MakeDirectWarpConfig

class lsst.drp.tasks.make_direct_warp.MakeDirectWarpConfig(*args, **kw)

Bases: PipelineTaskConfig

Configuration for the MakeDirectWarpTask.

The config fields are as similar as possible to the corresponding fields in MakeWarpConfig.

Notes

The config fields are in camelCase to match the fields in the earlier version of the makeWarp task as closely as possible.

Attributes Summary

MAX_NUMBER_OF_NOISE_REALIZATIONS

numberOfNoiseRealizations is defined as a RangeField to prevent from making multiple output connections and blowing up the memory usage by accident.

bgSubtracted

border

Pad the patch boundary of the warp by these many pixels, so as to allow for PSF-matching later (int, default 256)

coaddPsf

Configuration for CoaddPsf (CoaddPsfConfig, default <class 'lsst.meas.algorithms.CoaddPsfConfig'>)

connections

Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.

doApplyNewBackground

Apply the new backgrounds from the background_apply_list connection? (bool, default False)

doApplySkyCorr

doPreWarpInterpolation

Interpolate over bad pixels before warping? (bool, default False)

doRevertOldBackground

Revert the old backgrounds from the background_revert_list connection? (bool, default False)

doSelectPreWarp

Select ccds before warping? (bool, default True)

doWarpMaskedFraction

Warp the masked fraction image? (bool, default False)

history

idGenerator

Configuration for how to generate catalog IDs from data IDs.

includeCalibVar

Add photometric calibration variance to warp variance plane? (bool, default False)

inputRecorder

Subtask that helps fill CoaddInputs catalogs added to the final coadd (ConfigurableInstance, default <class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)

maskedFractionWarper

Configuration for the warp that warps the mask fraction image (WarperConfig, default <class 'lsst.afw.math._warper.WarperConfig'>)

numberOfNoiseRealizations

Number of noise realizations to simulate and persist.

preWarpInterpolation

Interpolation task to use for pre-warping interpolation (ConfigurableInstance, default <class 'lsst.meas.algorithms.cloughTocher2DInterpolator.CloughTocher2DInterpolateConfig'>)

saveLogOutput

Flag to enable/disable saving of log output for a task, enabled by default.

seedOffset

Offset to the seed used for the noise realization.

select

Image selection subtask.

useMedianVariance

Use the median of variance plane in the input calexp to generate noise realizations? If False, per-pixel variance will be used.

useVisitSummaryPsf

If True, use the PSF model and aperture corrections from the 'visit_summary' connection to make the warp.

warper

Configuration for the warper that warps the image and noise (WarperConfig, default <class 'lsst.afw.math._warper.WarperConfig'>)

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

MAX_NUMBER_OF_NOISE_REALIZATIONS = 3

numberOfNoiseRealizations is defined as a RangeField to prevent from making multiple output connections and blowing up the memory usage by accident. An upper bound of 3 is based on the best guess of the maximum number of noise realizations that will be used for metadetection.

bgSubtracted
border

Pad the patch boundary of the warp by these many pixels, so as to allow for PSF-matching later (int, default 256)

coaddPsf

Configuration for CoaddPsf (CoaddPsfConfig, default <class 'lsst.meas.algorithms.CoaddPsfConfig'>)

connections: pexConfig.ConfigField

Field which refers to a dynamically added configuration class which is based on a PipelineTaskConnections class.

doApplyNewBackground

Apply the new backgrounds from the background_apply_list connection? (bool, default False)

doApplySkyCorr
doPreWarpInterpolation

Interpolate over bad pixels before warping? (bool, default False)

doRevertOldBackground

Revert the old backgrounds from the background_revert_list connection? (bool, default False)

doSelectPreWarp

Select ccds before warping? (bool, default True)

doWarpMaskedFraction

Warp the masked fraction image? (bool, default False)

history

Read-only history.

idGenerator

Configuration for how to generate catalog IDs from data IDs. (DetectorVisitIdGeneratorConfig, default <class 'lsst.meas.base._id_generator.DetectorVisitIdGeneratorConfig'>)

includeCalibVar

Add photometric calibration variance to warp variance plane? (bool, default False)

inputRecorder

Subtask that helps fill CoaddInputs catalogs added to the final coadd (ConfigurableInstance, default <class 'lsst.pipe.tasks.coaddInputRecorder.CoaddInputRecorderConfig'>)

maskedFractionWarper

Configuration for the warp that warps the mask fraction image (WarperConfig, default <class 'lsst.afw.math._warper.WarperConfig'>)

numberOfNoiseRealizations

Number of noise realizations to simulate and persist. (int, default 0)

Valid Range = [0,3]

preWarpInterpolation

Interpolation task to use for pre-warping interpolation (ConfigurableInstance, default <class 'lsst.meas.algorithms.cloughTocher2DInterpolator.CloughTocher2DInterpolateConfig'>)

saveLogOutput

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

seedOffset

Offset to the seed used for the noise realization. This can be used to create a different noise realization if the default ones are catastrophic, or for testing sensitivity to the noise. (int, default 0)

select

Image selection subtask. (ConfigurableInstance, default <class 'lsst.pipe.tasks.selectImages.PsfWcsSelectImagesConfig'>)

useMedianVariance

Use the median of variance plane in the input calexp to generate noise realizations? If False, per-pixel variance will be used. (bool, default True)

useVisitSummaryPsf

If True, use the PSF model and aperture corrections from the ‘visit_summary’ connection to make the warp. If False, use the PSF model and aperture corrections from the ‘calexp’ connection. (bool, default True)

warper

Configuration for the warper that warps the image and noise (WarperConfig, default <class 'lsst.afw.math._warper.WarperConfig'>)

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() None

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.