CalcBinnedStatsAction¶

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

Bases: KeyedDataAction

Attributes Summary

`key_vector`	Vector on which to compute statistics (`str`)
`name_count`
`name_mask`
`name_median`
`name_prefix`	Field name to append stat names to (`str`, default `''`)
`name_select_maximum`
`name_select_median`
`name_select_minimum`
`name_sigmaMad`
`name_suffix`	Field name to append to stat names (`str`, default `''`)
`selector_range`	Range selector (`RangeSelector`, default `<class 'lsst.analysis.tools.actions.vector.selectors.RangeSelector'>`)

Methods Summary

`__call__`(data, **kwargs)	Call self as a function.
`getInputSchema`(**kwargs)	Return the schema an `AnalysisAction` expects to be present in the arguments supplied to the __call__ method.
`getOutputSchema`()	Return the schema an `AnalysisAction` will produce, if the `__call__` method returns `KeyedData`, otherwise this may return None.

Attributes Documentation

selector_range¶: Range selector (RangeSelector, default <class 'lsst.analysis.tools.actions.vector.selectors.RangeSelector'>)

Methods Documentation

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

getInputSchema(**kwargs) → Tensor]]]¶

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.

getOutputSchema() → Tensor]]]¶

Return the schema an AnalysisAction will produce, if the __call__ method returns KeyedData, otherwise this may return None.

Returns:

resultKeyedDataSchema or None: The schema this action will produce when returning from call. This will be unformatted if any templates are present. Should return None if action does not return KeyedData.