PhotonTransferCurveSolveConfig

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

Bases: PipelineTaskConfig

Configuration for fitting measured covariances.

Attributes Summary

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.

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.

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 by approximate gain? If yes then maxSignalInitialPtcOutlierFit is 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

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)

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)

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 by approximate gain? If yes then maxSignalInitialPtcOutlierFit is 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.

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.

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:

  1. Field name.

  2. 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.

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.

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.

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).

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.

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.

setDefaults()

Subclass hook for computing defaults.

Notes

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

toDict()

Make a dictionary of field names and their values.

Returns:
dict_dict

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

Notes

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

update(**kw)

Update values of fields specified by the keyword arguments.

Parameters:
**kw

Keywords are configuration field names. Values are configuration field values.

Notes

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

Examples

This is a config with three fields:

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

These are the default values of each field:

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

Using this method to update fieldA and fieldC:

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

Now the values of each field are:

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

Validate the Config, raising an exception if invalid.

Raises:
lsst.pex.config.FieldValidationError

Raised if verification fails.

Notes

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

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

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

values()

Get field values.

Returns:
valuesValuesView

Iterator of field values.