Skip to main content

A python implementation of the whole-history-rating algorythm by Rémi Coulom

Project description

# whole_history_rating
a python convertion from the ruby implementation of Rémi Coulom's Whole-History Rating (WHR) algorithm.

the original code can be found [here](


pip install whole_history_rating


from whr import whole_history_rating

whr = whole_history_rating.Base()

# Base.create_game() arguments: black player name, white player name, winner, day number, handicap
# Handicap should generally be less than 500 elo
whr.create_game("shusaku", "shusai", "B", 1, 0)
whr.create_game("shusaku", "shusai", "W", 2, 0)
whr.create_game("shusaku", "shusai", "W", 3, 0)

# Iterate the WHR algorithm towards convergence with more players/games, more iterations are needed.

# Or let the module iterate until the elo is stable (precision by default 10E-3) with a time limit of 10 seconds by default
whr.auto_iterate(time_limit = 10, precision = 10E-3)

# Results are stored in one triplet for each day: [day_number, elo_rating, uncertainty]
whr.ratings_for_player("shusaku") =>
[[1, -43, 84],
[2, -45, 84],
[3, -45, 84]]
whr.ratings_for_player("shusai") =>
[[1, 43, 84],
[2, 45, 84],
[3, 45, 84]]

# You can print or get all ratings ordered

# You can get a prediction for a future game between two players (even non existing players)
# Base.probability_future_match() arguments: black player name, white player name, handicap
whr.probability_future_match("shusaku", "shusai",0) =>
win probability: shusaku:37.24%; shusai:62.76%

# You can load several games all together using a file or a list of string representing the game
# all elements in list must be like: "black_name white_name winner time_step handicap extras"
# you can exclude handicap (default=0) and extras (default={})
whr.load_games(["shusaku shusai B 1 0", "shusaku shusai W 2", "shusaku shusai W 3 0"])
whr.load_games(["firstname1 name1, firstname2 name2, W, 1"], separator=",")

# You can save and load a base (you don't have to redo all iterations)
whr2 = whole_history_rating.Base.load_base(path)

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
whole_history_rating-1.3.3-py3-none-any.whl (11.0 kB) Copy SHA256 hash SHA256 Wheel py3 Jul 7, 2018
whole_history_rating-1.3.3.tar.gz (7.9 kB) Copy SHA256 hash SHA256 Source None Jul 7, 2018

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page