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swaits committed 2013-07-30 01:54:47 -07:00
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rb/glicko2.rb
+168 -158
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@@ -40,179 +40,189 @@ class Glicko2
protected
# Glicko2 reprensentation (Glicko2 uses different scales from Glicko)
attr_accessor :g2rating, :g2deviation, :g2volatility
# Glicko2 reprensentation (Glicko2 uses different scales from Glicko)
attr_reader :g2rating, :g2deviation, :g2volatility
# a nested Class to hold a single result
Result = Struct.new(:opponent, :result)
# a nested Class to hold a single result
Result = Struct.new(:opponent, :result)
public
WIN = 1.0
LOSS = 0.0
DRAW = 0.5
WIN = 1.0
LOSS = 0.0
DRAW = 0.5
# Constructor with rating, rating deviation, and volatility optionally
# specified. If nothing specified, nitializes to a rating of 1500, a
# rating deviation of 350, and a volatility of 0.06.
def initialize(rating = 1500.0, deviation = 350.0, volatility = 0.06)
@dvolatility = 0.3
self.rating = rating
self.deviation = deviation
self.volatility = volatility
clear_results
# system constant, determines delta volatility over time; should be [0.3,1.2]
DVOL = 0.3
# Constructor with rating, rating deviation, and volatility optionally
# specified. If nothing specified, nitializes to a rating of 1500, a
# rating deviation of 350, and a volatility of 0.06.
def initialize(rating = 1500.0, deviation = 350.0, volatility = 0.06)
self.rating = rating
self.deviation = deviation
self.volatility = volatility
clear_results
end
include Comparable
# Comparison operator
def <=>(other)
p_win(other) <=> 0.5
end
# get the probability of beating opponent
def p_win(opponent)
1.0 / (1.0 + 10.0**(((opponent.rating - self.rating) / (400.0 * Math.sqrt(1.0 + 0.0000100723986 * (self.deviation**2.0 + opponent.deviation**2.0))))))
end
# Get the current rating. This rating is a Glicko rating, not a Glicko2 rating.
# For details, please see http://www.glicko.com/
def rating
(@g2rating * 173.7178) + 1500.0
end
# Set Glicko rating. Internally this is converted to a Glicko2 rating.
# For details, please see http://www.glicko.com/
def rating=(r)
@g2rating = (r - 1500.0) / 173.7178
end
# Get the current rating deviation. This is a Glicko rating deviation, not a
# Glicko-2 RD. For details, please see http://www.glicko.com/
def deviation
@g2deviation * 173.7178
end
# Set Glicko rating deviation. Internally this is converted to a Glicko-2 RD.
# For details, please see http://www.glicko.com/
def deviation=(d)
@g2deviation = d / 173.7178
end
# Get the current rating volatility.
def volatility
@g2volatility
end
# Set rating volatility.
def volatility=(v)
@g2volatility = v
end
# Clear all results previously added via add_result(), add_win(), add_loss(),
# and/or add_draw(). This method is called automatically whenever update()
# is called.
def clear_results
@opponents = Array.new
@results = Array.new
end
# Add a result to this rating. Note that no calculation is performed until
# update() is called.
def add_result(opponent,result)
@results << Result.new(opponent.clone, result)
end
# Add a win result to this rating. Note that no calculation is performed until
# update() is called.
def add_win(opponent)
add_result(opponent,Glicko2::WIN)
end
# Add a loss result to this rating. Note that no calculation is performed until
# update() is called.
def add_loss(opponent)
add_result(opponent,Glicko2::LOSS)
end
# Add a draw result to this rating. Note that no calculation is performed until
# update() is called.
def add_draw(opponent)
add_result(opponent,Glicko2::DRAW)
end
# util func 'g'
def Glicko2.g(deviation)
1.0 / (Math.sqrt(1.0 + 3.0 * deviation ** 2.0 / (Math::PI ** 2.0)))
end
# util func 'E'
def Glicko2.E(rating, rating_opponent, deviation_opponent)
1.0 / (1.0 + Math.exp(-Glicko2.g(deviation_opponent)*(rating - rating_opponent)));
end
# Update rating based on current results list, and clear results.
def update
# Note that if a player does not compete during the rating period, then
# only Step 6 applies.
if @results.empty?
# In this case, the player's rating and volatility parameters remain the
# same, but the RD increases according to:
@g2deviation = Math.sqrt(@g2deviation**2.0 + @g2volatility**2.0)
return
end
include Comparable
# Step 1. Determine a rating and RD for each player at the onset of the
# rating period. The system constant which constrains the change in
# volatility over time, needs to be set prior to application of the system.
# Reasonable choices are between 0.3 and 1.2, though the system should be
# tested to decide which value results in greatest predictive accuracy
# ... (ratings already stored in instance)
# Comparison operator
def <=>(other)
self.rating <=> other.rating
# Step 2. For each player, convert the ratings and RD's onto the Glicko-2
# scale.
# ... (ratings already stored in G2 format)
# Step 3. Compute the quantity v. This is the estimated variance of the
# team's/player's rating based only on game outcomes.
variance = 1.0 / @results.inject(0.0) do |sum,r|
g_i = Glicko2.g(r.opponent.g2deviation)
e_i = Glicko2.E(@g2rating, r.opponent.g2rating, r.opponent.g2deviation)
sum + g_i**2.0 * e_i * (1.0 - e_i)
end
# Get the current rating. This rating is a Glicko rating, not a Glicko2 rating.
# For details, please see http://www.glicko.com/
def rating
(@g2rating * 173.7178) + 1500.0
# Step 4. Compute the quantity 'delta', the estimated improvement in rating
# by comparing the pre-period rating to the performance rating based only
# on game outcomes.
delta = variance * @results.inject(0.0) do |sum,r|
g_i = Glicko2.g(r.opponent.g2deviation)
e_i = Glicko2.E(@g2rating, r.opponent.g2rating, r.opponent.g2deviation)
sum + g_i * (r.result - e_i)
end
# Set Glicko rating. Internally this is converted to a Glicko2 rating.
# For details, please see http://www.glicko.com/
def rating=(r)
@g2rating = (r - 1500.0) / 173.7178
# Step 5. Determine the new value of the volatility.
a = Math.log(@g2volatility**2.0)
x0, x1 = 0.0, a
while ((x0 - x1).abs > 0.0000001)
x0 = x1
d = @g2deviation**2.0 + variance + Math.exp(x0)
h1 = -(x0 - a)/(DVOL**2.0) - 0.5*Math.exp(x0)/d + 0.5*Math.exp(x0)*(delta/d)*(delta/d)
h2 = -1.0/(DVOL**2.0) - 0.5*Math.exp(x0)*(@g2deviation**2.0+variance)/(d**2.0) + 0.5*(delta**2.0)*Math.exp(x0)*((@g2deviation**2.0) + variance - Math.exp(x0))/(d**3.0)
x1 = x0 - h1/h2
end
new_volatility = Math.exp(x1 / 2.0)
# Step 6. Update the rating deviation to the new pre-rating period value.
pre_deviation = Math.sqrt(@g2deviation**2.0 + new_volatility**2.0)
# Step 7. Update the rating and RD to the new values.
new_deviation = 1.0 / (Math.sqrt(1.0/(pre_deviation**2.0) + 1.0 / variance))
new_rating = @g2rating + new_deviation**2.0 * @results.inject(0.0) do |sum,r|
g_i = Glicko2.g(r.opponent.g2deviation)
e_i = Glicko2.E(@g2rating, r.opponent.g2rating, r.opponent.g2deviation)
sum + g_i * (r.result - e_i)
end
# Get the current rating deviation. This is a Glicko rating deviation, not a
# Glicko-2 RD. For details, please see http://www.glicko.com/
def deviation
@g2deviation * 173.7178
end
# Step 8. Convert ratings and RD's back to original scale.
@g2deviation = new_deviation
@g2volatility = new_volatility
@g2rating = new_rating
# Set Glicko rating deviation. Internally this is converted to a Glicko-2 RD.
# For details, please see http://www.glicko.com/
def deviation=(d)
@g2deviation = d / 173.7178
end
# wipe our result lists
clear_results
end
# Get the current rating volatility.
def volatility
@g2volatility
end
# Set rating volatility.
def volatility=(v)
@g2volatility = v
end
# Clear all results previously added via add_result(), add_win(), add_loss(),
# and/or add_draw(). This method is called automatically whenever update()
# is called.
def clear_results
@opponents = []
@results = []
end
# Add a result to this rating. Note that no calculation is performed until
# update() is called.
def add_result(opponent,result)
@results.push( Result.new(opponent.clone, result) )
end
# Add a win result to this rating. Note that no calculation is performed until
# update() is called.
def add_win(opponent)
add_result(opponent,Glicko2::WIN)
end
# Add a loss result to this rating. Note that no calculation is performed until
# update() is called.
def add_loss(opponent)
add_result(opponent,Glicko2::LOSS)
end
# Add a draw result to this rating. Note that no calculation is performed until
# update() is called.
def add_draw(opponent)
add_result(opponent,Glicko2::DRAW)
end
# util func
def Glicko2.g(deviation)
1.0 / (Math.sqrt(1.0 + 3.0 * deviation ** 2.0 / (Math::PI ** 2.0)))
end
# util func
def Glicko2.E(rating, rating_opponent, deviation_opponent)
1.0 / (1.0 + Math.exp(-Glicko2.g(deviation_opponent)*(rating - rating_opponent)));
end
# Update rating based on current results list, and clear results.
def update
# util func
# bail if no opponents set
if @results.empty?
@g2deviation = Math.sqrt(@g2deviation**2.0 + @g2volatility**2.0)
return
end
# compute variance
#variance = 0.0
#@results.inject(0.0) do |variance,r|
# g_i = Glicko2.g(r.opponent.g2deviation)
# e_i = Glicko2.E(@g2rating,r.opponent.g2rating,r.opponent.g2deviation)
# g_i ** 2.0 * e_i * (1.0 - e_i)
#end
variance = 0.0
@results.each do |r|
g_i = Glicko2.g(r.opponent.g2deviation)
e_i = Glicko2.E(@g2rating,r.opponent.g2rating,r.opponent.g2deviation)
variance += g_i ** 2.0 * e_i * (1.0 - e_i)
end
variance = 1.0 / variance
# compute delta
delta = 0.0
@results.each do |r|
delta += Glicko2.g(r.opponent.g2deviation) * (r.result - Glicko2.E(@g2rating, r.opponent.g2rating, r.opponent.g2deviation))
end
delta *= variance
# determine new volatility
new_volatility = 0.0
a = Math.log( @g2volatility**2.0 )
x = 0.0
x_new = a
while ( (x - x_new).abs > 0.0000001 )
x = x_new
d = @g2deviation**2.0 + variance + Math.exp(x)
h1 = -(x - a)/(@dvolatility**2.0) - 0.5*Math.exp(x)/d + 0.5*Math.exp(x)*(delta/d)*(delta/d)
h2 = -1.0/(@dvolatility**2.0) - 0.5*Math.exp(x)*(@g2deviation**2.0+variance)/(d**2.0) + 0.5*(delta**2.0)*Math.exp(x)*((@g2deviation**2.0) + variance - Math.exp(x))/(d**3.0)
x_new = x - h1/h2
end
new_volatility = Math.exp(x_new / 2.0)
# update the rating deviation to the new pre-rating period value
pre_deviation = Math.sqrt( @g2deviation**2.0 + new_volatility**2.0 )
# update the rating and deviation
new_deviation = 1.0 / (Math.sqrt( 1.0/(pre_deviation**2.0) + 1.0 / variance))
new_rating = 0.0
@results.each do |r|
new_rating += Glicko2.g(r.opponent.g2deviation) * (r.result - Glicko2.E(@g2rating, r.opponent.g2rating, r.opponent.g2deviation))
end
new_rating = new_rating * new_deviation**2.0
new_rating += @g2rating
# wipe our result lists
clear_results
# copy new values
@g2deviation = new_deviation
@g2volatility = new_volatility
@g2rating = new_rating
end
end
rb/test_glicko2.rb
+23 -23
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@@ -5,30 +5,30 @@ require 'test/unit'
class TestGlicko2 < Test::Unit::TestCase
def test_simple
a = Glicko2.new(1500.0, 200.0, 0.06)
b = Glicko2.new(1400.0, 30.0, 0.06)
c = Glicko2.new(1550.0, 100.0, 0.06)
d = Glicko2.new(1700.0, 300.0, 0.06)
a.add_win(b)
a.add_loss(c)
a.add_result(d,0.0)
assert_equal(1500.0, a.rating)
assert_equal(200.0, a.deviation)
a.update()
assert_in_delta(1464.05,a.rating,0.01)
assert_in_delta(151.516,a.deviation,0.01)
def test_simple
a = Glicko2.new(1500.0, 200.0, 0.06)
b = Glicko2.new(1400.0, 30.0, 0.06)
c = Glicko2.new(1550.0, 100.0, 0.06)
d = Glicko2.new(1700.0, 300.0, 0.06)
a.update()
assert_in_delta(1464.05,a.rating,0.01)
assert_in_delta(151.875,a.deviation,0.01)
a.add_win(b)
a.add_loss(c)
a.add_result(d,0.0)
assert_equal(1500.0, a.rating)
assert_equal(200.0, a.deviation)
a.update()
assert_in_delta(1464.05,a.rating,0.01)
assert_in_delta(151.516,a.deviation,0.01)
a.update()
assert_in_delta(1464.05,a.rating,0.01)
assert_in_delta(151.875,a.deviation,0.01)
end
end
end