add perf_ceiling in rating computation

Author: xiaowuc1

judge/ratings.py

@@ -1,5 +1,5 @@
 from bisect import bisect
-from math import pi, sqrt, tanh
+from math import inf, pi, sqrt, tanh
 from operator import attrgetter, itemgetter
 
 from django.db import transaction
@@ -19,6 +19,7 @@
 VAR_LIM = (sqrt(VAR_PER_CONTEST**2 + 4 * BETA2 * VAR_PER_CONTEST) - VAR_PER_CONTEST) / 2
 SD_LIM = sqrt(VAR_LIM)
 TANH_C = sqrt(3) / pi
+PERF_CEILING_INCREMENT = 400
 
 
 def tie_ranker(iterable, key=attrgetter('points')):
@@ -77,7 +78,7 @@ def get_var(times_ranked, cache=[VAR_INIT]):
     return cache[times_ranked]
 
 
-def recalculate_ratings(ranking, old_mean, times_ranked, historical_p):
+def recalculate_ratings(ranking, old_mean, times_ranked, historical_p, perf_ceiling):
     n = len(ranking)
     new_p = [0.] * n
     new_mean = [0.] * n
@@ -96,7 +97,7 @@ def solve_idx(i, bounds=VALID_RANGE):
             elif s < r:     # s beats r
                 y_tg -= 1. / d
             # Otherwise, this is a tie that counts as half a win, as per Elo-MMR.
-        new_p[i] = solve(p_tanh_terms, y_tg, bounds=bounds)
+        new_p[i] = min(perf_ceiling, solve(p_tanh_terms, y_tg, bounds=bounds))
 
     # Fill all indices between i and j, inclusive. Use the fact that new_p is non-increasing.
     def divconq(i, j):
@@ -160,6 +161,9 @@ def rate_contest(contest):
         users = users.exclude(last_rating__lt=contest.rating_floor)
     if contest.rating_ceiling is not None:
         users = users.exclude(last_rating__gt=contest.rating_ceiling)
+        perf_ceiling = contest.rating_ceiling + PERF_CEILING_INCREMENT
+    else:
+        perf_ceiling = inf
 
     users = list(users)
     participation_ids = list(map(itemgetter('id'), users))
@@ -176,7 +180,7 @@ def rate_contest(contest):
         idx = user_id_to_idx[h['user_id']]
         historical_p[idx].append(h['performance'])
 
-    rating, mean, performance = recalculate_ratings(ranking, old_mean, times_ranked, historical_p)
+    rating, mean, performance = recalculate_ratings(ranking, old_mean, times_ranked, historical_p, perf_ceiling)
 
     now = timezone.now()
     ratings = [Rating(user_id=i, contest=contest, rating=r, mean=m, performance=perf,