FlagSelector

class lsst.analysis.tools.actions.vector.FlagSelector(*args, **kw)

Bases: SelectorBase

The base flag selector to use to select valid sources for QA.

Attributes Summary

plotLabelKey	Key to use when populating plot info, ignored if empty string (str, default '')
selectWhenFalse	Names of the flag columns to select on when False (List, default [])
selectWhenTrue	Names of the flag columns to select on when True (List, default [])

Methods Summary

__call__(data, **kwargs)	Select on the given flags
getInputSchema()	Return the schema an AnalysisAction expects to be present in the arguments supplied to the __call__ method.

Attributes Documentation

plotLabelKey

Key to use when populating plot info, ignored if empty string (str, default '')

selectWhenFalse

Names of the flag columns to select on when False (List, default [])

selectWhenTrue

Names of the flag columns to select on when True (List, default [])

Methods Documentation

__call__(data: MutableMapping[str, ndarray[tuple[Any, ...], dtype[_ScalarT]] | Scalar | HealSparseMap | Tensor | Mapping], **kwargs) → ndarray[tuple[Any, ...], dtype[_ScalarT]]

Select on the given flags

Parameters

data : KeyedData

Returns

resultVector

A mask of the objects that satisfy the given flag cuts.

Notes

Uses the columns in selectWhenFalse and selectWhenTrue to decide which columns to select on in each circumstance.

getInputSchema() → Iterable[tuple[str, type[ndarray[tuple[Any, ...], dtype[_ScalarT]]] | type[Scalar] | type[HealSparseMap] | type[Tensor] | type[Mapping]]]

Return the schema an AnalysisAction expects to be present in the arguments supplied to the __call__ method.

Returns

resultKeyedDataSchema

The schema this action requires to be present when calling this action, keys are unformatted.