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
, defaultTrue
)clipIter
Number of iterations of outlier rejection; ignored if non-clipping statistic selected. 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)
)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'>
)detectTemplate
Detect sources on static sky model. detection
Task to detect sources for PSF measurement, if doCalculatePsf
is set.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
, defaultFalse
)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
, defaultTrue
)doInterp
Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly. doMaskBrightObjects
Set mask and flag bits for bright objects? ( bool
, defaultFalse
)doNImage
Create image of number of contributing exposures for each pixel ( bool
, defaultFalse
)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
, defaultTrue
)doSigmaClip
Perform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED) ( bool
, defaultFalse
)doUsePsfMatchedPolygons
Use ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only. doWrite
Persist coadd? ( bool
, defaultTrue
)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.measurement
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
, defaultlsst.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
, default0.05
)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
, defaultlsst.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
, defaultTrue
)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
, defaultTrue
)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 ofbaseGain
.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
, default3
)
-
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
, defaultNone
)
-
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)
)
-
calcErrorFromInputVariance
¶ Calculate coadd variance from input variance by stacking statistic.Passed to StatisticsControl.setCalcErrorFromInputVariance() (
bool
, defaultTrue
)
-
clipIter
¶ Number of iterations of outlier rejection; ignored if non-clipping statistic selected. (
int
, default2
)
-
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)
)
-
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
, default0.001
)
-
dcrNumSubfilters
¶ Number of sub-filters to forward model chromatic effects to fit the supplied exposures. (
int
, default3
)
-
detect
¶ Detect outlier sources on difference between each psfMatched warp and static sky model (
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'>
)
-
detection
¶ Task to detect sources for PSF measurement, if
doCalculatePsf
is set. (ConfigurableInstance
, default<class 'lsst.pipe.tasks.multiBand.DetectCoaddSourcesConfig'>
)
-
doAirmassWeight
¶ Weight exposures by airmass? Useful if there are relatively few high-airmass observations. (
bool
, defaultFalse
)
-
doAttachTransmissionCurve
¶ Attach a piecewise TransmissionCurve for the coadd? (requires all input Exposures to have TransmissionCurves). (
bool
, defaultFalse
)
-
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
, defaultTrue
)
-
doInterp
¶ Interpolate over NaN pixels? Also extrapolate, if necessary, but the results are ugly. (
bool
, defaultTrue
)
-
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
)
-
doPreserveContainedBySource
¶ Rescue artifacts from clipping that completely lie within a footprint detectedon the PsfMatched Template Coadd. Replicates a behavior of SafeClip. (
bool
, defaultTrue
)
-
doPsfMatch
¶ Match to modelPsf? Deprecated. Sets makePsfMatched=True, makeDirect=False (
bool
, defaultFalse
)
-
doSigmaClip
¶ Perform sigma clipped outlier rejection with MEANCLIP statistic? (DEPRECATED) (
bool
, defaultFalse
)
-
doUsePsfMatchedPolygons
¶ Use ValidPolygons from shrunk Psf-Matched Calexps? Should be set to True by CompareWarp only. (
bool
, defaultFalse
)
-
hasFakes
¶ Should be set to True if fake sources have been inserted into the input data. (
bool
, defaultFalse
)
-
history
¶
-
imageInterpOrder
¶ The order of the spline interpolation used to shift the image plane. (
int
, default3
)
-
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
, defaultlsst.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}
)
-
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)
-
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)
-
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
)
-
measurePsf
¶ Task to measure the PSF of the coadd, if
doCalculatePsf
is set. (ConfigurableInstance
, default<class 'lsst.pipe.tasks.measurePsf.MeasurePsfConfig'>
)
-
measurement
¶ Task to measure sources for PSF measurement, if
doCalculatePsf
is set. (ConfigurableInstance
, default<class 'lsst.meas.base.sfm.SingleFrameMeasurementConfig'>
)
-
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
, default3
)
-
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)
)
-
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
, default0.05
)
-
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
, defaultlsst.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
, default2
)
-
regularizeModelFrequency
¶ Maximum relative change of the model allowed between subfilters.Set to zero to disable. (
float
, default4.0
)
-
regularizeModelIterations
¶ Maximum relative change of the model allowed between iterations.Set to zero to disable. (
float
, default2.0
)
-
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
, default3.0
)
-
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)
)
-
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]
-
splitSubfilters
¶ Calculate DCR for two evenly-spaced wavelengths in each subfilter.Instead of at the midpoint (
bool
, defaultTrue
)
-
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
, defaultTrue
)
-
useMeasMosaic
¶ Use meas_mosaic’s applyMosaicResultsExposure() to do the photometric calibration/wcs update (deprecated). (
bool
, defaultFalse
)
-
useModelWeights
¶ Width of the region around detected sources to include in the DcrModel. (
bool
, defaultTrue
)
-
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 ofbaseGain
. (bool
, defaultTrue
)
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 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
True
when the twolsst.pex.config.Config
instances are equal.False
if there is an inequality.
See also
Notes
Unselected targets of
RegistryField
fields and unselected choices ofConfigChoiceField
fields are not considered by this method.Floating point comparisons are performed by
numpy.allclose
.- other :
-
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
- name :
-
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
- items :
-
iteritems
()¶ Iterate over (field name, field value) pairs.
Yields: - item :
tuple
Tuple items are:
- Field name.
- Field value.
See also
- item :
-
itervalues
()¶ Iterate over field values.
Yields: - value : obj
A field value.
See also
-
keys
()¶ Get field names.
Returns: - names :
list
List of
lsst.pex.config.Field
names.
See also
- 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 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 :
-
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 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
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
- stream : file-like object,
-
names
()¶ Get all the field names in the config, recursively.
Returns:
-
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 :
-
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 theField
instances’s defaults should do so here. To correctly use inherited defaults, implementations ofsetDefaults
must call their base class’ssetDefaults
.
-
toDict
()¶ Make a dictionary of field names and their values.
Returns: See also
Notes
This method uses the
toDict
method of individual fields. Subclasses ofField
may need to implement atoDict
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 aConfig
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
andfieldC
:>>> 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
andConfigChoiceField
) are defined inlsst.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.
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