use meas_mosaic’s applyMosaicResultsExposure() to do the photometric calibration/wcs update (deprecated). (
bool, defaultFalse)
Methods Documentation
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compare(other, shortcut=True, rtol=1e-08, atol=1e-08, output=None)¶ Compare this configuration to another
Configfor equality.Parameters: - other :
lsst.pex.config.Config Other
Configobject to compare against this config.- shortcut :
bool, optional If
True, return as soon as an inequality is found. Default isTrue.- 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 Truewhen the twolsst.pex.config.Configinstances are equal.Falseif there is an inequality.
See also
Notes
Unselected targets of
RegistryFieldfields and unselected choices ofConfigChoiceFieldfields are not considered by this method.Floating point comparisons are performed by
numpy.allclose.- other :
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formatHistory(name, **kwargs)¶ Format a configuration field’s history to a human-readable format.
Parameters: - name :
str Name of a
Fieldin this config.- kwargs
Keyword arguments passed to
lsst.pex.config.history.format.
Returns: - history :
str A string containing the formatted history.
See also
- name :
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formatTemplateNames(templateParamsDict)¶
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freeze()¶ Make this config, and all subconfigs, read-only.
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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
- items :
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iteritems()¶ Iterate over (field name, field value) pairs.
Yields: - item :
tuple Tuple items are:
- Field name.
- Field value.
See also
- item :
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itervalues()¶ Iterate over field values.
Yields: - value : obj
A field value.
See also
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keys()¶ Get field names.
Returns: - names :
list List of
lsst.pex.config.Fieldnames.
See also
- names :
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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
myFieldis set to5.Deprecated: For backwards compatibility, older config files that use
root="root"instead ofroot="config"will be loaded with a warning printed tosys.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- filename :
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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
myFieldis set to5.Deprecated: For backwards compatibility, older config files that use
root="root"instead ofroot="config"will be loaded with a warning printed tosys.stderr. This feature will be removed at some point.- filename :
str, optional Name of the configuration file, or
Noneif 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- stream : file-like object,
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names()¶ Get all the field names in the config, recursively.
Returns:
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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).
- filename :
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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).
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setDefaults()¶ Subclass hook for computing defaults.
Notes
Derived
Configclasses that must compute defaults rather than using theFieldinstances’s defaults should do so here. To correctly use inherited defaults, implementations ofsetDefaultsmust call their base class’ssetDefaults.
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toDict()¶ Make a dictionary of field names and their values.
Returns: See also
Notes
This method uses the
toDictmethod of individual fields. Subclasses ofFieldmay need to implement atoDictmethod for this method to work.
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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
__atand__labelkeyword 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 aConfiginstance’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
fieldAandfieldC:>>> 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!'
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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
validatemethods.Complex single-field validation can be defined by deriving new Field types. For convenience, some derived
lsst.pex.config.Field-types (ConfigFieldandConfigChoiceField) are defined inlsst.pex.configthat handle recursing into subconfigs.Inter-field relationships should only be checked in derived
Configclasses after calling this method, and base validation is complete.
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