MatcherProbabilistic

class lsst.meas.astrom.MatcherProbabilistic(config: MatchProbabilisticConfig)

Bases: object

A probabilistic, greedy catalog matcher.

Parameters:

config: `MatchProbabilisticConfig`

A configuration instance.

Methods Summary

match(catalog_ref, catalog_target[, ...])

Match catalogs.

Methods Documentation

match(catalog_ref: DataFrame, catalog_target: DataFrame, select_ref: Optional[array] = None, select_target: Optional[array] = None, logger: Optional[Logger] = None, logging_n_rows: Optional[int] = None, **kwargs)

Match catalogs.

Parameters:

catalog_refpandas.DataFrame

A reference catalog to match in order of a given column (i.e. greedily).

catalog_targetpandas.DataFrame

A target catalog for matching sources from catalog_ref. Must contain measurements with errors.

select_refnumpy.array

A boolean array of the same length as catalog_ref selecting the sources that can be matched.

select_targetnumpy.array

A boolean array of the same length as catalog_target selecting the sources that can be matched.

loggerlogging.Logger

A Logger for logging.

logging_n_rowsint

The number of sources to match before printing a log message.

kwargs

Additional keyword arguments to pass to format_catalogs.

Returns:

catalog_out_refpandas.DataFrame

A catalog of identical length to catalog_ref, containing match information for rows selected by select_ref (including the matching row index in catalog_target).

catalog_out_targetpandas.DataFrame

A catalog of identical length to catalog_target, containing the indices of matching rows in catalog_ref.

exceptionsdict [int, Exception]

A dictionary keyed by catalog_target row number of the first exception caught when matching.