self.pg = pg
# the list of k factors for each game in the ranking period
- self.ks = []
+ 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 = []
class GlickoProcessor(object):
"""
- Processes the given list games using the Glicko2 algorithm.
+ 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.
- :param game_ids: the list of game_ids that need to be processed.
"""
self.session = session
self.wips = {}
- def scorefactor(self, si, sj, game_type_cd):
- """
- Calculate the real scorefactor of the game. This is how players
- actually performed, which is compared to their expected performance.
-
- :param si: the score per second of player I
- :param sj: the score per second of player J
- :param game_type_cd: the game type of the game in question
- :return: float
- """
- scorefactor_real = si / float(si + sj)
-
- # duels are done traditionally - a win nets
- # full points, not the score factor
- if game_type_cd == 'duel':
- # player i won
- if scorefactor_real > 0.5:
- scorefactor_real = 1.0
- # player j won
- elif scorefactor_real < 0.5:
- scorefactor_real = 0.0
- # nothing to do here for draws
-
- return scorefactor_real
-
- def pingfactor(self, pi, pj):
+ def _pingratio(self, pi, pj):
"""
Calculate the ping differences between the two players, but only if both have them.
else:
return float(pi)/(pi+pj)
- def load(self, game_id):
- """
- Load all of the needed information from the database.
- """
+ def _load_game(self, game_id):
try:
game = self.session.query(Game).filter(Game.game_id==game_id).one()
- except:
+ return game
+ except Exception as e:
log.error("Game ID {} not found.".format(game_id))
- return
+ 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_id)\
+ .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
- for pgstat in pgstats_raw:
- if pgstat.alivetime > game.duration:
- pgstat.alivetime = game.duration
+ if pgstat.alivetime > game.duration:
+ pgstat.alivetime = game.duration
+
+ # ensure players played enough of the match to be included
+ k = KREDUCTION.eval(pgstat.alivetime.seconds, game.duration.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:
- log.error("Error fetching player_game_stat records for game {}".format(self.game_id))
- return
+ 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.seconds, game.duration.seconds)
+ si = pgstats[i].score/float(game.duration.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.seconds, game.duration.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):
"""