CalcBinnedStatsAction¶
- class lsst.analysis.tools.actions.vector.CalcBinnedStatsAction(*args, **kw)¶
Bases:
KeyedDataAction
Attributes Summary
Vector on which to compute statistics (
str
)Field name to append stat names to (
str
, default''
)Field name to append to stat names (
str
, default''
)Whether to return the bin minimum and maximum (
bool
, defaultTrue
)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.Return the schema an
AnalysisAction
will produce, if the__call__
method returnsKeyedData
, otherwise this may return None.Attributes Documentation
- name_count¶
- name_mask¶
- name_median¶
- name_select_maximum¶
- name_select_median¶
- name_select_minimum¶
- name_sigmaMad¶
- 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:
- result
KeyedDataSchema
The schema this action requires to be present when calling this action, keys are unformatted.
- result
- getOutputSchema() Tensor]]] ¶
Return the schema an
AnalysisAction
will produce, if the__call__
method returnsKeyedData
, otherwise this may return None.- Returns:
- result
KeyedDataSchema
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
.
- result