ColorDiff#

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

Bases: VectorAction

Calculate the difference between two colors from flux actions.

Attributes Summary

`color1_flux1`	Action providing first color's first flux (`VectorAction`, default `<class 'lsst.analysis.tools.interfaces._actions.VectorAction'>`)
`color1_flux2`	Action providing first color's second flux (`VectorAction`, default `<class 'lsst.analysis.tools.interfaces._actions.VectorAction'>`)
`color2_flux1`	Action providing second color's first flux (`VectorAction`, default `<class 'lsst.analysis.tools.interfaces._actions.VectorAction'>`)
`color2_flux2`	Action providing second color's second flux (`VectorAction`, default `<class 'lsst.analysis.tools.interfaces._actions.VectorAction'>`)
`returnMillimags`	Whether to return color_diff in millimags (mags if not) (`bool`, default `True`)

Methods Summary

`__call__`(data, **kwargs)	Call self as a function.
`getInputSchema`()	Return the schema an `AnalysisAction` expects to be present in the arguments supplied to the __call__ method.

Attributes Documentation

color1_flux1#: Action providing first color’s first flux (VectorAction, default <class 'lsst.analysis.tools.interfaces._actions.VectorAction'>)

color1_flux2#: Action providing first color’s second flux (VectorAction, default <class 'lsst.analysis.tools.interfaces._actions.VectorAction'>)

color2_flux1#: Action providing second color’s first flux (VectorAction, default <class 'lsst.analysis.tools.interfaces._actions.VectorAction'>)

color2_flux2#: Action providing second color’s second flux (VectorAction, default <class 'lsst.analysis.tools.interfaces._actions.VectorAction'>)

returnMillimags#: Whether to return color_diff in millimags (mags if not) (bool, default True)

Methods Documentation

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

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.