X-Git-Url: http://de.git.xonotic.org/?a=blobdiff_plain;f=xonstat%2Fmodels.py;h=84a64ea9a665fc6c9d49e52f12c041d8d48bca17;hb=016bec5e5150cd0357379afb43463f1975b9119b;hp=e8eb3a371051a7f23e74763ff975c082ff27c604;hpb=9ec79a0c28ea3a6f7958188bac04808564ea1f02;p=xonotic%2Fxonstat.git diff --git a/xonstat/models.py b/xonstat/models.py index e8eb3a3..84a64ea 100644 --- a/xonstat/models.py +++ b/xonstat/models.py @@ -8,7 +8,6 @@ from sqlalchemy.orm import mapper from sqlalchemy.orm import scoped_session from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base -from xonstat.elo import KREDUCTION, ELOPARMS from xonstat.util import strip_colors, html_colors, pretty_date log = logging.getLogger(__name__) @@ -99,159 +98,6 @@ class Game(object): def fuzzy_date(self): return pretty_date(self.start_dt) - def process_elos(self, session, game_type_cd=None): - if game_type_cd is None: - game_type_cd = self.game_type_cd - - # we do not have the actual duration of the game, so use the - # maximum alivetime of the players instead - duration = 0 - for d in session.query(sfunc.max(PlayerGameStat.alivetime)).\ - filter(PlayerGameStat.game_id==self.game_id).\ - one(): - duration = d.seconds - - scores = {} - alivetimes = {} - winners = [] - for (p,s,a,r,t) in session.query(PlayerGameStat.player_id, - PlayerGameStat.score, PlayerGameStat.alivetime, - PlayerGameStat.rank, PlayerGameStat.team).\ - filter(PlayerGameStat.game_id==self.game_id).\ - filter(PlayerGameStat.alivetime > timedelta(seconds=0)).\ - filter(PlayerGameStat.player_id > 2).\ - all(): - # scores are per second - scores[p] = s/float(a.seconds) - alivetimes[p] = a.seconds - - # winners are either rank 1 or on the winning team - # team games are where the team is set (duh) - if r == 1 or (t == self.winner and t is not None): - winners.append(p) - - player_ids = scores.keys() - - elos = {} - for e in session.query(PlayerElo).\ - filter(PlayerElo.player_id.in_(player_ids)).\ - filter(PlayerElo.game_type_cd==game_type_cd).all(): - elos[e.player_id] = e - - # ensure that all player_ids have an elo record - for pid in player_ids: - if pid not in elos.keys(): - elos[pid] = PlayerElo(pid, game_type_cd) - - for pid in player_ids: - elos[pid].k = KREDUCTION.eval(elos[pid].games, alivetimes[pid], - duration) - if elos[pid].k == 0: - del(elos[pid]) - del(scores[pid]) - del(alivetimes[pid]) - - elos = self.update_elos(session, elos, scores, winners, ELOPARMS) - - # add the elos to the session for committing - for e in elos: - session.add(elos[e]) - - # no longer calculate DM elo for a duel game - # if game_type_cd == 'duel': - # self.process_elos(session, "dm") - - - def update_elos(self, session, elos, scores, winners, ep): - eloadjust = {} - for pid in elos.keys(): - eloadjust[pid] = 0 - - if len(elos) < 2: - return elos - - pids = elos.keys() - - for i in xrange(0, len(pids)): - ei = elos[pids[i]] - for j in xrange(i+1, len(pids)): - ej = elos[pids[j]] - si = scores[ei.player_id] - sj = scores[ej.player_id] - - # normalize scores - ofs = min(0, si, sj) - si -= ofs - sj -= ofs - if si + sj == 0: - si, sj = 1, 1 # a draw - - # real score factor - scorefactor_real = si / float(si + sj) - - # estimated score factor by elo - elodiff = min(ep.maxlogdistance, max(-ep.maxlogdistance, - (float(ei.elo) - float(ej.elo)) * ep.logdistancefactor)) - scorefactor_elo = 1 / (1 + math.exp(-elodiff)) - - # how much adjustment is good? - # scorefactor(elodiff) = 1 / (1 + e^(-elodiff * logdistancefactor)) - # elodiff(scorefactor) = -ln(1/scorefactor - 1) / logdistancefactor - # elodiff'(scorefactor) = 1 / ((scorefactor) (1 - scorefactor) logdistancefactor) - # elodiff'(scorefactor) >= 4 / logdistancefactor - - # adjust'(scorefactor) = K1 + K2 - - # so we want: - # K1 + K2 <= 4 / logdistancefactor <= elodiff'(scorefactor) - # as we then don't overcompensate - - adjustment = scorefactor_real - scorefactor_elo - eloadjust[ei.player_id] += adjustment - eloadjust[ej.player_id] -= adjustment - - elo_deltas = {} - for pid in pids: - new_elo = max(float(elos[pid].elo) + eloadjust[pid] * elos[pid].k * ep.global_K / float(len(elos) - 1), ep.floor) - - log.debug("Player {0}'s Elo would be going from {1} to {2}.".format(pid, - elos[pid].elo, new_elo)) - - # winners are not penalized with negative elo - if pid in winners and new_elo < elos[pid].elo: - elo_deltas[pid] = 0.0 - else: - elos[pid].elo = new_elo - elo_deltas[pid] = new_elo - float(elos[pid].elo) - - elos[pid].games += 1 - - self.save_elo_deltas(session, elo_deltas) - - return elos - - - def save_elo_deltas(self, session, elo_deltas): - """ - Saves the amount by which each player's Elo goes up or down - in a given game in the PlayerGameStat row, allowing for scoreboard display. - - elo_deltas is a dictionary such that elo_deltas[player_id] is the elo_delta - for that player_id. - """ - pgstats = {} - for pgstat in session.query(PlayerGameStat).\ - filter(PlayerGameStat.game_id == self.game_id).\ - all(): - pgstats[pgstat.player_id] = pgstat - - for pid in elo_deltas.keys(): - try: - pgstats[pid].elo_delta = elo_deltas[pid] - session.add(pgstats[pid]) - except: - log.debug("Unable to save Elo delta value for player_id {0}".format(pid)) - class PlayerGameStat(object): def __init__(self, player_game_stat_id=None, create_dt=None): @@ -334,13 +180,13 @@ class PlayerNick(object): class PlayerElo(object): - def __init__(self, player_id=None, game_type_cd=None): + def __init__(self, player_id=None, game_type_cd=None, elo=None): self.player_id = player_id self.game_type_cd = game_type_cd + self.elo = elo self.score = 0 self.games = 0 - self.elo = ELOPARMS.initial def __repr__(self): return "" % (self.player_id, self.game_type_cd, self.elo)