+class KReduction:
+ """
+ Scale the points gained or lost for players based on time played in the given game.
+ """
+ def __init__(self, full_time=600, min_time=120, min_ratio=0.5):
+ # full time is the time played to count the player in a game
+ self.full_time = full_time
+
+ # min time is the time played to count the player at all in a game
+ self.min_time = min_time
+
+ # min_ratio is the ratio of the game's time to be played to be counted fully (provided
+ # they went past `full_time` and `min_time` above.
+ self.min_ratio = min_ratio
+
+ def eval(self, my_time, match_time):
+ # kick out players who didn't play enough of the match
+ if my_time < self.min_time:
+ return 0.0
+
+ if my_time < self.min_ratio * match_time:
+ return 0.0
+
+ # scale based on time played versus what is defined as `full_time`
+ if my_time < self.full_time:
+ k = my_time / float(self.full_time)
+ else:
+ k = 1.0
+
+ return k
+
+
+# Parameters for reduction of points
+KREDUCTION = KReduction()
+
+
+class GlickoWIP(object):
+ """ A work-in-progress Glicko value. """
+ def __init__(self, pg):
+ """
+ Initialize a GlickoWIP instance.
+ :param pg: the player's PlayerGlicko record.
+ """
+ # the player's current (or base) PlayerGlicko record
+ self.pg = pg
+
+ # the list of k factors for each game in the ranking period
+ self.k_factors = []
+
+ # the list of ping factors for each game in the ranking period
+ self.ping_factors = []
+
+ # the list of opponents (PlayerGlicko or PlayerGlickoBase) in the ranking period
+ self.opponents = []
+
+ # the list of results for those games in the ranking period
+ self.results = []
+
+
+class GlickoProcessor(object):
+ """
+ Processes an arbitrary list games using the Glicko2 algorithm.
+ """
+ def __init__(self, session):
+ """
+ Create a GlickoProcessor instance.
+
+ :param session: the SQLAlchemy session to use for fetching/saving records.
+ """
+ self.session = session
+ self.wips = {}
+
+ def _pingratio(self, pi, pj):
+ """
+ Calculate the ping differences between the two players, but only if both have them.
+
+ :param pi: the latency of player I
+ :param pj: the latency of player J
+ :return: float
+ """
+ if pi is None or pj is None or pi < 0 or pj < 0:
+ # default to a draw
+ return 0.5
+
+ else:
+ return float(pi)/(pi+pj)
+
+ def _load_game(self, game_id):
+ try:
+ game = self.session.query(Game).filter(Game.game_id==game_id).one()
+ return game
+ except Exception as e:
+ log.error("Game ID {} not found.".format(game_id))
+ log.error(e)
+ raise e
+
+ def _load_pgstats(self, game):
+ """
+ Retrieve the game stats from the database for the game in question.
+
+ :param game: the game record whose player stats will be retrieved
+ :return: list of PlayerGameStat
+ """
+ try:
+ pgstats_raw = self.session.query(PlayerGameStat)\
+ .filter(PlayerGameStat.game_id==game.game_id)\
+ .filter(PlayerGameStat.player_id > 2)\
+ .all()
+
+ except Exception as e:
+ log.error("Error fetching player_game_stat records for game {}".format(game.game_id))
+ log.error(e)
+ raise e
+
+ pgstats = []
+ for pgstat in pgstats_raw:
+ # ensure warmup isn't included in the pgstat records
+ if pgstat.alivetime > game.duration:
+ pgstat.alivetime = game.duration
+
+ # ensure players played enough of the match to be included
+ k = KREDUCTION.eval(pgstat.alivetime.total_seconds(), game.duration.total_seconds())
+ if k <= 0.0:
+ continue
+ else:
+ pgstats.append(pgstat)
+
+ return pgstats
+
+ def _load_glicko_wip(self, player_id, game_type_cd, category):
+ """
+ Retrieve a PlayerGlicko record from the database.
+
+ :param player_id: the player ID to fetch
+ :param game_type_cd: the game type code
+ :param category: the category of glicko to retrieve
+ :return: PlayerGlicko
+ """
+ if (player_id, game_type_cd, category) in self.wips:
+ return self.wips[(player_id, game_type_cd, category)]
+
+ try:
+ pg = self.session.query(PlayerGlicko)\
+ .filter(PlayerGlicko.player_id==player_id)\
+ .filter(PlayerGlicko.game_type_cd==game_type_cd)\
+ .filter(PlayerGlicko.category==category)\
+ .one()
+
+ except:
+ pg = PlayerGlicko(player_id, game_type_cd, category)
+
+ # cache this in the wips dict
+ wip = GlickoWIP(pg)
+ self.wips[(player_id, game_type_cd, category)] = wip
+
+ return wip
+
+ def load(self, game_id):
+ """
+ Load all of the needed information from the database. Compute results for each player pair.
+ """
+ game = self._load_game(game_id)
+ pgstats = self._load_pgstats(game)
+ game_type_cd = game.game_type_cd
+ category = game.category
+
+ # calculate results:
+ # wipi/j => work in progress record for player i/j
+ # ki/j => k reduction value for player i/j
+ # si/j => score per second for player i/j
+ # pi/j => ping ratio for player i/j
+ for i in xrange(0, len(pgstats)):
+ wipi = self._load_glicko_wip(pgstats[i].player_id, game_type_cd, category)
+ ki = KREDUCTION.eval(pgstats[i].alivetime.total_seconds(),
+ game.duration.total_seconds())
+ si = pgstats[i].score/float(game.duration.total_seconds())
+
+ for j in xrange(i+1, len(pgstats)):
+ # ping factor is opponent-specific
+ pi = self._pingratio(pgstats[i].avg_latency, pgstats[j].avg_latency)
+ pj = 1.0 - pi
+
+ wipj = self._load_glicko_wip(pgstats[j].player_id, game_type_cd, category)
+ kj = KREDUCTION.eval(pgstats[j].alivetime.total_seconds(),
+ game.duration.total_seconds())
+ sj = pgstats[j].score/float(game.duration.seconds)
+
+ # normalize scores
+ ofs = min(0.0, si, sj)
+ si -= ofs
+ sj -= ofs
+ if si + sj == 0:
+ si, sj = 1, 1 # a draw
+
+ scorefactor_i = si / float(si + sj)
+ scorefactor_j = 1.0 - si
+
+ wipi.k_factors.append(ki)
+ wipi.ping_factors.append(pi)
+ wipi.opponents.append(wipj.pg)
+ wipi.results.append(scorefactor_i)
+
+ wipj.k_factors.append(kj)
+ wipj.ping_factors.append(pj)
+ wipj.opponents.append(wipi.pg)
+ wipj.results.append(scorefactor_j)
+
+ def process(self):
+ """
+ Calculate the Glicko2 ratings, deviations, and volatility updates for the records loaded.
+ """
+ for wip in self.wips.values():
+ new_pg = rate(wip.pg, wip.opponents, wip.results)
+
+ log.debug("New rating for player {} before factors: mu={} phi={} sigma={}"
+ .format(pg.player_id, new_pg.mu, new_pg.phi, new_pg.sigma))
+
+ avg_k_factor = sum(wip.k_factors)/len(wip.k_factors)
+ avg_ping_factor = LATENCY_TREND_FACTOR * sum(wip.ping_factors)/len(wip.ping_factors)
+
+ points_delta = (new_pg.mu - wip.pg.mu) * avg_k_factor * avg_ping_factor
+
+ wip.pg.mu += points_delta
+ wip.pg.phi = new_pg.phi
+ wip.pg.sigma = new_pg.sigma
+
+ log.debug("New rating for player {} after factors: mu={} phi={} sigma={}"
+ .format(wip.pg.player_id, wip.pg.mu, wip.pg.phi, wip.pg.sigma))
+
+ def save(self, session):
+ """
+ Put all changed PlayerElo and PlayerGameStat instances into the
+ session to be updated or inserted upon commit.
+ """
+ pass
+
+