libera_utils.footprint_matching.aggregation.AggregationResult#

class libera_utils.footprint_matching.aggregation.AggregationResult(values: dict[str, Any], n_valid: int, n_total: int)#

Bases: object

Output of a single aggregation, with sample bookkeeping.

The values dict holds the strategy’s named sub-results (e.g. {"mean": ...}, {"mode": ..., "coverage_fractions": ...}). Footprint coverage is not recorded here: a swath gap has no samples, so it can only be measured on the weigher’s reference grid (WeightField.coverage), which check_coverage() scores.

Variables:

  • values (dict[str, Any]) – Named results produced by the strategy function.

  • n_valid (int) – Number of samples that contributed (finite value, positive weight).

  • n_total (int) – Number of samples considered (the sample set’s size).

__init__(values: dict[str, Any], n_valid: int, n_total: int) → None#