openskill package# Subpackages# openskill.models package Submodules openskill.models.bradley_terry_full module BradleyTerryFull BradleyTerryFull.calculate() openskill.models.bradley_terry_part module BradleyTerryPart BradleyTerryPart.calculate() openskill.models.plackett_luce module PlackettLuce PlackettLuce.calculate() openskill.models.thurstone_mosteller_full module openskill.models.thurstone_mosteller_part module Module contents Submodules# openskill.constants module# class openskill.constants.Constants(**options)[source]# Bases: object openskill.constants.beta(**options) → float[source]# openskill.constants.beta_squared(**options) → float[source]# openskill.constants.epsilon(**options) → float[source]# openskill.constants.mu(**options) → float[source]# openskill.constants.sigma(**options) → float[source]# openskill.constants.tau(**options) → float[source]# openskill.constants.z(**options) → float[source]# openskill.rate module# openskill.statistics module# openskill.util module# openskill.util.gamma(**options)[source]# openskill.util.ladder_pairs(ranks: List[int])[source]# openskill.util.rank_minimum(a)[source]# openskill.util.rank_simple(vector)[source]# openskill.util.rankings(teams, rank: Optional[List[int]] = None)[source]# openskill.util.score(q, i) → float[source]# openskill.util.transpose(xs)[source]# openskill.util.unwind(ranks, teams) → Tuple[List, List[int]][source]# openskill.util.util_a(team_ratings)[source]# openskill.util.util_c(team_ratings, **options)[source]# openskill.util.util_sum_q(team_ratings, c)[source]# Module contents#