Flag for half handicap rank adjustments for hc1

For testing as per #7

analysis/analyze_glicko2_weekly_window_no_unxepected_changes.py

@@ -42,7 +42,7 @@ def process_game(self, game: GameRecord) -> Glicko2Analytics:
         ## since we do not update deviation in periods without games, we have to do update it now if there are empty periods size the base rating was calclulated
         black_base_time = self._storage.get_first_timestamp_older_than(game.black_id, window)
         white_base_time = self._storage.get_first_timestamp_older_than(game.white_id, window)
-        
+
         if black_base_time is not None:
             black_base.expand_deviation_because_no_games_played(int((game.ended - black_base_time) / no_games_window_witdh))
         if white_base_time is not None:
@@ -118,7 +118,7 @@ def process_game(self, game: GameRecord) -> Glicko2Analytics:
 
 
 # Run
-config(cli.parse_args(), name="glicko2-glickman-1-week-window")
+config(cli.parse_args(), name="glicko2-week-window-no-unexpected-changes")
 ogs_game_data = GameData()
 storage = InMemoryStorage(Glicko2Entry)
 engine = DailyWindows(storage)

analysis/analyze_glicko2_weekly_window_reduce_rating_movement.py

@@ -44,7 +44,7 @@ def process_game(self, game: GameRecord) -> Glicko2Analytics:
         ## since we do not update deviation in periods without games, we have to do update it now if there are empty periods size the base rating was calclulated
         black_base_time = self._storage.get_first_timestamp_older_than(game.black_id, window)
         white_base_time = self._storage.get_first_timestamp_older_than(game.white_id, window)
-        
+
         if black_base_time is not None:
             black_base.expand_deviation_because_no_games_played(int((game.ended - black_base_time) / no_games_window_witdh))
         if white_base_time is not None:
@@ -85,7 +85,7 @@ def process_game(self, game: GameRecord) -> Glicko2Analytics:
         )
 
         ## limit rating changes by base RD * num games
-        # glicko2 is desinged to update ratings based on full rating periods. There is a natural lower bound of the RD 
+        # glicko2 is desinged to update ratings based on full rating periods. There is a natural lower bound of the RD
         # depending on the number of games in the period. If there are fewer games in a period the RD is higher which
         # results in bigger changes per game.
         # We calculate imemdiate ratings each time a game ends. So after a new rating period started the game pool is
@@ -134,7 +134,7 @@ def process_game(self, game: GameRecord) -> Glicko2Analytics:
 
 
 # Run
-config(cli.parse_args(), name="glicko2-glickman-1-week-window")
+config(cli.parse_args(), name="glicko2-week-window-reduce-rating-movement")
 ogs_game_data = GameData()
 storage = InMemoryStorage(Glicko2Entry)
 engine = DailyWindows(storage)

analysis/util/RatingMath.py

@@ -23,10 +23,17 @@
     help="Use logarithmic, linear, or GoR ranking",
 )
 
-A = 850
-C = 32.25
+#A = 850
+#C = 32.25
+A = 478
+C = 12.9
 D = 0
 P = 1
+HALF_STONE_HANDICAP = False
+
+cli.add_argument(
+    "--half-stone-handicap", dest="half_stone_handicap", const=1, default=False, action="store_const", help="Use a 0.5 rank adjustment for hc1",
+)
 
 logarithmic = cli.add_argument_group(
     "logarithmic ranking variables", "rating to ranks converted with `(log(rating / a) ** p) * c + d`",
@@ -65,10 +72,10 @@ def set_exhaustive_log_parameters(a: float, c:float, d:float, p:float = 1.0) ->
     P = p
 
 def get_handicap_adjustment(rating: float, handicap: int) -> float:
-    #return rank_to_rating(rating_to_rank(rating) + handicap) - rating
-
-    #return rank_to_rating(rating_to_rank(rating) + (handicap - 0.5 if handicap > 0 else 0)) - rating
-    return rank_to_rating(rating_to_rank(rating) + (0.5 if handicap == 1 else handicap)) - rating
+    global HALF_STONE_HANDICAP
+    if HALF_STONE_HANDICAP:
+        return rank_to_rating(rating_to_rank(rating) + (0.5 if handicap == 1 else handicap)) - rating
+    return rank_to_rating(rating_to_rank(rating) + handicap) - rating
 
 def set_optimizer_rating_points(points: List[float]) -> None:
     global optimizer_rating_control_points
@@ -81,7 +88,9 @@ def configure_rating_to_rank(args: argparse.Namespace) -> None:
     global A
     global C
     global D
+    global HALF_STONE_HANDICAP
 
+    HALF_STONE_HANDICAP = args.half_stone_handicap
     system: str = args.ranks
     a: float = args.a
     c: float = args.c
@@ -95,6 +104,7 @@ def configure_rating_to_rank(args: argparse.Namespace) -> None:
 
     rating_config["system"] = system
 
+
     if system == "linear":
 
         def __rank_to_rating(rank: float) -> float: