PhotonTransferCurveSolveConfig¶

class lsst.cp.pipe.PhotonTransferCurveSolveConfig(*args, **kw)¶

Bases: PipelineTaskConfig

Configuration for fitting measured covariances.

Attributes Summary

`ampOffsetGainRatioMaxAdu`	Maximum number of adu to use for amp offset gain ratio fixup.
`ampOffsetGainRatioMinAdu`	Minimum number of adu to use for amp offset gain ratio fixup.
`binSize`	Bin the image by this factor in both dimensions.
`connections`	Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.
`consecutivePointsVarDecreases`	Required number of consecutive points/fluxes in the PTC where the variance decreases in order to find a first estimate of the PTC turn-off.
`doAmpOffsetGainRatioFixup`	Do gain ratio fixup based on amp offsets? (`bool`, default `False`)
`doFitBootstrap`	Use bootstrap for the PTC fit parameters and errors?.
`doLegacyTurnoffSelection`	Use 'legacy' computation for PTC turnoff selection.
`doSubtractLongRangeCovariances`	Subtract long-range covariances before FULLCOVARIANCE fit, beyond startLongRangeCovariances? (`bool`, default `False`)
`history`
`ksTestMinPvalue`	Minimum value of the Gaussian histogram KS test p-value to be used in PTC fit.
`maxDeltaInitialPtcOutlierFit`	If there are any outliers in the initial fit that have mean greater than maxSignalInitialPtcOutlierFit, then no points that have this delta mean from the previous `good` point are allowed.
`maxIterFullFitCovariancesAstier`	Maximum number of iterations in full model fit for FULLCOVARIANCE ptcFitType (`int`, default `3`)
`maxIterationsPtcOutliers`	Maximum number of iterations for outlier rejection in PTC.
`maxMeanSignal`	Maximum values (inclusive) of mean signal (in adu) below which to consider, per amp.
`maxSignalInitialPtcOutlierFit`	Maximum signal considered for intial outlier fit.
`maximumRangeCovariancesAstier`	Maximum range of measured covariances as in Astier+19 (`int`, default `8`)
`maximumRangeCovariancesAstierFullCovFit`	Maximum range up to where to fit covariances as in Astier+19, for the FULLCOVARIANCE model.This is different from maximumRangeCovariancesAstier.It should be less or equal than maximumRangeCovariancesAstier.The number of parameters for this model is 3*maximumRangeCovariancesAstierFullCovFit^2 + 1, so increase with care so that the fit is not too slow.
`minMeanSignal`	Minimum values (inclusive) of mean signal (in adu) per amp to use.
`minVarPivotSearch`	The code looks for a pivot signal point after which the variance starts decreasing at high-flux to exclude then from the PTC model fit.
`polyDegLongRangeCovariances`	If doSubtractLongRangeCovariances is True, polynomial degree to fit data beyond startLongRangeCovariances.
`polynomialFitDegree`	Degree of polynomial to fit the PTC, when 'ptcFitType'=POLYNOMIAL.
`ptcFitType`	Fit PTC to Eq.
`saveLogOutput`	Flag to enable/disable saving of log output for a task, enabled by default.
`scaleMaxSignalInitialPtcOutlierFit`	Scale maxSignalInitialPtcOutlierFit and maxDeltaInitialPtcOutlierFit by approximate gain? If yes then maxSignalInitialPtcOutlierFit and maxDeltaInitialPtcOutlierFit are assumed to have units of electrons, otherwise adu.
`sigmaClipFullFitCovariancesAstier`	sigma clip for full model fit for FULLCOVARIANCE ptcFitType (`float`, default `5.0`)
`sigmaCutPtcOutliers`	Sigma cut for outlier rejection in PTC.
`startLongRangeCovariances`	If doSubtractLongRangeCovariances is True, subtract covariances beyond this range.

Methods Summary

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

Attributes Documentation

ampOffsetGainRatioMaxAdu¶: Maximum number of adu to use for amp offset gain ratio fixup. (float, default 20000.0)

ampOffsetGainRatioMinAdu¶: Minimum number of adu to use for amp offset gain ratio fixup. (float, default 1000.0)

binSize¶: Bin the image by this factor in both dimensions. (int, default 1)

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

consecutivePointsVarDecreases¶

Required number of consecutive points/fluxes in the PTC where the variance decreases in order to find a first estimate of the PTC turn-off. Only used if doLegacyTurnoffSelection is True. (int, default 2)

Valid Range = [2,inf)

doAmpOffsetGainRatioFixup¶: Do gain ratio fixup based on amp offsets? (bool, default False)

doFitBootstrap¶: Use bootstrap for the PTC fit parameters and errors?. (bool, default False)

doLegacyTurnoffSelection¶: Use ‘legacy’ computation for PTC turnoff selection. If set to False, then the KS test p-value selection will be used instead. (bool, default False)

doSubtractLongRangeCovariances¶: Subtract long-range covariances before FULLCOVARIANCE fit, beyond startLongRangeCovariances? (bool, default False)

history¶: Read-only history.

ksTestMinPvalue¶: Minimum value of the Gaussian histogram KS test p-value to be used in PTC fit. Only used if doLegacyTurnoffSelection is False. (float, default 0.01)

maxDeltaInitialPtcOutlierFit¶: If there are any outliers in the initial fit that have mean greater than maxSignalInitialPtcOutlierFit, then no points that have this delta mean from the previous good point are allowed. If scaleMaxSignalInitialPtcOutlierFit=True then the units are electrons; otherwise adu. (float, default 9000.0)

maxIterFullFitCovariancesAstier¶: Maximum number of iterations in full model fit for FULLCOVARIANCE ptcFitType (int, default 3)

maxIterationsPtcOutliers¶

Maximum number of iterations for outlier rejection in PTC. (int, default 2)

Valid Range = [0,inf)

maxMeanSignal¶: Maximum values (inclusive) of mean signal (in adu) below which to consider, per amp. The same cut is applied to all amps if this dictionary is of the form {‘ALL_AMPS’: value} (Dict, default {'ALL_AMPS': 1000000.0})

maxSignalInitialPtcOutlierFit¶: Maximum signal considered for intial outlier fit. This should be below the PTC turnoff to ensure accurate outlier rejection. If scaleMaxSignalInitialPtcOutlierFit=True then the units are electrons; otherwise adu. (float, default 50000.0)

maximumRangeCovariancesAstier¶: Maximum range of measured covariances as in Astier+19 (int, default 8)

maximumRangeCovariancesAstierFullCovFit¶: Maximum range up to where to fit covariances as in Astier+19, for the FULLCOVARIANCE model.This is different from maximumRangeCovariancesAstier.It should be less or equal than maximumRangeCovariancesAstier.The number of parameters for this model is 3*maximumRangeCovariancesAstierFullCovFit^2 + 1, so increase with care so that the fit is not too slow. (int, default 8)

minMeanSignal¶: Minimum values (inclusive) of mean signal (in adu) per amp to use. The same cut is applied to all amps if this parameter [dict] is passed as {‘ALL_AMPS’: value} (Dict, default {'ALL_AMPS': 0.0})

minVarPivotSearch¶: The code looks for a pivot signal point after which the variance starts decreasing at high-flux to exclude then from the PTC model fit. However, sometimes at low fluxes, the variance decreases slightly. Set this variable for the variance value, in adu^2, after which the pivot should be sought. Only used if doLegacyTurnoffSelection is True. (float, default 10000)

polyDegLongRangeCovariances¶: If doSubtractLongRangeCovariances is True, polynomial degree to fit data beyond startLongRangeCovariances. (int, default 1)

polynomialFitDegree¶: Degree of polynomial to fit the PTC, when ‘ptcFitType’=POLYNOMIAL. (int, default 3)

ptcFitType¶

Fit PTC to Eq. 16, Eq. 20 in Astier+19, or to a polynomial. (str, default 'POLYNOMIAL')

Allowed values:

'POLYNOMIAL': n-degree polynomial (use ‘polynomialFitDegree’ to set ‘n’).
'EXPAPPROXIMATION': Approximation in Astier+19 (Eq. 16).
'FULLCOVARIANCE': Full covariances model in Astier+19 (Eq. 20)
'None': Field is optional

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

scaleMaxSignalInitialPtcOutlierFit¶: Scale maxSignalInitialPtcOutlierFit and maxDeltaInitialPtcOutlierFit by approximate gain? If yes then maxSignalInitialPtcOutlierFit and maxDeltaInitialPtcOutlierFit are assumed to have units of electrons, otherwise adu. (bool, default True)

sigmaClipFullFitCovariancesAstier¶: sigma clip for full model fit for FULLCOVARIANCE ptcFitType (float, default 5.0)

sigmaCutPtcOutliers¶: Sigma cut for outlier rejection in PTC. (float, default 5.0)

startLongRangeCovariances¶: If doSubtractLongRangeCovariances is True, subtract covariances beyond this range. It should be less than maximumRangeCovariancesAstier. (int, default 4)

Methods Documentation

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

Apply config overrides to this config instance.

Parameters:

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

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

Compare this configuration to another Config for equality.

Parameters:

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

Returns:

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

See also

lsst.pex.config.compareConfigs

Notes

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

Floating point comparisons are performed by numpy.allclose.

formatHistory(name, **kwargs)¶

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

Parameters:

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

Returns:

historystr: A string containing the formatted history.

See also

lsst.pex.config.history.format

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

items()¶

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

Returns:

itemsItemsView

Iterator of tuples for each configuration. Tuple items are:

Field name.
Field value.

keys()¶

Get field names.

Returns:

namesKeysView: 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:

filenamestr

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

rootstr, optional

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

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

config.myField = 5

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

See also

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

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

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

Parameters:

streamfile-like object, str, bytes, or CodeType

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

rootstr, optional

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

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

config.myField = 5

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

filenamestr, optional

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

extraLocalsdict of str to object, optional

Any extra variables to include in local scope when loading.

See also

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

Notes

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

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

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

Parameters:

codestr, bytes, or CodeType

Stream containing configuration override code.

rootstr, optional

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

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

config.myField = 5

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

filenamestr, optional

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

extraLocalsdict of str to object, optional

Any extra variables to include in local scope when loading.

Raises:

ValueError: Raised if a key in extraLocals is the same value as the value of the root argument.

See also

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

names()¶

Get all the field names in the config, recursively.

Returns:

nameslist of str: Field names.

save(filename, root='config')¶

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

Parameters:

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

See also

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

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

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

Parameters:

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

See also

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

saveToString(skipImports=False)¶

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

Parameters:

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

Returns:

codestr: A code string readable by loadFromString.

See also

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

setDefaults()¶

Subclass hook for computing defaults.

Notes

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

toDict()¶

Make a dictionary of field names and their values.

Returns:

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

See also

lsst.pex.config.Field.toDict

Notes

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

update(**kw)¶

Update values of fields specified by the keyword arguments.

Parameters:

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

Notes

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

Examples

This is a config with three fields:

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

These are the default values of each field:

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

Using this method to update fieldA and fieldC:

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

Now the values of each field are:

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

validate()¶

Validate the Config, raising an exception if invalid.

Raises:

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

Notes

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

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

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

values()¶

Get field values.

Returns:

valuesValuesView: Iterator of field values.

Navigation

PhotonTransferCurveSolveConfig¶