Differential D2630 Diff 15807 source/tools/lobbybots/EcheLOn/ELO.py

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source/tools/lobbybots/EcheLOn/ELO.py

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	"""Copyright (C) 2014 Wildfire Games.
	* This file is part of 0 A.D.
	*
	* 0 A.D. is free software: you can redistribute it and/or modify
	* it under the terms of the GNU General Public License as published by
	* the Free Software Foundation, either version 2 of the License, or
	* (at your option) any later version.
	*
	* 0 A.D. is distributed in the hope that it will be useful,
	* but WITHOUT ANY WARRANTY; without even the implied warranty of
	* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
	* GNU General Public License for more details.
	*
	* You should have received a copy of the GNU General Public License
	* along with 0 A.D. If not, see <http://www.gnu.org/licenses/>.
	"""

	############ Constants ############
	# Difference between two ratings such that it is
	# regarded as a "sure win" for the higher player.
	# No points are gained or lost for such a game.
	elo_sure_win_difference = 600.0

	# Lower ratings "move faster" and change more
	# dramatically than higher ones. Anything rating above
	# this value moves at the same rate as this value.
	elo_k_factor_constant_rating = 2200.0

	# This preset number of games is the number of games
	# where a player is considered "stable".
	# Rating volatility is constant after this number.
	volatility_constant = 20.0

	# Fair rating adjustment loses against inflation
	# This constant will battle inflation.
	# NOTE: This can be adjusted as needed by a
	# bot/server administrator
	anti_inflation = 0.015

	############ Functions ############
	def get_rating_adjustment(rating, opponent_rating, games_played, opponent_games_played, result):
	"""
	Calculates the rating adjustment after a 1v1 game finishes using simplified ELO.

	Arguments:
	rating, opponent_rating - Ratings of the players before this game.
	games_played, opponent_games_played - Number of games each player has played
	before this game.
	result - 1 for the first player (rating, games_played) won, 0 for draw, or
	-1 for the second player (opponent_rating, opponent_games_played) won.

	Returns:
	The integer that should be subtracted from the loser's rating and added
	to the winner's rating to get their new ratings.

	TODO: Team games.
	"""
	player_volatility = (min(games_played, volatility_constant) / volatility_constant + 0.25) / 1.25
	rating_k_factor = 50.0 * (min(rating, elo_k_factor_constant_rating) / elo_k_factor_constant_rating + 1.0) / 2.0
	volatility = rating_k_factor * player_volatility
	difference = opponent_rating - rating
	if result == 1:
	return round(max(0, (difference + result * elo_sure_win_difference) / volatility - anti_inflation))
	elif result == -1:
	return round(min(0, (difference + result * elo_sure_win_difference) / volatility - anti_inflation))
	else:
	return round(difference / volatility - anti_inflation)

	# Inflation test - A slightly negative is better than a slightly positive
	# Lower rated players stop playing more often than higher rated players
	# Uncomment to test.
	# In this example, two evenly matched players play for 150000 games.
	"""
	from random import randrange
	r1start = 1600
	r2start = 1600
	r1 = r1start
	r2 = r2start
	for x in range(0, 150000):
	res = randrange(3)-1 # How often one wins against the other
	if res >= 1:
	res = 1
	elif res <= -1:
	res = -1
	r1gain = get_rating_adjustment(r1, r2, 20, 20, res)
	r2gain = get_rating_adjustment(r2, r1, 20, 20, -1 * res)
	r1 += r1gain
	r2 += r2gain
	print(str(r1) + " " + str(r2) + " : " + str(r1 + r2-r1start - r2start))
	"""
	bbUnsubmitted Not Done Inline Actions This test should find his way into the test scripts bb: This test should find his way into the test scripts