SnSelector¶
- class lsst.analysis.tools.actions.vector.SnSelector(*args, **kw)¶
Bases:
SelectorBase
Selects points that have S/N > threshold in the given flux type.
Attributes Summary
The bands to apply the signal to noise cut in.Takes precedence if bands passed to call (
List
, default[]
)Flux type to calculate the S/N in.
Maximum S/N to include in the sample (to allow S/N ranges).
Key to use when populating plot info, ignored if empty string (
str
, default''
)The S/N threshold to remove sources with.
Suffix to add to fluxType to specify uncertainty column (
str
, default'Err'
)Methods Summary
__call__
(data, **kwargs)Makes a mask of objects that have S/N greater than self.threshold in self.fluxType
Return the schema an
AnalysisAction
expects to be present in the arguments supplied to the __call__ method.Attributes Documentation
- bands¶
The bands to apply the signal to noise cut in.Takes precedence if bands passed to call (
List
, default[]
)
Methods Documentation
- __call__(data: MutableMapping[str, ndarray[Any, dtype[ScalarType]] | Scalar | HealSparseMap | Tensor], **kwargs) ndarray[Any, dtype[ScalarType]] ¶
Makes a mask of objects that have S/N greater than self.threshold in self.fluxType
- Parameters:
- data
KeyedData
The data to perform the selection on.
- data
- Returns:
- result
Vector
A mask of the objects that satisfy the given S/N cut.
- result
- getInputSchema() Tensor]]] ¶
Return the schema an
AnalysisAction
expects to be present in the arguments supplied to the __call__ method.- Returns:
- result
KeyedDataSchema
The schema this action requires to be present when calling this action, keys are unformatted.
- result