CalcRelativeDistances¶
- class lsst.analysis.tools.actions.keyedData.CalcRelativeDistances(*args, **kw)¶
Bases:
KeyedDataAction
Calculate relative distances in a matched catalog.
Given a catalog of matched sources from multiple visits, this finds all pairs of objects at a given separation, then calculates the separation of their component source measurements from the individual visits. The RMS of these is used to calculate the astrometric relative repeatability metric, AMx, while the overall distribution of separations is used to compute the ADx and AFx metrics.
Attributes Summary
Radial distance of the annulus in arcmin (
float
, default5.0
)Dec column key (
str
, default'coord_dec'
)Column key to use for forming groups (
str
, default'obj_index'
)Maximum number of pairs to use; downsample otherwise.
RA column key (
str
, default'coord_ra'
)Random seed to use when downsampling.
Threshold in mas for AFx calculation.
Percentile of differences that can vary by more than threshAD.
Column key to use for matching visits (
str
, default'visit'
)Width of annulus in arcmin (
float
, default2.0
)Methods Summary
__call__
(data, **kwargs)Run the calculation.
Return the schema an
AnalysisAction
expects to be present in the arguments supplied to the __call__ method.Attributes Documentation
Methods Documentation
- __call__(data: MutableMapping[str, ndarray[Any, dtype[ScalarType]] | Scalar | HealSparseMap | Tensor], **kwargs) MutableMapping[str, ndarray[Any, dtype[ScalarType]] | Scalar | HealSparseMap | Tensor] ¶
Run the calculation.
- Parameters:
- dataKeyedData
Catalog of data including coordinate, visit, and object group information.
- Returns:
- 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