def get_new_ratings(players, teams):
"""
Affect new ratings to players from teams results
"""
nb_players_team0 = len(teams[0])
nb_players_team1 = len(teams[1])
winner = players[teams[0][0]]
loser = players[teams[1][0]]
if nb_players_team0 == 1 and nb_players_team1 == 1:
new_r1, new_r3 = rate_1vs1(winner,loser)
elif nb_players_team0 == 1 and nb_players_team1 > 1:
team_loser = [loser, players[teams[1][1]]]
(new_r1), (new_r3, new_r4) = rate([winner, team_loser], ranks=[0, 1])
elif nb_players_team0 > 1 and nb_players_team1 == 1:
team_winner = [winner, players[teams[0][1]]]
(new_r1, new_r2), (new_r3) = rate([team_winner, loser], ranks=[0, 1])
else:
team_loser = [loser, players[teams[1][1]]]
team_winner = [winner, players[teams[0][1]]]
(new_r1, new_r2), (new_r3, new_r4) = rate([team_winner, team_loser], ranks=[0, 1])
player1 = {'name': teams[0][0], 'mu': new_r1.mu, 'sigma': new_r1.sigma}
player3 = {'name': teams[1][0], 'mu': new_r3.mu, 'sigma': new_r3.sigma}
if nb_players_team0 > 1:
player2 = {'name': teams[0][1], 'mu': new_r2.mu, 'sigma': new_r2.sigma}
if nb_players_team1 > 1:
player4 = {'name': teams[1][1], 'mu': new_r4.mu, 'sigma': new_r4.sigma}
if nb_players_team0 > 1:
return [player1, player2, player3, player4]
return [player1, player2, player4]
return [player1, player3]
def update_trueskill(self):
"""
Updates the game’s participants TrueSkill values based on the game result.
"""
import trueskill
session = object_session(self)
# participant.trueskill represents pre-game values
# p.player.ratings[p.role] is the PlayerRating relevant to the game that was scored
team_ratings = {
team: {
p.player.ratings[p.role]:
trueskill.Rating(p.trueskill_mu, p.trueskill_sigma)
for p in self.participants.values() if p.team == team
}
for team in ["blue", "red"]
}
if self.winner == "blue":
new_ratings = trueskill.rate(
[team_ratings["blue"], team_ratings["red"]])
else:
new_ratings = trueskill.rate(
[team_ratings["red"], team_ratings["blue"]])
for team in new_ratings:
for player_rating in team:
player_rating.trueskill_mu = team[player_rating].mu
player_rating.trueskill_sigma = team[player_rating].sigma
session.add(player_rating)
session.commit()
def form_valid(self, form):
from trueskill import Rating, rate
match = form.save(commit=False)
histories = []
if match.score_team2 > match.score_team1: # put winning team first
(match.score_team1, match.team1_player1, match.team1_player2,
match.score_team2, match.team2_player1, match.team2_player2) = \
(match.score_team2, match.team2_player1, match.team2_player2,
match.score_team1, match.team1_player1, match.team1_player2)
player_list = (match.team1_player1, match.team1_player2,
match.team2_player1, match.team2_player2)
ratings = [Rating(mu=p.mu, sigma=p.sigma) for p in player_list]
seperate_ratings = [
(Rating(mu=a.attacker_mu, sigma=a.attacker_sigma),
Rating(mu=d.defender_mu, sigma=d.defender_sigma))
for a, d in [player_list[0:2], player_list[2:4]]
]
ranks = [match.score_team2 > match.score_team1,
match.score_team2 < match.score_team1]
new_ratings = rate([ratings[0:2], ratings[2:4]], ranks=ranks)
new_ratings = new_ratings[0] + new_ratings[1]
new_seperate_ratings = rate(seperate_ratings, ranks=ranks)
new_seperate_ratings = \
new_seperate_ratings[0] + new_seperate_ratings[1]
match.save()
for i in range(len(player_list)):
p = player_list[i]
s = new_seperate_ratings[i]
p.mu = new_ratings[i].mu
p.sigma = new_ratings[i].sigma
p.rank = p.mu - 3 * p.sigma
h = PlayerHistory(match=match, player=p,
mu=p.mu, sigma=p.sigma, rank=p.rank,
seperate_mu=s.mu, seperate_sigma=s.sigma,
seperate_rank=(s.mu - 3 * s.sigma))
if not i % 2:
h.was_attacker = True
p.attacker_mu = s.mu
p.attacker_sigma = s.sigma
p.attacker_rank = s.mu - 3 * s.sigma
else:
h.was_attacker = False
p.defender_mu = s.mu
p.defender_sigma = s.sigma
p.defender_rank = s.mu - 3 * s.sigma
p.save()
p.old_mu = ratings[i].mu
p.old_sigma = ratings[i].sigma
p.old_rank = p.old_mu - 3 * p.old_sigma
histories.append(h)
PlayerHistory.objects.bulk_create(histories)
context = {
'match': match,
'player_list': player_list,
'ratings': ratings,
}
return render(self.request, 'league/match_enter_success.html', context)
def update_trueskill(game: Game, session):
"""
Updates the player’s rating based on the game’s result
"""
blue_team_ratings = {
participant.player.ratings[participant.role]:
trueskill.Rating(mu=participant.trueskill_mu,
sigma=participant.trueskill_sigma)
for participant in game.teams.BLUE
}
red_team_ratings = {
participant.player.ratings[participant.role]:
trueskill.Rating(mu=participant.trueskill_mu,
sigma=participant.trueskill_sigma)
for participant in game.teams.RED
}
if game.winner == "BLUE":
new_ratings = trueskill.rate([blue_team_ratings, red_team_ratings])
else:
new_ratings = trueskill.rate([red_team_ratings, blue_team_ratings])
for ratings in new_ratings:
for player_rating in ratings:
# This is the PlayerRating object
player_rating.trueskill_mu = ratings[player_rating].mu
player_rating.trueskill_sigma = ratings[player_rating].sigma
session.merge(player_rating)
def get_new_ratings(players, teams):
"""
Affect new ratings to players from teams results
"""
nb_players_team0 = len(teams[0])
nb_players_team1 = len(teams[1])
winner = players[teams[0][0]]
loser = players[teams[1][0]]
if nb_players_team0 == 1 and nb_players_team1 == 1:
new_r1, new_r3 = rate_1vs1(winner,loser)
elif nb_players_team0 == 1 and nb_players_team1 > 1:
team_loser = [loser, players[teams[1][1]]]
(new_r1), (new_r3, new_r4) = rate([winner, team_loser], ranks=[0, 1])
elif nb_players_team0 > 1 and nb_players_team1 == 1:
team_winner = [winner, players[teams[0][1]]]
(new_r1, new_r2), (new_r3) = rate([team_winner, loser], ranks=[0, 1])
else:
team_loser = [loser, players[teams[1][1]]]
team_winner = [winner, players[teams[0][1]]]
(new_r1, new_r2), (new_r3, new_r4) = rate([team_winner, team_loser], ranks=[0, 1])
player1 = {'name': teams[0][0], 'mu': new_r1.mu, 'sigma': new_r1.sigma}
player3 = {'name': teams[1][0], 'mu': new_r3.mu, 'sigma': new_r3.sigma}
if nb_players_team0 > 1:
player2 = {'name': teams[0][1], 'mu': new_r2.mu, 'sigma': new_r2.sigma}
if nb_players_team1 > 1:
player4 = {'name': teams[1][1], 'mu': new_r4.mu, 'sigma': new_r4.sigma}
if nb_players_team0 > 1:
return [player1, player2, player3, player4]
return [player1, player2, player4]
return [player1, player3]
def calculate_doubles_ratings(game_df,
rating_object=Rating(),
return_type='dataframe'):
for col in game_df.columns:
if 'player' in col:
game_df[col] = game_df[col].apply(remove_whitespace)
all_players = set(
list(game_df.player_a_team_a.unique()) +
list(game_df.player_b_team_a.unique()) +
list(game_df.player_a_team_b.unique()) +
list(game_df.player_b_team_b.unique()))
ratings = {k: rating_object for k in all_players}
for row in game_df.iterrows():
player_a_team_a = ratings[row[1]['player_a_team_a']]
player_b_team_a = ratings[row[1]['player_b_team_a']]
player_a_team_b = ratings[row[1]['player_a_team_b']]
player_b_team_b = ratings[row[1]['player_b_team_b']]
t_a = player_a_team_a, player_b_team_a
t_b = player_a_team_b, player_b_team_b
if row[1]['score_team_a'] > row[1]['score_team_b']:
t_a, t_b = rate([t_a, t_b], ranks=[0, 1])
elif row[1]['score_team_a'] < row[1]['score_team_b']:
t_a, t_b = rate([t_a, t_b], ranks=[1, 0])
else:
t_a, t_b = rate([t_a, t_b], ranks=[0, 0])
player_a_team_a, player_b_team_a = t_a
player_a_team_b, player_b_team_b = t_b
ratings[row[1]['player_a_team_a']] = player_a_team_a
ratings[row[1]['player_b_team_a']] = player_b_team_a
ratings[row[1]['player_a_team_b']] = player_a_team_b
ratings[row[1]['player_b_team_b']] = player_b_team_b
if return_type == 'dict':
return ratings
elif return_type == 'dataframe':
rating_df = pd.DataFrame()
for k, v in ratings.iteritems():
rating_df.loc[k, 'rating'] = v.mu
rating_df.loc[k, 'sigma'] = v.sigma
rating_df.loc[k, 'tau'] = v.tau
rating_df.loc[k, 'pi'] = v.pi
rating_df.loc[k, 'trueskill'] = v.exposure
rating_df.reset_index(inplace=True)
return rating_df
def test_compatibility_with_another_rating_systems():
"""All rating system modules should implement ``rate_1vs1`` and
``quality_1vs1`` to provide shortcuts for 1 vs 1 simple competition games.
"""
r1, r2 = Rating(30, 3), Rating(20, 2)
assert quality_1vs1(r1, r2) == quality([(r1,), (r2,)])
rated = rate([(r1,), (r2,)])
assert rate_1vs1(r1, r2) == (rated[0][0], rated[1][0])
rated = rate([(r1,), (r2,)], [0, 0])
assert rate_1vs1(r1, r2, drawn=True) == (rated[0][0], rated[1][0])
def test_compatibility_with_another_rating_systems():
"""All rating system modules should implement ``rate_1vs1`` and
``quality_1vs1`` to provide shortcuts for 1 vs 1 simple competition games.
"""
r1, r2 = Rating(30, 3), Rating(20, 2)
assert quality_1vs1(r1, r2) == quality([(r1, ), (r2, )])
rated = rate([(r1, ), (r2, )])
assert rate_1vs1(r1, r2) == (rated[0][0], rated[1][0])
rated = rate([(r1, ), (r2, )], [0, 0])
assert rate_1vs1(r1, r2, drawn=True) == (rated[0][0], rated[1][0])
def handle_match_elo(match: Match) -> None:
global matches_added, verbose
print("Handling match", match.key)
match_alliances = match.alliances.all()
print("\tDetermining Alliance and Team Winners...")
drawn = False
if match.winner is None:
drawn = True
ally_winner = match_alliances[0]
team_winners = ally_winner.teams.all()
else:
ally_winner = match.winner
team_winners = ally_winner.teams.all()
print("\tSelecting losing alliance...")
ally_loser = next(x for x in match_alliances if x.id != match.winner_id)
team_losers = ally_loser.teams.all()
print("\tRunning Alliance TrueSkill calculations...")
ally_winner_ts = Rating(ally_winner.elo_mu, ally_winner.elo_sigma)
ally_loser_ts = Rating(ally_loser.elo_mu, ally_loser.elo_sigma)
(ally_winner_result, ally_loser_result) = rate_1vs1(ally_winner_ts, ally_loser_ts, drawn=drawn)
ally_winner.elo_mu = ally_winner_result.mu
ally_winner.elo_sigma = ally_winner_result.sigma
ally_loser.elo_mu = ally_loser_result.mu
ally_loser.elo_sigma = ally_loser_result.sigma
team_winner_ts_pairs = [(t, Rating(t.elo_mu, t.elo_sigma)) for t in team_winners]
team_loser_ts_pairs = [(t, Rating(t.elo_mu, t.elo_sigma)) for t in team_losers]
print("\tRunning Team TrueSkill calculations...")
if drawn:
team_results = rate([[x[1] for x in team_winner_ts_pairs], [x[1] for x in team_loser_ts_pairs]], ranks=[0, 0])
else:
team_results = rate([[x[1] for x in team_winner_ts_pairs], [x[1] for x in team_loser_ts_pairs]])
print("\tUpdating team mu and sigma...")
result_and_teams = zip(team_results[0], team_winners, team_results[1], team_losers)
for winner_result, winner_team, loser_result, loser_team in result_and_teams:
winner_team.elo_mu = winner_result.mu
winner_team.elo_sigma = winner_result.sigma
loser_team.elo_mu = loser_result.mu
loser_team.elo_sigma = loser_result.sigma
print("\tSaving...")
ally_winner.save(update_fields=['elo_mu', 'elo_sigma'])
ally_loser.save(update_fields=['elo_mu', 'elo_sigma'])
Team.objects.bulk_update([*team_winners, *team_losers], update_fields=['elo_mu', 'elo_sigma'])
print("Done!")
matches_added += 1
def main():
a, b = Rating(25), Rating(30)
c = Rating()
d = Rating()
for i in range(9):
t1 = [a, b]
t2 = [c, d]
(a, b), (c, d) = rate([t1, t2], ranks=[0, 1])
print(a)
(a, b), (c, d) = rate([t1, t2], ranks=[1, 0])
print(a)
def eval_match(team1, team2, score1, score2):
# Update players in dictionary
for player in team1:
if player not in p:
p[player] = Player(player)
for player in team2:
if player not in p:
p[player] = Player(player)
global m
m += 1
# Update elos
s = 0.5
if score1 > score2:
s = 1
elif score1 < score2:
s = 0
global matches
matches.append((team1, team2, s))
# game counter
for player in team1:
p[player].add_game(s, score1)
for player in team2:
p[player].add_game(1 - s, score2)
t1 = [p[x].last_rating(ELO_MODEL) for x in team1]
t2 = [p[x].last_rating(ELO_MODEL) for x in team2]
t1_new, t2_new = elo.rate_match(t1, t2, s, 1 - s)
for player in team1:
p[player].add_rating(ELO_MODEL, t1_new.pop(0), m)
for player in team2:
p[player].add_rating(ELO_MODEL, t2_new.pop(0), m)
# Update trueskills
ranks = [0.5, 0.5]
if score1 > score2:
ranks = [0, 1]
elif score1 < score2:
ranks = [1, 0]
t1 = [p[x].last_rating(TRUESKILL_MODEL) for x in team1]
t2 = [p[x].last_rating(TRUESKILL_MODEL) for x in team2]
t1_new, t2_new = ts.rate([t1, t2], ranks=ranks)
t1_new = list(t1_new)
t2_new = list(t2_new)
for player in team1:
p[player].add_rating(TRUESKILL_MODEL, t1_new.pop(0), m)
for player in team2:
p[player].add_rating(TRUESKILL_MODEL, t2_new.pop(0), m)
def RatingRecount():
player_ratings = {p: Rating() for p in Player.objects.all()}
team_ratings = {t: Rating() for t in Team.objects.all()}
print "#"*60
print "RECOUNTING #"*4
print "#"*60
for match in Match.objects.order_by("id"):
# Get ratings for players
winners = {p: player_ratings[p] for p in match.winner.players.all()}
losers = {p: player_ratings[p] for p in match.loser.players.all()}
# Score the match
new_team_ratings = rate([winners, losers]) # Returns a list with a one or many dicts
for team in new_team_ratings:
for player, new_rating in team.iteritems():
player_ratings[player] = new_rating # save to database
# Team ranking
team_ratings[match.winner], team_ratings[match.loser] = rate_1vs1(team_ratings[match.winner], team_ratings[match.loser])
for player, rating in player_ratings.iteritems():
print player, " - ", rating.mu
player.mu = rating.mu
player.sigma = rating.sigma
player.save()
for team, rating in team_ratings.iteritems():
print team, " - ", rating.mu, team.mu
def getAdjList_Similarity3(self, QuestionList):
from trueskill import Rating, rate
AdjList = []
ext = ''
margin = 4
trainPairs = self.trainPairs
# compute trueSkill value
RatingDict = dict()
for i in trainPairs["Aer"].drop_duplicates().values.tolist():
RatingDict[i] = (Rating(), )
step1 = trainPairs.groupby(["Qid"])
for i, j in step1:
if int(i) in QuestionList:
IdList = j["Aer"].values.tolist()
rating = j["Credible"].apply(
lambda x: 1 - int(x)).values.tolist()
for i, j in zip(
IdList,
rate([RatingDict[x] for x in IdList], ranks=rating)):
RatingDict[i] = j
trainPairs["Rating"] = trainPairs["Aer"]
trainPairs["Rating"] = trainPairs["Rating"].apply(
lambda x: RatingDict[x][0].mu - 3 * RatingDict[x][0].sigma)
trainPairs["Link"] = [0 for i in range(len(trainPairs))]
self.Rating = trainPairs[["PairId", "Rating"]]
# create clique using trueSkill value
step2 = trainPairs.groupby(["Qid"])
idxList1 = []
idxList2 = []
for i, j in step2:
tempScore = sorted(j["Rating"].values.tolist())
if tempScore[-1] - tempScore[-2] >= margin:
idxList1.append(j["Rating"].idxmax())
if tempScore[1] - tempScore[0] >= margin / 2:
idxList2.append(j["Rating"].idxmin())
trainPairs.loc[idxList1, "Link"] = 1
trainPairs.loc[idxList2, "Link"] = 2
trainPairs["Credible"] = trainPairs["Credible"].apply(lambda x: int(x))
step3 = trainPairs[trainPairs["Link"].isin([1, 2])].groupby(
["Aer", "Link"])
for i, j in step3:
if len(j) >= 2:
for i in combinations(j["PairId"].tolist(), 2):
AdjList.append(i)
#exit()
AdjList = pd.DataFrame(data=AdjList, columns=["Nid1", "Nid2"])
AdjList = AdjList.drop_duplicates()
#AdjList = AdjList.sample(500)
print "similarity3:", len(AdjList)
edges = AdjList.sort_values(by=["Nid1", "Nid2"], ascending=True).values
with open(self.rootFolder + "/" + 'edges_' + 'line' + '.pkl',
'w') as f:
pickle.dump(edges, f)
return edges
def rate_outcome(race, runners, results, cache):
"""do rating from results, not finishingPosition (it is also 0 for non-placed)"""
parts = [r for r in runners if r['has_odds']]
logger.debug('{} participants'.format(len(parts)))
team = [(Rating(p['rating_mu'], p['rating_sigma']), ) for p in parts]
logger.debug('team = {}'.format(team))
for p in parts:
p['pos'] = 5
for i, result in enumerate(results):
for n in result:
for p in parts:
if p['runnerNumber'] == n:
logger.debug(
'outcome found: n {} and p {} at rank {}'.format(
n, p['runnerNumber'], i + 1))
p['pos'] = i + 1
break
pos = [p['pos'] for p in parts]
try:
new_ratings = rate(team, pos)
logger.debug('new ratings {}'.format(new_ratings))
except:
logger.info(team)
logger.info(pos)
raise
save_players(race, parts, new_ratings, cache)
def skill_commit_match_result(party_1, party_2, match_1_result):
"""
Adjust team's elo based on result
- Saves Player Models
Returns delta in ELO
"""
party_1_skill = skill_build_party_rating(party_1)
party_2_skill = skill_build_party_rating(party_2)
party_rosters = [party_1.players.all(), party_2.players.all()]
result_arr = [0, 1] if match_1_result else [1, 0]
result = rate([party_1_skill, party_2_skill], ranks=result_arr)
p_idx = 0
t_idx = 0
elo_deltas = [
abs(result[0][0].mu - party_rosters[0][0].elo),
abs(result[1][0].mu - party_rosters[1][0].elo)
]
for roster in party_rosters:
for player in roster:
print("%s -> %s" % (
int(player.elo),
int(result[t_idx][p_idx].mu),
))
player.elo = int(result[t_idx][p_idx].mu)
player.elo_weight = float(result[t_idx][p_idx].sigma)
player.save()
p_idx += 1
t_idx += 1 # Increase team index
p_idx = 0 # Reset player index
return elo_deltas
def run(self):
for game in Game.objects.filter(status__in=self.active_statuses):
try:
status = game.update_from_engine()
if game.is_leaderboard_game and game.status == Game.Status.COMPLETE:
sorted_snakes = sorted(sorted(status['snakes'].items(),
key=lambda s: s[1]['death']),
key=lambda s: s[1]['turn'],
reverse=True)
game_snake_ids = [s[0] for s in sorted_snakes]
game_snakes = GameSnake.objects.filter(
id__in=game_snake_ids)
snake_ids = [gs.snake_id for gs in game_snakes]
snakes = UserSnake.objects.filter(snake_id__in=snake_ids)
lb = [
UserSnakeLeaderboard.objects.get(user_snake=s)
for s in snakes
]
ratings = [(self.create_rating(l), ) for l in lb]
new_rankings = trueskill.rate(ratings,
ranks=list(
range(0, len(ratings))))
for x in range(0, len(ratings)):
r = new_rankings[x]
lb[x].mu = r[0].mu
lb[x].sigma = r[0].sigma
lb[x].save()
except Exception as e:
game.status = Game.Status.ERROR
game.save()
# Something wrong with this game, don't care
print(f'Unable to update game {game.id}', e)
pass
def compute_player_skills(rounds: [RoundRow], teams: [dict],
current_ratings: {int: trueskill.Rating} = None) \
-> ({int: trueskill.Rating}, [SkillHistory]):
ratings = {}
if current_ratings is not None:
ratings.update(current_ratings)
skill_history = []
for round in rounds:
rating_groups = (
{
player_id: ratings.get(player_id, trueskill.Rating())
for player_id in teams[round.winner]
},
{
player_id: ratings.get(player_id, trueskill.Rating())
for player_id in teams[round.loser]
},
)
new_ratings = trueskill.rate(rating_groups)
for rating in new_ratings:
ratings.update(rating)
for player_id, skill in rating.items():
skill_history.append(
SkillHistory(round_id=round.round_id,
player_id=player_id,
skill=skill))
return ratings, skill_history
def update_player_skill_values(self): winner_ratings = [] for winner in self.winners.all(): winner_ratings.append( trueskill.Rating(winner.rating_mu, winner.rating_sigma) ) winner_ratings = tuple(winner_ratings) loser_ratings = [] for loser in self.losers.all(): loser_ratings.append( trueskill.Rating(loser.rating_mu, loser.rating_sigma) ) loser_ratings = tuple(loser_ratings) match_rating_result = trueskill.rate([winner_ratings, loser_ratings]) i = 0 for winner in self.winners.all(): winner.rating_mu = match_rating_result[0][i].mu winner.rating_sigma = match_rating_result[0][i].sigma winner.save(update_fields=["rating_mu", "rating_sigma"]) i += 1 i = 0 for loser in self.losers.all(): loser.rating_mu = match_rating_result[1][i].mu loser.rating_sigma = match_rating_result[1][i].sigma loser.save(update_fields=["rating_mu", "rating_sigma"]) i += 1
def test_rating_dicts():
class Player(object):
def __init__(self, name, rating, team):
self.name = name
self.rating = rating
self.team = team
p1 = Player('Player A', Rating(), 0)
p2 = Player('Player B', Rating(), 0)
p3 = Player('Player C', Rating(), 1)
rated = rate([{p1: p1.rating, p2: p2.rating}, {p3: p3.rating}])
assert len(rated) == 2
assert isinstance(rated[0], dict)
assert isinstance(rated[1], dict)
assert len(rated[0]) == 2
assert len(rated[1]) == 1
assert p1 in rated[0]
assert p2 in rated[0]
assert p3 in rated[1]
assert p1 not in rated[1]
assert p2 not in rated[1]
assert p3 not in rated[0]
assert isinstance(rated[0][p1], Rating)
p1.rating = rated[p1.team][p1]
p2.rating = rated[p2.team][p2]
p3.rating = rated[p3.team][p3]
def rank(self, game):
logger.info(f"ranking game id={game.id}")
status = game.engine_status()
sorted_snakes = sorted(
status["snakes"].items(),
key=lambda i: game.turn + 1
if i[1]["death"] == "pending" else i[1]["turn"],
reverse=True,
)
lookup = []
for s in sorted_snakes:
gs = game.gamesnake_set.get(id=s[0])
lookup.append({
"rating":
(self.create_rating(gs.snake.snakeleaderboard_set.first()), ),
"snake":
gs.snake,
})
ratings = [i["rating"] for i in lookup]
new_rankings = trueskill.rate(ratings,
ranks=get_rankings(sorted_snakes))
for index, new_rank in enumerate(new_rankings):
t = lookup[index]
sl = t["snake"].snakeleaderboard_set.first()
sl.mu = new_rank[0].mu
sl.sigma = new_rank[0].sigma
sl.save()
LeaderboardResult.objects.create(
snake=t["snake"].snakeleaderboard_set.first(),
game=game,
mu_change=new_rank[0].mu - t["rating"][0].mu,
sigma_change=new_rank[0].sigma - t["rating"][0].sigma,
)
def applyTrueskill(games, players):
for player in players:
players[player]['rating'] = ts.Rating()
for i in games.index:
[(players[games.ix[i, 't1p1']]['rating'],
players[games.ix[i, 't1p2']]['rating'],
players[games.ix[i, 't1p3']]['rating'],
players[games.ix[i, 't1p4']]['rating'],
players[games.ix[i, 't1p5']]['rating']),
(players[games.ix[i, 't2p1']]['rating'],
players[games.ix[i, 't2p2']]['rating'],
players[games.ix[i, 't2p3']]['rating'],
players[games.ix[i, 't2p4']]['rating'],
players[games.ix[i, 't2p5']]['rating'])] = ts.rate(
[(players[games.ix[i, 't1p1']]['rating'],
players[games.ix[i, 't1p2']]['rating'],
players[games.ix[i, 't1p3']]['rating'],
players[games.ix[i, 't1p4']]['rating'],
players[games.ix[i, 't1p5']]['rating']),
(players[games.ix[i, 't2p1']]['rating'],
players[games.ix[i, 't2p2']]['rating'],
players[games.ix[i, 't2p3']]['rating'],
players[games.ix[i, 't2p4']]['rating'],
players[games.ix[i, 't2p5']]['rating'])],
[1 - games.ix[i, 'result'], games.ix[i, 'result']])
def save(self, *args, **kwargs):
winner_rating = Rating(mu=self.winner.mu, sigma=self.winner.sigma)
loser_rating = Rating(mu=self.loser.mu, sigma=self.loser.sigma)
new_winner_rating, new_loser_rating = rate_1vs1(
winner_rating, loser_rating)
self.winner.mu = new_winner_rating.mu
self.winner.sigma = new_winner_rating.sigma
self.winner.save()
self.loser.mu = new_loser_rating.mu
self.loser.sigma = new_loser_rating.sigma
self.loser.save()
# Personal rating
winners = {
p: Rating(mu=p.mu, sigma=p.sigma)
for p in self.winner.players.all()
}
losers = {
p: Rating(mu=p.mu, sigma=p.sigma)
for p in self.loser.players.all()
}
# Score the match
new_team_ratings = rate([winners, losers
]) # Returns a list with a one or many dicts
for team in new_team_ratings:
for player, new_rating in team.iteritems():
player.mu = new_rating.mu
player.sigma = new_rating.sigma
player.save()
super(Match, self).save(*args, **kwargs)
def compute(self):
games = sorted(self.games.values(),
key=lambda g: g.last_update)
for g in games:
results = sorted(g.results.values(),
key=lambda res: -res['vp'])
if len(results) < 2:
continue
teams = []
ranks = []
weights = []
rank = 0
prev = None
for res in results:
vp = res['vp']
if prev and vp < prev:
rank += 1
prev = vp
ranks.append(rank)
weights.append((1, options.faction_weight))
teams.append((res['player_ref']['rating'],
res['faction_ref']['rating']))
new = trueskill.rate(teams, ranks, weights)
i = 0
for res in results:
(res['player_ref']['rating'],
res['faction_ref']['rating']) = new[i]
i += 1
def calculate_mmr(self, r):
if not r:
return None
#get current rating
mmr_team0 = OrderedDict(
) # key = account | val = list(current_mmr, new_mmr)
mmr_team1 = OrderedDict()
for player in r.team0.memberList:
mmr_team0[r.players[player]][0] = trueskill.Rating(
self.get_mmr(r.players[player].toonHandle))
for player in r.team1.memberList:
mmr_team1[r.players[player]][0] = trueskill.Rating(
self.get_mmr(r.players[player].toonHandle))
ratings = trueskill.rate([[x for x in mmr_team0.itervalues()],
[x for x in mmr_team1.itervalues()]],
ranks=[r.team0.isLoser, r.team0.isWinner])
for player in r.team0.memberList:
mmr_team0[player][1] = ratings[player]
for player in r.team1.memberList:
mmr_team1[player][1] = ratings[player + len(r.team0.memberList) -
1]
return mmr_team0, mmr_team1
def calculate_and_adjust(players_per_side: int, team1: List['Skill'],
team2: List['Skill'], did_team_1_win: bool):
"""Calculates and adjusts a game."""
ranks = [0, 1] if did_team_1_win else [1, 0]
# Apply a weighting based on the number of players in the roster.
# This way, the game is always kept "fair" as if each player is subbed out at regular intervals.
if len(team1) < players_per_side:
team1_weights = (1, ) * len(team1)
else:
team1_weights = (players_per_side / len(team1), ) * len(team1)
if len(team2) < players_per_side:
team2_weights = (1, ) * len(team2)
else:
team2_weights = (players_per_side / len(team2), ) * len(team2)
teams = trueskill.rate(rating_groups=[
tuple([t1.rating for t1 in team1]),
tuple([t2.rating for t2 in team2])
],
ranks=ranks,
weights=[team1_weights, team2_weights])
for i in range(0, len(teams[0])):
team1[i].rating = teams[0][i]
for i in range(0, len(teams[1])):
team2[i].rating = teams[1][i]
def do_game(game, players, style="allplayer-trueskill"):
# Takes a game and stores the results
game_rank_list = []
player_list = []
rating_groups = []
rankable_users = []
if style == "allplayer-trueskill":
rankable_users = game.users
elif style == "topbottom-trueskill":
rankable_users = [game.users[0], game.users[-1]]
for user_data in rankable_users:
if user_data.user_name not in players:
players[user_data.user_name] = Player(user_data.user_name)
rating_groups.append(
{user_data.user_name: players[user_data.user_name].rating})
game_rank_list.append(user_data.rank)
player_list.append(user_data.user_name)
rated_list = rate(rating_groups, game_rank_list)
for i in range(len(rankable_users)):
if rankable_users[i].user_name not in players:
players[rankable_users[i].user_name] = Player(
rankable_users.user_name)
players[rankable_users[i].user_name].record_match(
game.timestamp, rated_list[i][rankable_users[i].user_name])
def update_ranking(self, match_ranking: Dict[str, int]):
# Transform the usernames to be lowercase for compatibility with database
match_ranking = {
key.lower(): value
for key, value in match_ranking.items()
}
# Get the current trueskill ratings for each player
entries = self.get_multi(*match_ranking.keys())
old_trueskill_rankings = [{
str(name): Rating(mu=mu, sigma=sigma)
} for name, _, mu, sigma in entries]
ordered_match_rankings = [
match_ranking[name] for name, _, _, _ in entries
]
# Update rankings using trueskill algorithm
new_trueskill_rankings = rate(old_trueskill_rankings,
ordered_match_rankings)
# Update database with new rankings
cursor = self.__db.cursor()
with self.__db_lock:
for name, rating in ChainMap(*new_trueskill_rankings).items():
cursor.execute(
"UPDATE userz SET mu=?, sigma=? WHERE username=?",
(rating.mu, rating.sigma, name))
self.__db.commit()
def update_ratings(game, session, elos, players):
if len(elos) < 2:
return []
oldRatings = []
ranks = []
for pid in players:
p = elos[pid]
#fixme
if len(oldRatings) < 8:
oldRatings.append((Rating(mu=p.mu, sigma=p.sigma), ))
ranks.append(players[pid].rank)
newRatings = rate(oldRatings, ranks)
elo_deltas = {}
i = 0
for pid in players:
if i >= 8: continue
old = oldRatings[i][0]
new = newRatings[i][0]
elo_deltas[pid] = (new.mu - 3 * new.sigma) - (old.mu - 3 * old.sigma)
elos[pid].mu = new.mu
elos[pid].sigma = new.sigma
elos[pid].ts_games += 1
i = i + 1
log.debug(
str(pid) + ": mu=" + str(new.mu) + ", sigma=" + str(new.sigma))
save_rating_deltas(game, session, elo_deltas)
return elos
def test_partial_play():
t1, t2 = (Rating(), ), (Rating(), Rating())
# each results from C# Skills:
assert rate([t1, t2], weights=[(1, ), (1, 1)]) == rate([t1, t2])
assert _rate([t1, t2], weights=[(1,), (1, 1)]) == \
[(33.730, 7.317), (16.270, 7.317), (16.270, 7.317)]
assert _rate([t1, t2], weights=[(0.5,), (0.5, 0.5)]) == \
[(33.939, 7.312), (16.061, 7.312), (16.061, 7.312)]
assert _rate([t1, t2], weights=[(1,), (0, 1)]) == \
[(29.440, 7.166), (25.000, 8.333), (20.560, 7.166)]
assert _rate([t1, t2], weights=[(1,), (0.5, 1)]) == \
[(32.417, 7.056), (21.291, 8.033), (17.583, 7.056)]
# match quality of partial play
t1, t2, t3 = (Rating(), ), (Rating(), Rating()), (Rating(), )
assert _quality([t1, t2, t3], [(1, ), (0.25, 0.75), (1, )]) == 0.2
assert _quality([t1, t2, t3], [(1, ), (0.8, 0.9), (1, )]) == 0.0809
def rank(self, force=False):
if self.ranked and not force:
return
if self.players.all().count() != self.game.player_count:
return
self.refresh_from_db()
arg = []
for player in self.players.all():
arg.append((player.get_rating_for_game(self.game).rating_obj, ))
results = rate(arg)
for i, player in enumerate(self.players.all()):
rating = player.get_rating_for_game(self.game)
rating.rating_obj = results[i]
rating.match_count += 1
rating.save()
if self.game is not None:
rating = player.get_rating_for_game(None)
rating.rating_obj = results[i]
rating.save()
self.ranked = True
self.save()
def update_trueskill_by_match(match):
w_ratings = []
l_ratings = []
for p in match.winning_players:
mu, sigma = p.get_current_trueskill()
w_ratings.append(ts.Rating(mu, sigma))
for p in match.losing_players:
mu, sigma = p.get_current_trueskill()
l_ratings.append(ts.Rating(mu, sigma))
rating_groups = [w_ratings, l_ratings]
new_ratings = ts.rate(rating_groups, ranks=[0, 1])
players = match.winning_players + match.losing_players
new_ratings_flat = [item for sublist in new_ratings for item in sublist]
for player, rating in zip(players, new_ratings_flat):
r_m = Rating(
user=player,
match=match,
rating_type='trueskill_mu',
rating_value=rating.mu,
timestamp=match.timestamp,
)
r_s = Rating(
user=player,
match=match,
rating_type='trueskill_sigma',
rating_value=rating.sigma,
timestamp=match.timestamp,
)
db.session.add_all([r_m, r_s])
db.session.commit()
def update_trueskill(scores, ratings):
env = TrueSkill()
# Parallel arrays! All of these are for the given game
players = []
teams = []
ranks = []
expose_before = {}
# Sanity check, some bad data in test systems
if len(scores) < 4:
return
for s in scores:
if s.player_id not in ratings.keys():
ratings[s.player_id] = Rating() # Default mu=25, sigma=8.333
r = ratings[s.player_id]
expose_before[s.player_id] = env.expose(r)
players.append(s.player_id)
teams.append([r])
ranks.append(s.rank)
# Crunch the numbers
new_ratings = rate(teams, ranks)
for i in range(0, len(new_ratings)):
ratings[players[i]] = new_ratings[i][0]
for s in scores:
s.trueskill = ratings[s.player_id].mu
s.trueskill_confidence = ratings[s.player_id].sigma
s.trueskill_change = round(env.expose(ratings[s.player_id]) - expose_before[s.player_id], 1)
s.save()
def main(games_file: str, ratings_file: str):
# Load data.
players = defaultdict(lambda: ts.Rating())
games = pd.read_csv(games_file)
# Sort data based on date.
games.sort_values(by=[DATE_COLUMN], inplace=True)
games.fillna("", inplace=True)
for _, (date, pl1, pl2, sc1, sc2, pl3, pl4) in games.iterrows():
team1 = []
skills1 = []
team2 = []
skills2 = []
team1, skills1 = append(pl1, players, team1, skills1)
team1, skills1 = append(pl2, players, team1, skills1)
team2, skills2 = append(pl3, players, team2, skills2)
team2, skills2 = append(pl4, players, team2, skills2)
ranks = compute_rank(sc1, sc2)
ratings1, ratings2 = ts.rate([skills1, skills2], ranks=ranks)
update(players, team1, ratings1)
update(players, team2, ratings2)
# Save ratings.
result = []
for name, rating in players.items():
result.append({"Name": name, "Mu": rating.mu, "Sigma": rating.sigma})
df = pd.DataFrame(result)
df.to_csv(ratings_file, index=False)
def update_player_ratings(self, match):
ratings_a = [p.get_rating() for p in match.teams[0]]
ratings_b = [p.get_rating() for p in match.teams[1]]
# Sort by score and get rank indices
rank = list(zip(match.score, range(len(match.score))))
rank.sort(key=lambda r: r[0], reverse=True)
rank_indices = list(zip(*rank))[1]
# Check for Draw
# TODO: make this generic for more than 2 teams
if match.score[0] == match.score[1]:
rank_indices = [0, 0]
# Calculate new Ratings using trueskill algorithm
new_ratings = trueskill.rate([ratings_a, ratings_b],
ranks=rank_indices,
weights=self.team_weights(
ratings_a, ratings_b))
for r, p in zip(new_ratings[0], match.teams[0]):
p.set_rating(r)
p.add_match(match)
for r, p in zip(new_ratings[1], match.teams[1]):
p.set_rating(r)
p.add_match(match)
def test_partial_play():
t1, t2 = (Rating(),), (Rating(), Rating())
# each results from C# Skills:
assert rate([t1, t2], weights=[(1,), (1, 1)]) == rate([t1, t2])
assert _rate([t1, t2], weights=[(1,), (1, 1)]) == \
[(33.730, 7.317), (16.270, 7.317), (16.270, 7.317)]
assert _rate([t1, t2], weights=[(0.5,), (0.5, 0.5)]) == \
[(33.939, 7.312), (16.061, 7.312), (16.061, 7.312)]
assert _rate([t1, t2], weights=[(1,), (0, 1)]) == \
[(29.440, 7.166), (25.000, 8.333), (20.560, 7.166)]
assert _rate([t1, t2], weights=[(1,), (0.5, 1)]) == \
[(32.417, 7.056), (21.291, 8.033), (17.583, 7.056)]
# match quality of partial play
t1, t2, t3 = (Rating(),), (Rating(), Rating()), (Rating(),)
assert _quality([t1, t2, t3], [(1,), (0.25, 0.75), (1,)]) == 0.2
assert _quality([t1, t2, t3], [(1,), (0.8, 0.9), (1,)]) == 0.0809
def update_ratings(game, session, elos, players):
if len(elos) < 2:
return []
oldRatings = []
ranks = []
for pid in players:
p = elos[pid]
#fixme
if len(oldRatings) < 8:
oldRatings.append((Rating(mu=p.mu, sigma=p.sigma),))
ranks.append(players[pid].rank)
newRatings = rate(oldRatings, ranks);
elo_deltas = {}
i=0
for pid in players:
if i>=8: continue
old = oldRatings[i][0]
new = newRatings[i][0]
elo_deltas[pid] = (new.mu - 3*new.sigma) - (old.mu - 3*old.sigma)
elos[pid].mu = new.mu
elos[pid].sigma = new.sigma
elos[pid].ts_games += 1
i = i + 1
log.debug(str(pid) + ": mu=" + str(new.mu) + ", sigma=" + str(new.sigma));
save_rating_deltas(game, session, elo_deltas)
return elos
def test_rating_dicts():
class Player(object):
def __init__(self, name, rating, team):
self.name = name
self.rating = rating
self.team = team
p1 = Player('Player A', Rating(), 0)
p2 = Player('Player B', Rating(), 0)
p3 = Player('Player C', Rating(), 1)
rated = rate([{p1: p1.rating, p2: p2.rating}, {p3: p3.rating}])
assert len(rated) == 2
assert isinstance(rated[0], dict)
assert isinstance(rated[1], dict)
assert len(rated[0]) == 2
assert len(rated[1]) == 1
assert p1 in rated[0]
assert p2 in rated[0]
assert p3 in rated[1]
assert p1 not in rated[1]
assert p2 not in rated[1]
assert p3 not in rated[0]
assert isinstance(rated[0][p1], Rating)
p1.rating = rated[p1.team][p1]
p2.rating = rated[p2.team][p2]
p3.rating = rated[p3.team][p3]
def add_match(conn, bots, results):
winner = None
for id_str, stats in results['stats'].items():
if stats['rank'] == 1:
winner = int(id_str)
if winner is None:
raise ValueError('Could not detect winner of game')
query = 'insert into games (datetime, winner, participants, results) values (?, ?, ?, ?)'
del results['final_snapshot']
current_time = datetime.datetime.now().isoformat()
conn.execute(query, (current_time, bots[winner]['id'], json.dumps(bots),
json.dumps(results)))
for bot in bots:
history_query = 'insert into rank_history (bot_id, datetime, rank, mu, sigma) values (?, ?, ?, ?, ?)'
conn.execute(
history_query,
(bot['id'], current_time, bot['rank'], bot['mu'], bot['sigma']))
games_played_query = 'update bots set games_played=games_played + 1 where id = ?'
conn.execute(games_played_query, (bot['id'], ))
trueskill.setup(tau=0.008, draw_probability=0.001)
teams = [[trueskill.Rating(mu=bot["mu"], sigma=bot["sigma"])]
for bot in bots]
ranks = [results["stats"][str(b)]["rank"] - 1 for b in range(len(bots))]
new_ratings = trueskill.rate(teams, ranks)
update_query = 'update bots set mu=?, sigma=? where id=?'
for bot, rating in zip(bots, new_ratings):
conn.execute(update_query, (rating[0].mu, rating[0].sigma, bot['id']))
rerank_bots(conn)
def update_ratings(players: dict, game: Game) -> None:
if not game.score:
return
if game.score == '1':
ranks = [0, 1]
elif game.score == '2':
ranks = [1, 0]
elif game.score == 'D':
ranks = [0, 0]
else:
return
for player_id in game.team1:
if not player_id in players:
players[player_id] = Player()
for player_id in game.team2:
if not player_id in players:
players[player_id] = Player()
team1_ratings = list(map(lambda id: players[id].rating, game.team1))
team2_ratings = list(map(lambda id: players[id].rating, game.team2))
team1_ratings, team2_ratings = trueskill.rate(
[team1_ratings, team2_ratings], ranks=ranks)
for i, player in enumerate(game.team1):
players[player].rating = team1_ratings[i]
for i, player in enumerate(game.team2):
players[player].rating = team2_ratings[i]
def test_microsoft_research_example():
# http://research.microsoft.com/en-us/projects/trueskill/details.aspx
alice, bob, chris, darren, eve, fabien, george, hillary = \
Rating(), Rating(), Rating(), Rating(), \
Rating(), Rating(), Rating(), Rating()
_rated = rate([{
'alice': alice
}, {
'bob': bob
}, {
'chris': chris
}, {
'darren': darren
}, {
'eve': eve
}, {
'fabien': fabien
}, {
'george': george
}, {
'hillary': hillary
}])
rated = {}
list(map(rated.update, _rated))
assert almost(rated['alice']) == (36.771, 5.749)
assert almost(rated['bob']) == (32.242, 5.133)
assert almost(rated['chris']) == (29.074, 4.943)
assert almost(rated['darren']) == (26.322, 4.874)
assert almost(rated['eve']) == (23.678, 4.874)
assert almost(rated['fabien']) == (20.926, 4.943)
assert almost(rated['george']) == (17.758, 5.133)
assert almost(rated['hillary']) == (13.229, 5.749)
def _updateRankings(winningTeam,losingTeam):
"""
Updates the Rankings of the PongUsers who played the Game.
Keyword arguments:
winningTeam -- the Team who won the Game
losingTeam -- the Team who lost the Game
Contributors: Richard Douglas
Output: None
"""
#obtain the Ranking objects
winningRankings = _obtainRankings(winningTeam)
losingRankings = _obtainRankings(losingTeam)
#obtain the corresponding TrueSkill Rating objects
oldWinningRatings = _obtainRatings(winningRankings)
oldLosingRatings = _obtainRatings(losingRankings)
#have TrueSkill rate the Game
newWinningRatings, newLosingRatings = rate([oldWinningRatings,oldLosingRatings], ranks = [0,1])
#update Ranking objects with their new Mu and Sigma values
_writeRatingsToRankings(newWinningRatings,winningRankings)
_writeRatingsToRankings(newLosingRatings,losingRankings)
return
def test_issue4():
"""The `issue #4`_, opened by @sublee.
numpy.float64 handles floating-point error by different way. For example,
it can just warn RuntimeWarning on n/0 problem instead of throwing
ZeroDivisionError.
.. _issue #4: https://github.com/sublee/trueskill/issues/4
"""
import numpy
r1, r2 = Rating(105.247, 0.439), Rating(27.030, 0.901)
# make numpy to raise FloatingPointError instead of warning
# RuntimeWarning
old_settings = numpy.seterr(divide='raise')
try:
rate([(r1,), (r2,)])
finally:
numpy.seterr(**old_settings)
def update_trueskills(chao_trueskills):
"""
makes updates to the trueskills based on the order
:param chao_trueskills: list of chao trueskills in the order in which they placed
:return: new list of trueskills for chaos in the same order in which they placed (were received)
"""
rating_groups = [(x,) for x in chao_trueskills]
rated = trueskill.rate(rating_groups)
return [rated[i][0] for i in xrange(len(rated))]
def test_rating_tuples():
r1, r2, r3 = Rating(), Rating(), Rating()
rated = rate([(r1, r2), (r3,)])
assert len(rated) == 2
assert isinstance(rated[0], tuple)
assert isinstance(rated[1], tuple)
assert len(rated[0]) == 2
assert len(rated[1]) == 1
assert isinstance(rated[0][0], Rating)
def test_setup_global_environment():
try:
setup(draw_probability=.50)
t1, t2 = generate_teams([1, 1])
rated = rate([t1, t2])
assert almost(rated) == [(30.267, 7.077), (19.733, 7.077)]
finally:
# rollback
setup()
def loadMatches(self, matches):
for match in matches:
rating_group = [dict(zip(match.radiant, [self.players[p] for p in match.radiant])),
dict(zip(match.dire, [self.players[p] for p in match.dire])),
]
result = rate(rating_group, ranks = match.result)
for side in result:
for p in side.keys():
self.players[p] = side[p]
def test_deprecated_individual_rating_groups():
r1, r2, r3 = Rating(50, 1), Rating(10, 5), Rating(15, 5)
with raises(TypeError):
deprecated_call(rate, [r1, r2, r3])
with raises(TypeError):
deprecated_call(quality, [r1, r2, r3])
assert t.transform_ratings([r1, r2, r3]) == rate([(r1,), (r2,), (r3,)])
assert t.match_quality([r1, r2, r3]) == quality([(r1,), (r2,), (r3,)])
deprecated_call(t.transform_ratings, [r1, r2, r3])
deprecated_call(t.match_quality, [r1, r2, r3])
def test_partial_play_with_weights_dict():
t1, t2 = (Rating(),), (Rating(), Rating())
assert rate([t1, t2], weights={(0, 0): 0.5, (1, 0): 0.5, (1, 1): 0.5}) == \
rate([t1, t2], weights=[[0.5], [0.5, 0.5]])
assert rate([t1, t2], weights={(1, 0): 0}) == \
rate([t1, t2], weights=[[1], [0, 1]])
assert rate([t1, t2], weights={(1, 0): 0.5}) == \
rate([t1, t2], weights=[[1], [0.5, 1]])
def process_match(self, line):
players = list(map(str, line[:4]))
score = list(map(int, line[4:]))
locker_room = self.locker_room
for player in players:
if player not in locker_room:
locker_room[player] = Rating()
t1 = [locker_room.pop(players[i]) for i in range(2)]
t2 = [locker_room.pop(players[i]) for i in range(2, 4)]
ranks = [score[1] > score[0], score[1] < score[0]]
t1, t2 = rate([t1, t2], ranks=ranks)
for i in range(2):
locker_room[players[i]] = t1[i]
locker_room[players[i + 2]] = t2[i]
def test_issue3():
"""The `issue #3`_, opened by @youknowone.
These inputs led to ZeroDivisionError before 0.1.4. Also another TrueSkill
implementations cannot calculate this case.
.. _issue #3: https://github.com/sublee/trueskill/issues/3
"""
# @konikos's case 1
t1 = (Rating(42.234, 3.728), Rating(43.290, 3.842))
t2 = (Rating(16.667, 0.500), Rating(16.667, 0.500), Rating(16.667, 0.500),
Rating(16.667, 0.500), Rating(16.667, 0.500), Rating(16.667, 0.500),
Rating(16.667, 0.500), Rating(16.667, 0.500), Rating(16.667, 0.500),
Rating(16.667, 0.500), Rating(16.667, 0.500), Rating(16.667, 0.500),
Rating(16.667, 0.500), Rating(16.667, 0.500), Rating(16.667, 0.500))
rate([t1, t2], [6, 5])
# @konikos's case 2
t1 = (Rating(25.000, 0.500), Rating(25.000, 0.500), Rating(25.000, 0.500),
Rating(25.000, 0.500), Rating(33.333, 0.500), Rating(33.333, 0.500),
Rating(33.333, 0.500), Rating(33.333, 0.500), Rating(41.667, 0.500),
Rating(41.667, 0.500), Rating(41.667, 0.500), Rating(41.667, 0.500))
t2 = (Rating(42.234, 3.728), Rating(43.291, 3.842))
rate([t1, t2], [0, 28])
def rate_players():
(ranked, teams) = build_ranked()
ranked = trueskill.rate(ranked)
# JSONify
result = []
for t, team in enumerate(ranked):
rated_team = []
for i, player in enumerate(team):
rated_team.append(jsonify_rating(player, teams[t][i]))
result.append(rated_team)
return {'teams': result}
def record_match_and_update_ratings(win_team, lose_team, loser_win_count):
# calculate new ratings
updated_ratings = rate([win_team.ratings, lose_team.ratings])
updated_ratings_dict = {}
updated_ratings_dict.update(updated_ratings[0])
updated_ratings_dict.update(updated_ratings[1])
for role, rating in updated_ratings_dict.iteritems():
role.rating_mu = rating.mu
role.rating_sigma = rating.sigma
role.save()
result = MatchResult.objects.create(
winners=win_team,
losers=lose_team,
loser_win_count=loser_win_count,
created_on=datetime.datetime.now())
def update_trueskill(match):
winner = match.winner
if match.team_1 == winner:
loser = match.team_2
else:
loser = match.team_1
winners = winner.players.all()
losers = loser.players.all()
winner_ratings = []
loser_ratings = []
for w in winners:
winner_ratings.append(Rating(w.current_mu, w.current_sigma))
for l in losers:
loser_ratings.append(Rating(l.current_mu, l.current_sigma))
winner_ratings, loser_ratings = rate([winner_ratings, loser_ratings])
for counter, p in enumerate(winners):
p.ts_mu = winner_ratings[counter].mu
p.ts_sigma = winner_ratings[counter].sigma
p.save()
sh, _ = StatHistory.objects.get_or_create(player=p,
match=match,
)
sh.season = match.season
sh.ts_mu = winner_ratings[counter].mu
sh.ts_sigma = winner_ratings[counter].sigma
sh.save()
# p.save()
for counter, p in enumerate(losers):
p.ts_mu = loser_ratings[counter].mu
p.ts_sigma = loser_ratings[counter].sigma
p.save()
sh, _ = StatHistory.objects.get_or_create(player=p,
match=match,
)
sh.season = match.season
sh.ts_mu = loser_ratings[counter].mu
sh.ts_sigma = loser_ratings[counter].sigma
sh.save()
def test_issue9_weights_dict_with_object_keys():
"""The `issue #9`_, opened by @.
.. _issue #9: https://github.com/sublee/trueskill/issues/9
"""
class Player(object):
def __init__(self, rating, team):
self.rating = rating
self.team = team
p1 = Player(Rating(), 0)
p2 = Player(Rating(), 0)
p3 = Player(Rating(), 1)
teams = [{p1: p1.rating, p2: p2.rating}, {p3: p3.rating}]
rated = rate(teams, weights={(0, p1): 1, (0, p2): 0.5, (1, p3): 1})
assert rated[0][p1].mu > rated[0][p2].mu
assert rated[0][p1].sigma < rated[0][p2].sigma
assert rated[0][p1].sigma == rated[1][p3].sigma
def test_microsoft_research_example():
# http://research.microsoft.com/en-us/projects/trueskill/details.aspx
alice, bob, chris, darren, eve, fabien, george, hillary = \
Rating(), Rating(), Rating(), Rating(), \
Rating(), Rating(), Rating(), Rating()
_rated = rate([{'alice': alice}, {'bob': bob}, {'chris': chris},
{'darren': darren}, {'eve': eve}, {'fabien': fabien},
{'george': george}, {'hillary': hillary}])
rated = {}
list(map(rated.update, _rated))
assert almost(rated['alice']) == (36.771, 5.749)
assert almost(rated['bob']) == (32.242, 5.133)
assert almost(rated['chris']) == (29.074, 4.943)
assert almost(rated['darren']) == (26.322, 4.874)
assert almost(rated['eve']) == (23.678, 4.874)
assert almost(rated['fabien']) == (20.926, 4.943)
assert almost(rated['george']) == (17.758, 5.133)
assert almost(rated['hillary']) == (13.229, 5.749)
def compute_rating(self, rating='global'):
"""
Compute new ratings
:param rating: 'global' or 'ladder'
:return: rating groups of the form:
>>> p1,p2,p3,p4 = Player()
>>> [{p1: p1.rating, p2: p2.rating}, {p3: p3.rating, p4: p4.rating}]
"""
assert self.state == GameState.LIVE or self.state == GameState.ENDED
team_scores = {}
ffa_scores = []
for player in sorted(self.players,
key=lambda p: self.get_player_option(p.id, 'Army') or -1):
team = self.get_player_option(player.id, 'Team')
army = self.get_player_option(player.id, 'Army')
if army < 0:
self._logger.info("Skipping {}".format(player))
continue
if not team:
raise GameError("Missing team for player id: {}".format(player.id))
if team != 1:
if team not in team_scores:
team_scores[team] = 0
try:
team_scores[team] += self.get_army_result(army)
except KeyError:
team_scores[team] += 0
self._logger.info("Missing game result for {army}: {player}".format(army=army,
player=player))
elif team == 1:
ffa_scores.append((player, self.get_army_result(army)))
ranks = [-score for team, score in sorted(team_scores.items(), key=lambda t: t[0])]
rating_groups = []
for team in sorted(self.teams):
if team != 1:
rating_groups += [{player: Rating(*getattr(player, '{}_rating'.format(rating)))
for player in self.players if
self.get_player_option(player.id, 'Team') == team}]
for player, score in sorted(ffa_scores, key=lambda x: self.get_player_option(x[0].id, 'Army')):
rating_groups += [{player: Rating(*getattr(player, '{}_rating'.format(rating)))}]
ranks.append(-score)
self._logger.debug("Rating groups: {}".format(rating_groups))
self._logger.debug("Ranks: {}".format(ranks))
return trueskill.rate(rating_groups, ranks)
def rate(cls, names):
"""
:type names: list[str]
"""
if not isinstance(names, list):
raise TypeError("Argument must be a list")
if len(names) != 4:
raise ValueError("Please specify 4 players")
players = []
missing = []
for name in names:
player = cls.get_player(name)
if not player:
missing.append(name)
else:
players.append(player)
if missing:
raise RuntimeError("Players not registered: %s" % missing)
winner1 = players[0]
winner2 = players[1]
loser1 = players[2]
loser2 = players[3]
winners = [winner1.rating, winner2.rating]
losers = [loser1.rating, loser2.rating]
winners, losers = trueskill.rate([winners, losers])
winner1.rating = winners[0]
winner2.rating = winners[1]
loser1.rating = losers[0]
loser2.rating = losers[1]
Store.get_store().set_player(winner1)
Store.get_store().set_player(winner2)
Store.get_store().set_player(loser1)
Store.get_store().set_player(loser2)
Store.get_store().log_results(names)
def calculate_mmr(self, r):
if not r:
return None
#get current rating
mmr_team0 = OrderedDict() # key = account | val = list(current_mmr, new_mmr)
mmr_team1 = OrderedDict()
for player in r.team0.memberList:
mmr_team0[r.players[player]][0] = trueskill.Rating(self.get_mmr(r.players[player].toonHandle))
for player in r.team1.memberList:
mmr_team1[r.players[player]][0] = trueskill.Rating(self.get_mmr(r.players[player].toonHandle))
ratings = trueskill.rate([[x for x in mmr_team0.itervalues()], [x for x in mmr_team1.itervalues()]], ranks=[r.team0.isLoser, r.team0.isWinner])
for player in r.team0.memberList:
mmr_team0[player][1] = ratings[player]
for player in r.team1.memberList:
mmr_team1[player][1] = ratings[player + len(r.team0.memberList) - 1]
return mmr_team0, mmr_team1
def rate_skill(names, results, metrics):
from trueskill import Rating, rate, setup
MU = 1000
setup(MU, MU / 3, MU * 5, MU / 5000)
started = time.clock()
ratings = {x : Rating() for x in names}
for entry in results:
adjusted = rate([(ratings[x[0]],) for x in entry],
[(int(not x[1]),) for x in entry])
for index, rating in enumerate(adjusted):
ratings[entry[index][0]] = rating[0]
print("Completed rankings in", str(int(time.clock() - started)), "seconds")
print("")
descending = sorted(ratings.items(), key=lambda x:x[1], reverse=True)
for index, (name, rating) in enumerate(descending):
metrics[name]["Rank"] = index
metrics[name]["Mu"] = "%.0f" % rating.mu
metrics[name]["Sigma"] = "%.0f" % rating.sigma
def test_1_vs_n():
t1, = generate_teams([1])
# 1 vs 2
t2, = generate_teams([2])
assert _quality([t1, t2]) == 0.135
assert _rate([t1, t2]) == \
[(33.730, 7.317), (16.270, 7.317), (16.270, 7.317)]
assert _rate([t1, t2], [0, 0]) == \
[(31.660, 7.138), (18.340, 7.138), (18.340, 7.138)]
# 1 vs 3
t2, = generate_teams([3])
assert _quality([t1, t2]) == 0.012
assert _rate([t1, t2]) == \
[(36.337, 7.527), (13.663, 7.527), (13.663, 7.527), (13.663, 7.527)]
assert almost(rate([t1, t2], [0, 0]), 2) == \
[(34.990, 7.455), (15.010, 7.455), (15.010, 7.455), (15.010, 7.455)]
# 1 vs 7
t2, = generate_teams([7])
assert _quality([t1, t2]) == 0
assert _rate([t1, t2]) == \
[(40.582, 7.917), (9.418, 7.917), (9.418, 7.917), (9.418, 7.917),
(9.418, 7.917), (9.418, 7.917), (9.418, 7.917), (9.418, 7.917)]
