jct/trueskill
1
0
Fork 0
mirror of https://github.com/furyfire/trueskill.git synced 2025-10-31 00:12:29 +01:00
Code Issues Packages Projects Releases Wiki Activity

Start of factor graph port. Things don't work yet, but a lot of syntax updates towards PHP

Browse Source
This commit is contained in:
Jeff Moser
2010-09-18 11:11:44 -04:00
parent 4a76cc34cc
commit e434696b44
25 changed files with 1637 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files

46
HashMap.php Normal file
View File

@@ -0,0 +1,46 @@
<?php
class HashMap
{
private $_hashToValue = array();
private $_hashToKey = array();
public function getValue($key)
{
return $this->_hashToValue[self::getHash($key)];
}
public function setValue($key, $value)
{
$hash = self::getHash($key);
$this->_hashToKey[$hash] = $key;
$this->_hashToValue[$hash] = $value;
return $this;
}
public function getAllKeys()
{
return \array_values($this->_hashToKey);
}
public function getAllValues()
{
return \array_values($this->_hashToValue);
}
public function count()
{
return \count($this->_hashToKey);
}
private static function getHash($key)
{
if(\is_object($key))
{
return \spl_object_hash($key);
}
return $key;
}
}
?>

96
PHPSkills/FactorGraphs/Factor.php Normal file
View File

@@ -0,0 +1,96 @@
<?php
namespace Moserware\Skills\FactorGraphs;
require_once(dirname(__FILE__) . "../Guard.php");
require_once(dirname(__FILE__) . "../HashMap.php");
use Moserware\Skills\Guard;
use Moserware\Skills\HashMap;
class Factor
{
private $_messages = array();
private $_messageToVariableBinding;
private $_name;
private $_variables = array();
protected function __construct($name)
{
$this->_name = "Factor[" . $name . "]";
$this->_messagesToVariableBinding = new HashMap();
}
/// Returns the log-normalization constant of that factor
public function getLogNormalization()
{
return 0;
}
/// Returns the number of messages that the factor has
public function getNumberOfMessages()
{
return count($this->_messages);
}
protected function getVariables()
{
return $this->_variables;
}
protected function getMessages()
{
return $this->_messages;
}
/// Update the message and marginal of the i-th variable that the factor is connected to
public function updateMessageIndex($messageIndex)
{
Guard::argumentIsValidIndex($messageIndex, count($this->_messages), "messageIndex");
return $this->updateMessageVariable($this->_messages[$messageIndex], $this->_messageToVariableBinding->getValue($messageIndex));
}
protected function updateMessageVariable($message, $variable)
{
throw new Exception();
}
/// Resets the marginal of the variables a factor is connected to
public function resetMarginals()
{
foreach ($this->_messageToVariableBindings->getAllValues() as $currentVariable)
{
$currentVariable->resetToPrior();
}
}
/// Sends the ith message to the marginal and returns the log-normalization constant
public function sendMessageIndex($messageIndex)
{
Guard::argumentIsValidIndex($messageIndex, count($_messages), "messageIndex");
$message = $this->_messages[$messageIndex];
$variable = $this->_messageToVariableBinding->getValue($message);
return $this->sendMessageVariable($message, $variable);
}
protected abstract function sendMessageVariable($message, $variable);
public abstract function createVariableToMessageBinding($variable);
protected function createVariableToMessageBinding($variable, $message)
{
$index = count($this->_messages);
$this->_messages[] = $message;
$this->_messageToVariableBinding->setValue($message) = $variable;
$this->_variables[] = $variable;
return $message;
}
public function __toString()
{
return ($this->_name != null) ? $this->_name : base::__toString();
}
}
?>

18
PHPSkills/FactorGraphs/FactorGraph.php Normal file
View File

@@ -0,0 +1,18 @@
<?php
namespace Moserware\Skills\FactorGraphs;
class FactorGraph
{
private $_variableFactory;
public function getVariableFactory()
{
return $this->_variableFactory;
}
public function setVariableFactory($factory)
{
$this->_variableFactory = $factory;
}
}
?>

67
PHPSkills/FactorGraphs/FactorGraphLayer.php Normal file
View File

@@ -0,0 +1,67 @@
<?php
namespace Moserware\Skills\FactorGraphs;
abstract class FactorGraphLayer
{
private $_localFactors = array();
private $_outputVariablesGroups = array();
private $_inputVariablesGroups = array();
private $_parentFactorGraph;
protected function __construct($parentGraph)
{
$this->_parentFactorGraph = $parentGraph;
}
protected function getInputVariablesGroups()
{
return $this->_inputVariablesGroups;
}
// HACK
public function getParentFactorGraph()
{
return $this->_parentFactorGraph;
}
public function getOutputVariablesGroups()
{
return $this->_outputVariablesGroups;
}
public function getLocalFactors()
{
return $this->_localFactors;
}
public function setInputVariablesGroups($value)
{
$this->_inputVariablesGroups = $value;
}
protected function scheduleSequence($itemsToSequence)
{
return new ScheduleSequence($itemsToSequence);
}
protected function addLayerFactor($factor)
{
$this->_localFactors[] = $factor;
}
public abstract function buildLayer();
public function createPriorSchedule()
{
return null;
}
public function createPosteriorSchedule()
{
return null;
}
}
?>

57
PHPSkills/FactorGraphs/FactorList.php Normal file
View File

@@ -0,0 +1,57 @@
<?php
namespace Moserware\Skills\FactorGraphs;
/// <summary>
/// Helper class for computing the factor graph's normalization constant.
/// </summary>
class FactorList
{
private $_list = array();
public function getLogNormalization()
{
foreach($this->_list as $currentFactor)
{
$currentFactor->resetMarginals();
}
$sumLogZ = 0.0;
$listCount = count($this->_list);
for ($i = 0; $i < $listCount; $i++)
{
$f = $this->_list[$i];
$numberOfMessages = $f->getNumberOfMessages();
for ($j = 0; $j < $numberOfMessages; $j++)
{
$sumLogZ += $f->sendMessageIndex($j);
}
}
$sumLogS = 0;
foreach($this->_list as $currentFactor)
{
$sumLogS = $sumLogS + $currentFactor->getLogNormalization();
}
return $sumLogZ + $sumLogS;
}
public function count()
{
return count($this->_list);
}
public function addFactor(Factor $factor)
{
$this->_list[] = $factor;
return $factor;
}
}
?>

28
PHPSkills/FactorGraphs/Message.php Normal file
View File

@@ -0,0 +1,28 @@
<?php
namespace Moserware\Skills\FactorGraphs;
class Message
{
private $_nameFormat;
private $_nameFormatArgs;
private $_value;
public function __construct($value = null, $nameFormat = null, $args = null)
{
$this->_nameFormat = $nameFormat;
$this->_nameFormatArgs = $args;
$this->_value = $value;
}
public function getValue()
{
return $this->_value;
}
public function __toString()
{
return $this->_nameFormat; //return (_NameFormat == null) ? base.ToString() : String.Format(_NameFormat, _NameFormatArgs);
}
}
?>

89
PHPSkills/FactorGraphs/Schedule.php Normal file
View File

@@ -0,0 +1,89 @@
<?php
namespace Moserware\Skills\FactorGraphs;
abstract class Schedule
{
private $_name;
protected function __construct($name)
{
$this->_name = $name;
}
public abstract function visit($depth = -1, $maxDepth = 0);
public function __toString()
{
return $this->_name;
}
}
class ScheduleStep extends Schedule
{
private $_factor;
private $_index;
public function __construct($name, $factor, $index)
{
parent::__construct($name);
$this->_factor = $factor;
$this->_index = $index;
}
public function visit($depth, $maxDepth)
{
$delta = $this->_factor->updateMessageIndex($this->_index);
return $delta;
}
}
class ScheduleSequence extends Schedule
{
private $_schedules;
public function __construct($name, $schedules)
{
parent::__construct($name);
$this->_schedules = $schedules;
}
public function visit($depth, $maxDepth)
{
$maxDelta = 0;
foreach ($this->_schedules as $currentSchedule)
{
$maxDelta = max($currentSchedule->visit($depth + 1, $maxDepth), $maxDelta);
}
return $maxDelta;
}
}
class ScheduleLoop extends Schedule
{
private $_maxDelta;
private $_scheduleToLoop;
public function __construct($name, Schedule $scheduleToLoop, $maxDelta)
{
parent::__construct($name);
$this->_scheduleToLoop = $scheduleToLoop;
$this->_maxDelta = $maxDelta;
}
public function visit($depth, $maxDepth)
{
$totalIterations = 1;
$delta = $this->_scheduleToLoop->visit($depth + 1, $maxDepth);
while ($delta > $this->_maxDelta)
{
$delta = $this->_scheduleToLoop->visit($depth + 1, $maxDepth);
$totalIterations++;
}
return $delta;
}
}
?>

71
PHPSkills/FactorGraphs/Variable.php Normal file
View File

@@ -0,0 +1,71 @@
<?php
namespace Moserware\Skills\FactorGraphs;
class Variable
{
private $_name;
private $_prior;
private $_value;
public function __construct($name, $prior)
{
$this->_name = "Variable[" . $name . "]";
$this->_prior = $prior;
$this->resetToPrior();
}
public function getValue()
{
return $this->_value;
}
public function setValue($value)
{
$this->_value = $value;
}
public function resetToPrior()
{
$this->_value = $this->_prior;
}
public function __toString()
{
return $this->_name;
}
}
class DefaultVariable extends Variable
{
public function __construct()
{
parent::__construct("Default", null);
}
public function getValue()
{
return null;
}
public function setValue($value)
{
throw new Exception();
}
}
class KeyedVariable extends Variable
{
private $_key;
public function __construct($key, $name, $prior)
{
parent::__construct($name, $prior);
$this->_key = $key;
}
public function getKey()
{
return $this->_key;
}
}
?>

28
PHPSkills/FactorGraphs/VariableFactory.php Normal file
View File

@@ -0,0 +1,28 @@
<?php
namespace Moserware\Skills\FactorGraphs;
class VariableFactory
{
// using a Func<TValue> to encourage fresh copies in case it's overwritten
private $_variablePriorInitializer;
public function __construct($variablePriorInitializer)
{
$this->_variablePriorInitializer = $variablePriorInitializer;
}
public function createBasicVariable()
{
$newVar = new Variable($this->_variablePriorInitializer());
return $newVar;
}
public function createKeyedVariable($key)
{
$newVar = new KeyedVariable($key, $this->_variablePriorInitializer());
return $newVar;
}
}s
?>

10
PHPSkills/Numerics/GaussianDistribution.php
View File

@@ -48,6 +48,16 @@ class GaussianDistribution
{
return $this->_standardDeviation;
}
public function getPrecision()
{
return $this->_precision;
}
public function getPrecisionMean()
{
return $this->_precisionMean;
}
public function getNormalizationConstant()
{

34
PHPSkills/RatingContainer.php
View File

@@ -1,46 +1,40 @@
<?php
namespace Moserware\Skills;
require_once(dirname(__FILE__) . "/HashMap.php");
class RatingContainer
{
private $_playerHashToRating = array();
private $_playerHashToPlayer = array();
private $_playerToRating;
public function __construct()
{
$this->_playerToRating = new \HashMap();
}
public function getRating($player)
{
return $this->_playerHashToRating[self::getHash($player)];
return $this->_playerToRating->getValue($player);
}
public function setRating($player, $rating)
{
$hash = self::getHash($player);
$this->_playerHashToPlayer[$hash] = $player;
$this->_playerHashToRating[$hash] = $rating;
return $this;
return $this->_playerToRating->setValue($player, $rating);
}
public function getAllPlayers()
{
return \array_values($this->_playerHashToPlayer);
return $this->_playerToRating->getAllKeys();
}
public function getAllRatings()
{
return \array_values($this->_playerHashToRating);
return $this->_playerToRating->getAllValues();
}
public function count()
{
return \count($this->_playerHashToPlayer);
}
private static function getHash($player)
{
if(\is_object($player))
{
return \spl_object_hash($player);
}
return $player;
}
return \count($this->_playerToRating->count());
}
}
?>

168
PHPSkills/TrueSkill/FactorGraphTrueSkillCalculator.php Normal file
View File

@@ -0,0 +1,168 @@
<?php
namespace Moserware\Skills\TrueSkill;
/// <summary>
/// Calculates TrueSkill using a full factor graph.
/// </summary>
class FactorGraphTrueSkillCalculator extends SkillCalculator
{
public function __construct()
{
parent::__construct(SkillCalculatorSupportedOptions::PARTIAL_PLAY | SkillCalculatorSupportedOptions::PARTIAL_UPDATE, TeamsRange::atLeast(2), PlayersRange::atLeast(1));
}
public function CalculateNewRatings(GameInfo $gameInfo,
array $teams,
array $teamRanks)
{
Guard::argumentNotNull($gameInfo, "gameInfo");
$this->validateTeamCountAndPlayersCountPerTeam($teams);
RankSorter::sort($teams, $teamRanks);
$factorGraph = new TrueSkillFactorGraph($gameInfo, $teams, $teamRanks);
$factorGraph->buildGraph();
$factorGraph->runSchedule();
$probabilityOfOutcome = $factorGraph->getProbabilityOfRanking();
return $factorGraph->getUpdatedRatings();
}
public function calculateMatchQuality(GameInfo $gameInfo,
array $teams)
{
// We need to create the A matrix which is the player team assigments.
$teamAssignmentsList = $teams.ToList();
$skillsMatrix = $this->getPlayerCovarianceMatrix($teamAssignmentsList);
$meanVector = $this->getPlayerMeansVector($teamAssignmentsList);
$meanVectorTranspose = $meanVector->getTranspose();
$playerTeamAssignmentsMatrix = $this->createPlayerTeamAssignmentMatrix($teamAssignmentsList, $meanVector->getRowCount());
$playerTeamAssignmentsMatrixTranspose = $playerTeamAssignmentsMatrix->getTranspose();
$betaSquared = square($gameInfo->getBeta());
$start = Matrix::multiply($meanVectorTranspose, $playerTeamAssignmentsMatrix);
$aTa = Matrix::multiply(
Matrix::scalarMultiply($betaSquared,
$playerTeamAssignmentsMatrixTranspose),
$playerTeamAssignmentsMatrix);
$aTSA = Matrix::multiply(
Matrix::multiply($playerTeamAssignmentsMatrixTranspose, $skillsMatrix),
$playerTeamAssignmentsMatrix);
$middle = Matrix::add($aTa, $aTSA);
$middleInverse = $middle->getInverse();
$end = Matrix::multiply($playerTeamAssignmentsMatrixTranspose, $meanVector);
$expPartMatrix = Matrix::scalarMultiply(-0.5, (Matrix::multiply(Matrix::multiply($start, $middleInverse), $end)));
$expPart = $expPartMatrix->getDeterminant();
$sqrtPartNumerator = $aTa->getDeterminant();
$sqrtPartDenominator = $middle->getDeterminant();
$sqrtPart = $sqrtPartNumerator / $sqrtPartDenominator;
$result = exp($expPart) * sqrt($sqrtPart);
return $result;
}
private static function getPlayerMeansVector(array $teamAssignmentsList)
{
// A simple vector of all the player means.
return new Vector($this->getPlayerRatingValues($teamAssignmentsList,
function($rating)
{
return $rating->getMean();
}));
}
private static function getPlayerCovarianceMatrix(array $teamAssignmentsList)
{
// This is a square matrix whose diagonal values represent the variance (square of standard deviation) of all
// players.
return new DiagonalMatrix(
$this->getPlayerRatingValues($teamAssignmentsList,
function($rating)
{
return square($rating->getStandardDeviation());
}));
}
// Helper function that gets a list of values for all player ratings
private static function getPlayerRatingValues(array $teamAssignmentsList,
$playerRatingFunction)
{
$playerRatingValues = array();
foreach ($teamAssignmentsList as $currentTeam)
{
foreach (currentTeam.Values as $currentRating)
{
$playerRatingValues[] = $playerRatingFunction($currentRating);
}
}
return $playerRatingValues;
}
private static function createPlayerTeamAssignmentMatrix($teamAssignmentsList, $totalPlayers)
{
// The team assignment matrix is often referred to as the "A" matrix. It's a matrix whose rows represent the players
// and the columns represent teams. At Matrix[row, column] represents that player[row] is on team[col]
// Positive values represent an assignment and a negative value means that we subtract the value of the next
// team since we're dealing with pairs. This means that this matrix always has teams - 1 columns.
// The only other tricky thing is that values represent the play percentage.
// For example, consider a 3 team game where team1 is just player1, team 2 is player 2 and player 3, and
// team3 is just player 4. Furthermore, player 2 and player 3 on team 2 played 25% and 75% of the time
// (e.g. partial play), the A matrix would be:
// A = this 4x2 matrix:
// | 1.00 0.00 |
// | -0.25 0.25 |
// | -0.75 0.75 |
// | 0.00 -1.00 |
$playerAssignments = array();
$totalPreviousPlayers = 0;
$teamAssignmentsListCount = count($teamAssignmentsList);
for ($i = 0; $i < $teamAssignmentsListCount - 1; $i++)
{
$currentTeam = $teamAssignmentsList[$i];
// Need to add in 0's for all the previous players, since they're not
// on this team
$currentRowValues = array();
$playerAssignments[] = &$currentRowValues;
foreach ($currentTeam as $currentRating)
{
$currentRowValues[] = PartialPlay::getPartialPlayPercentage($currentRating->getKey());
// indicates the player is on the team
$totalPreviousPlayers++;
}
$nextTeam = $teamAssignmentsList[$i + 1];
foreach ($nextTeam as $nextTeamPlayerPair)
{
// Add a -1 * playing time to represent the difference
$currentRowValues[] = -1 * PartialPlay::getPartialPlayPercentage($nextTeamPlayerPair->getKey());
}
}
$playerTeamAssignmentsMatrix = new Matrix($totalPlayers, $teamAssignmentsListCount - 1, $playerAssignments);
return $playerTeamAssignmentsMatrix;
}
}
?>

32
PHPSkills/TrueSkill/Factors/GaussianFactor.php Normal file
View File

@@ -0,0 +1,32 @@
<?php
namespace Moserware\Skills\TrueSkill\Factors;
abstract class GaussianFactor extends Factor
{
protected function __construct($name)
{
parent::__construct($name);
}
/// Sends the factor-graph message with and returns the log-normalization constant
protected function sendMessageVariable(Message $message, Variable $variable)
{
$marginal = $variable->getValue();
$messageValue = $message->getValue();
$logZ = GaussianDistribution::logProductNormalization($marginal, $messageValue);
$variable->setValue($marginal*$messageValue);
return $logZ;
}
public function createVariableToMessageBinding(Variable $variable)
{
return parent::createVariableToMessageBinding($variable,
new Message(
GaussianDistribution::fromPrecisionMean(0, 0),
"message from {0} to {1}", $this));
}
}
?>

73
PHPSkills/TrueSkill/Factors/GaussianGreaterThanFactor.php Normal file
View File

@@ -0,0 +1,73 @@
<?php
namespace Moserware\Skills\TrueSkill\Factors;
/// <summary>
/// Factor representing a team difference that has exceeded the draw margin.
/// </summary>
/// <remarks>See the accompanying math paper for more details.</remarks>
class GaussianGreaterThanFactor extends GaussianFactor
{
private $_epsilon;
public function __construct($epsilon, Variable $variable)
{
parent::_construct("{0} > {1:0.000}");
$this->_epsilon = $epsilon;
$this->createVariableToMessageBinding($variable);
}
public function getLogNormalization()
{
$vars = $this->getVariables();
$marginal = $vars[0]->getValue();
$messages = $this->getMessages();
$message = $messages[0]->getValue();
$messageFromVariable = GaussianDistribution::divide($marginal, $message);
return -GaussianDistribution::logProductNormalization($messageFromVariable, $message)
+
log(
GaussianDistribution::cumulativeTo(($messageFromVariable->getMean() - $this->_epsilon)/
$messageFromVariable->getStandardDeviation()));
}
protected function updateMessageVariable(Message $message, Variable $variable)
{
$oldMarginal = clone $variable->getValue();
$oldMessage = clone $message->getValue();
$messageFromVar = GaussianDistribution::divide($oldMarginal, $oldMessage);
$c = $messageFromVar->getPrecision();
$d = $messageFromVar->getPrecisionMean();
$sqrtC = sqrt($c);
$dOnSqrtC = $d/$sqrtC;
$epsilsonTimesSqrtC = $this->_epsilon*$sqrtC;
$d = $messageFromVar->getPrecisionMean();
$denom = 1.0 - TruncatedGaussianCorrectionFunctions::vExceedsMargin($dOnSqrtC, $epsilsonTimesSqrtC);
$newPrecision = $c/$denom;
$newPrecisionMean = ($d +
$sqrtC*
TruncatedGaussianCorrectionFunctions::vExceedsMargin($dOnSqrtC, $epsilsonTimesSqrtC))/
$denom;
$newMarginal = GaussianDistribution::fromPrecisionMean($newPrecisionMean, $newPrecision);
$newMessage = GaussianDistribution::divide(
GaussianDistribution::multiply($oldMessage, $newMarginal),
$oldMarginal);
/// Update the message and marginal
$message->setValue($newMessage);
$variable->setValue($newMarginal);
/// Return the difference in the new marginal
return GaussianDistribution::subtract($newMarginal, $oldMarginal);
}
}
?>

78
PHPSkills/TrueSkill/Factors/GaussianLikelihoodFactor.php Normal file
View File

@@ -0,0 +1,78 @@
<?php
namespace Moserware\Skills\TrueSkill\Factors;
/// <summary>
/// Connects two variables and adds uncertainty.
/// </summary>
/// <remarks>See the accompanying math paper for more details.</remarks>
class GaussianLikelihoodFactor extends GaussianFactor
{
private $_precision;
public function __construct($betaSquared, Variable $variable1, Variable $variable2)
{
parent::__construct("Likelihood of {0} going to {1}");
$this->_precision = 1.0/$betaSquared;
$this->createVariableToMessageBinding($variable1);
$this->createVariableToMessageBinding($variable2);
}
public function getLogNormalization()
{
$vars = $this->getVariables();
$messages = $this->getMessages();
return GaussianDistribution::logRatioNormalization(
$vars[0]->getValue(),
$messages[0]->getValue());
}
private function updateHelper(Message $message1, Message $message2,
Variable $variable1, Variable $variable2)
{
$message1Value = clone $message1->getValue();
$message2Value = clone $message2->getValue();
$marginal1 = clone $variable1->getValue();
$marginal2 = clone $variable2->getValue();
$a = $this->_precision/($this->_precision + $marginal2->getPrecision() - $message2Value->getPrecision());
$newMessage = GaussianDistribution::fromPrecisionMean(
$a*($marginal2->getPrecisionMean() - $message2Value->getPrecisionMean()),
$a*($marginal2->getPrecision() - $message2Value->getPrecision()));
$oldMarginalWithoutMessage = GaussianDistribution::divide($marginal1, $message1Value);
$newMarginal = GaussianDistribution::multiply($oldMarginalWithoutMessage, $newMessage);
/// Update the message and marginal
$message1->setValue($newMessage);
$variable1->setValue($newMarginal);
/// Return the difference in the new marginal
return GaussianDistribution::subtract($newMarginal, $marginal1);
}
public function updateMessageIndex($messageIndex)
{
$messages = $this->getMessages();
$vars = $this->getVariables();
switch ($messageIndex)
{
case 0:
return $this->updateHelper($messages[0], $messages[1],
$vars[0], $vars[1]);
case 1:
return $this->updateHelper($messages[1], $messages[0],
$vars[1], $vars[0]);
default:
throw new Exception();
}
}
}
?>

40
PHPSkills/TrueSkill/Factors/GaussianPriorFactor.php Normal file
View File

@@ -0,0 +1,40 @@
<?php
namespace Moserware\Skills\TrueSkill\Factors;
/// <summary>
/// Supplies the factor graph with prior information.
/// </summary>
/// <remarks>See the accompanying math paper for more details.</remarks>
class GaussianPriorFactor extends GaussianFactor
{
private $_newMessage;
public function __construct($mean, $variance, Variable $variable)
{
parent::__construct("Prior value going to {0}");
$this->_newMessage = new GaussianDistribution($mean, sqrt($variance));
$this->createVariableToMessageBinding($variable,
new Message(
GaussianDistribution::fromPrecisionMean(0, 0),
"message from {0} to {1}",
this, variable));
}
protected function updateMessageVariable(Message $message, Variable $variable)
{
$oldMarginal = clone $variable->getValue();
$oldMessage = $message;
$newMarginal =
GaussianDistribution::fromPrecisionMean(
$oldMarginal->getPrecisionMean() + $this->_newMessage->getPrecisionMean() - $oldMessage->getValue()->getPrecisionMean(),
$oldMarginal->getPrecision() + $this->_newMessage->getPrecision() - $oldMessage->getValue()->getPrecision());
$variable->setValue($newMarginal);
$message->setValue($this->_newMessage);
return GaussianDistribution::subtract($oldMarginal, $newMarginal);
}
}
?>

216
PHPSkills/TrueSkill/Factors/GaussianWeightedSumFactor.php Normal file
View File

@@ -0,0 +1,216 @@
<?php
namespace Moserware\Skills\TrueSkill\Factors;
/// <summary>
/// Factor that sums together multiple Gaussians.
/// </summary>
/// <remarks>See the accompanying math paper for more details.</remarks>
class GaussianWeightedSumFactor extends GaussianFactor
{
private $_variableIndexOrdersForWeights = array();
// This following is used for convenience, for example, the first entry is [0, 1, 2]
// corresponding to v[0] = a1*v[1] + a2*v[2]
private $_weights;
private $_weightsSquared;
public function __construct(Variable $sumVariable, array $variablesToSum, array $variableWeights = null)
{
parent::__construct($this->createName($sumVariable, $variablesToSum, $variableWeights));
$this->_weights = array();
$this->_weightsSquared = array();
// The first weights are a straightforward copy
// v_0 = a_1*v_1 + a_2*v_2 + ... + a_n * v_n
$this->_weights[0] = array();
$variableWeightsLength = count($variableWeights);
for($i = 0; $i < $variableWeightsLength; $i++)
{
$weight = $variableWeights[$i];
$this->_weights[0][$i] = $weight;
$this->_weightsSquared[0][i] = $weight * $weight;
}
$variablesToSumLength = count($variablesToSum);
// 0..n-1
for($i = 0; $i < ($variablesToSumLength + 1); $i++)
{
$this->_variableIndexOrdersForWeights[] = $i;
}
// The rest move the variables around and divide out the constant.
// For example:
// v_1 = (-a_2 / a_1) * v_2 + (-a3/a1) * v_3 + ... + (1.0 / a_1) * v_0
// By convention, we'll put the v_0 term at the end
$weightsLength = $variableWeightsLength + 1;
for ($weightsIndex = 1; $weightsIndex < $weightsLength; $weightsIndex++)
{
$this->_weights[$weightsIndex] = array();
$variableIndices = array();
$variableIndices[] = $weightsIndex;
$currentWeightsSquared = array();
$this->_WeightsSquared[$weightsIndex] = $currentWeightsSquared;
// keep a single variable to keep track of where we are in the array.
// This is helpful since we skip over one of the spots
$currentDestinationWeightIndex = 0;
for ($currentWeightSourceIndex = 0;
$currentWeightSourceIndex < $variableWeights.Length;
$currentWeightSourceIndex++)
{
if ($currentWeightSourceIndex == ($weightsIndex - 1))
{
continue;
}
$currentWeight = (-$variableWeights[$currentWeightSourceIndex]/$variableWeights[$weightsIndex - 1]);
if ($variableWeights[$weightsIndex - 1] == 0)
{
// HACK: Getting around division by zero
$currentWeight = 0;
}
$currentWeights[$currentDestinationWeightIndex] = $currentWeight;
$currentWeightsSquared[$currentDestinationWeightIndex] = $currentWeight*currentWeight;
$variableIndices[$currentDestinationWeightIndex + 1] = $currentWeightSourceIndex + 1;
$currentDestinationWeightIndex++;
}
// And the final one
$finalWeight = 1.0/$variableWeights[$weightsIndex - 1];
if ($variableWeights[$weightsIndex - 1] == 0)
{
// HACK: Getting around division by zero
$finalWeight = 0;
}
$currentWeights[$currentDestinationWeightIndex] = finalWeight;
$currentWeightsSquared[currentDestinationWeightIndex] = finalWeight*finalWeight;
$variableIndices[$variableIndices.Length - 1] = 0;
$this->_variableIndexOrdersForWeights[] = $variableIndices;
}
$this->createVariableToMessageBinding($sumVariable);
foreach ($variablesToSum as $currentVariable)
{
$this->createVariableToMessageBinding($currentVariable);
}
}
public function getLogNormalization()
{
$vars = $this->getVariables();
$messages = $this->getMessages();
$result = 0.0;
// We start at 1 since offset 0 has the sum
$varCount = count($vars);
for ($i = 1; $i < $varCount; $i++)
{
$result += GaussianDistribution::logRatioNormalization($vars[i]->getValue(), $messages[i]->getValue());
}
return $result;
}
private function updateHelper(array $weights, array $weightsSquared,
array $messages,
array $variables)
{
// Potentially look at http://mathworld.wolfram.com/NormalSumDistribution.html for clues as
// to what it's doing
$messages = $this->getMessages();
$message0 = clone $messages[0]->getValue();
$marginal0 = clone $variables[0]->getValue();
// The math works out so that 1/newPrecision = sum of a_i^2 /marginalsWithoutMessages[i]
$inverseOfNewPrecisionSum = 0.0;
$anotherInverseOfNewPrecisionSum = 0.0;
$weightedMeanSum = 0.0;
$anotherWeightedMeanSum = 0.0;
$weightsSquaredLength = count($weightsSquared);
for ($i = 0; $i < $weightsSquaredLength; $i++)
{
// These flow directly from the paper
$inverseOfNewPrecisionSum += $weightsSquared[i]/
($variables[$i + 1]->getValue()->getPrecision() - $messages[$i + 1]->getValue()->getPrecision());
$diff = GaussianDistribution::divide($variables[$i + 1]->getValue(), $messages[$i + 1]->getValue());
$anotherInverseOfNewPrecisionSum += $weightsSquared[i]/$diff->getPrecision();
$weightedMeanSum += $weights[i]
*
($variables[$i + 1]->getValue()->getPrecisionMean() - $messages[$i + 1]->getValue()->getPrecisionMean())
/
($variables[$i + 1]->getValue()->getPrecision() - $messages[$i + 1]->getValue()->getPrecision());
$anotherWeightedMeanSum += $weights[$i]*$diff->getPrecisionMean()/$diff->getPrecision();
}
$newPrecision = 1.0/$inverseOfNewPrecisionSum;
$anotherNewPrecision = 1.0/$anotherInverseOfNewPrecisionSum;
$newPrecisionMean = $newPrecision*$weightedMeanSum;
$anotherNewPrecisionMean = $anotherNewPrecision*$anotherWeightedMeanSum;
$newMessage = GaussianDistribution::fromPrecisionMean($newPrecisionMean, $newPrecision);
$oldMarginalWithoutMessage = GaussianDistribution::divide($marginal0, $message0);
$newMarginal = GaussianDistribution::multiply($oldMarginalWithoutMessage, $newMessage);
/// Update the message and marginal
$messages[0]->setValue($newMessage);
$variables[0]->setValue($newMarginal);
/// Return the difference in the new marginal
$finalDiff = GaussianDistribution::subtract($newMarginal, $marginal0);
return $finalDiff;
}
public function updateMessageIndex($messageIndex)
{
$allMessages = $this->getMessages();
$allVariables = $this->getVariables();
Guard::argumentIsValidIndex($messageIndex, count($allMessages),"messageIndex");
$updatedMessages = array();
$updatedVariables = array();
$indicesToUse = $this->_variableIndexOrdersForWeights[$messageIndex];
// The tricky part here is that we have to put the messages and variables in the same
// order as the weights. Thankfully, the weights and messages share the same index numbers,
// so we just need to make sure they're consistent
$allMessagesCount = count($allMessages);
for ($i = 0; i < $allMessagesCount; $i++)
{
$updatedMessages[] =$allMessages[$indicesToUse[$i]];
$updatedVariables[] = $allVariables[$indicesToUse[$i]];
}
return updateHelper($this->_weights[$messageIndex],
$this->_weightsSquared[$messageIndex],
$updatedMessages,
$updatedVariables);
}
}
?>

72
PHPSkills/TrueSkill/Factors/GaussianWithinFactor.php Normal file
View File

@@ -0,0 +1,72 @@
<?php
namespace Moserware\Skills\TrueSkill\Factors;
/// <summary>
/// Factor representing a team difference that has not exceeded the draw margin.
/// </summary>
/// <remarks>See the accompanying math paper for more details.</remarks>
class GaussianWithinFactor extends GaussianFactor
{
private $_epsilon;
public function __construct($epsilon, Variable $variable)
{
$this->_epsilon = $epsilon;
$this->createVariableToMessageBinding($variable);
}
public function getLogNormalization()
{
$variables = $this->getVariables();
$marginal = $variables[0]->getValue();
$messages = $this->getMessages();
$message = $messages[0]->getValue();
$messageFromVariable = GaussianDistribution::divide($marginal, $message);
$mean = $messageFromVariable->getMean();
$std = $messageFromVariable->getStandardDeviation();
$z = GaussianDistribution::cumulativeTo(($this->_epsilon - $mean)/$std)
-
GaussianDistribution::cumulativeTo((-$this->_epsilon - $mean)/$std);
return -GaussianDistribution::logProductNormalization($messageFromVariable, $message) + log($z);
}
protected function updateMessage(Message $message, Variable $variable)
{
$oldMarginal = clone $variable->getValue();
$oldMessage = clone $message->getValue();
$messageFromVariable = GaussianDistribution::divide($oldMarginal, $oldMessage);
$c = $messageFromVariable->getPrecision();
$d = $messageFromVariable->getPrecisionMean();
$sqrtC = sqrt($c);
$dOnSqrtC = $d/$sqrtC;
$epsilonTimesSqrtC = $this->_epsilon*$sqrtC;
$d = $messageFromVariable->getPrecisionMean();
$denominator = 1.0 - TruncatedGaussianCorrectionFunctions::wWithinMargin($dOnSqrtC, $epsilonTimesSqrtC);
$newPrecision = $c/$denominator;
$newPrecisionMean = ($d +
$sqrtC*
TruncatedGaussianCorrectionFunctions::vWithinMargin($dOnSqrtC, $epsilonTimesSqrtC))/
$denominator;
$newMarginal = GaussianDistribution::fromPrecisionMean($newPrecisionMean, $newPrecision);
$newMessage = GaussianDistribution::divide(
GaussianDistribution::multiply($oldMessage, $newMarginal),
$oldMarginal);
/// Update the message and marginal
$message->setValue($newMessage);
$variable->setValue($newMarginal);
/// Return the difference in the new marginal
return GaussianDistribution::subtract($newMarginal, $oldMarginal);
}
}
?>

147
PHPSkills/TrueSkill/Layers/IteratedTeamDifferencesInnerLayer.php Normal file
View File

@@ -0,0 +1,147 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
// The whole purpose of this is to do a loop on the bottom
class IteratedTeamDifferencesInnerLayer extends TrueSkillFactorGraphLayer
{
private $_TeamDifferencesComparisonLayer;
private $_TeamPerformancesToTeamPerformanceDifferencesLayer;
public function __construct(TrueSkillFactorGraph $parentGraph,
TeamPerformancesToTeamPerformanceDifferencesLayer $teamPerformancesToPerformanceDifferences,
TeamDifferencesComparisonLayer $teamDifferencesComparisonLayer)
{
parent::__construct($parentGraph);
$this->_TeamPerformancesToTeamPerformanceDifferencesLayer = $teamPerformancesToPerformanceDifferences;
$this->_TeamDifferencesComparisonLayer = $teamDifferencesComparisonLayer;
}
public function buildLayer()
{
$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->setRawInputVariablesGroups($this->getInputVariablesGroups());
$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->buildLayer();
$this->_TeamDifferencesComparisonLayer->setRawInputVariablesGroups(
$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getRawOutputVariablesGroups());
$this->_TeamDifferencesComparisonLayer->buildLayer();
}
public function createPriorSchedule()
{
// BLOG about $loop
switch (count($this->getInputVariablesGroups()))
{
case 0:
case 1:
throw new InvalidOperationException();
case 2:
$loop = $this->createTwoTeamInnerPriorLoopSchedule();
break;
default:
$loop = $this->createMultipleTeamInnerPriorLoopSchedule();
break;
}
// When dealing with differences, there are always (n-1) differences, so add in the 1
$totalTeamDifferences = count($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors());
$totalTeams = $totalTeamDifferences + 1;
$innerSchedule = new ScheduleSequence(
"inner schedule",
array(
$loop,
new ScheduleStep(
"teamPerformanceToPerformanceDifferenceFactors[0] @ 1",
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[0], 1),
new ScheduleStep(
"teamPerformanceToPerformanceDifferenceFactors[teamTeamDifferences = {0} - 1] @ 2",
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[$totalTeamDifferences - 1], 2)
)
);
return innerSchedule;
}
private function createTwoTeamInnerPriorLoopSchedule()
{
return $this->scheduleSequence(
array(
new ScheduleStep(
"send team perf to perf differences",
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[0],
0),
new ScheduleStep(
"send to greater than or within factor",
($this->_TeamDifferencesComparisonLayer->getLocalFactors())[0],
0)
),
"loop of just two teams inner sequence");
}
private function createMultipleTeamInnerPriorLoopSchedule()
{
$totalTeamDifferences = count($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors());
$forwardScheduleList = array();
for ($i = 0; $i < $totalTeamDifferences - 1; $i++)
{
$currentForwardSchedulePiece =
$this->scheduleSequence(
array(
new ScheduleStep(
sprintf("team perf to perf diff %d", $i),
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[$i], 0),
new ScheduleStep(
sprintf("greater than or within result factor %d", $i),
($this->_TeamDifferencesComparisonLayer->getLocalFactors())[$i], 0),
new ScheduleStep(
sprintf("team perf to perf diff factors [%d], 2", $i),
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[$i], 2)
), sprintf("current forward schedule piece %d", $i);
$forwardScheduleList[] = $currentForwardSchedulePiece;
}
$forwardSchedule = new ScheduleSequence("forward schedule", $forwardScheduleList);
$backwardScheduleList = array();
for ($i = 0; $i < $totalTeamDifferences - 1; $i++)
{
$currentBackwardSchedulePiece = new ScheduleSequence(
"current backward schedule piece",
array(
new ScheduleStep(
sprintf("teamPerformanceToPerformanceDifferenceFactors[totalTeamDifferences - 1 - %d] @ 0", $i),
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[$totalTeamDifferences - 1 - $i], 0),
new ScheduleStep(
sprintf("greaterThanOrWithinResultFactors[totalTeamDifferences - 1 - %d] @ 0", $i),
($this->_TeamDifferencesComparisonLayer->getLocalFactors())[$totalTeamDifferences - 1 - $i], 0),
new ScheduleStep(
sprintf("teamPerformanceToPerformanceDifferenceFactors[totalTeamDifferences - 1 - %d] @ 1", $i),
($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors())[$totalTeamDifferences - 1 - $i], 1)
);
$backwardScheduleList[] = $currentBackwardSchedulePiece;
}
$backwardSchedule = new ScheduleSequence("backward schedule", $backwardScheduleList);
$forwardBackwardScheduleToLoop =
new ScheduleSequence(
"forward Backward Schedule To Loop",
array($forwardSchedule, $backwardSchedule));
$initialMaxDelta = 0.0001;
$loop = new ScheduleLoop(
sprintf("loop with max delta of %f", $initialMaxDelta),
$forwardBackwardScheduleToLoop,
$initialMaxDelta);
return $loop;
}
}
?>

71
PHPSkills/TrueSkill/Layers/PlayerPerformancesToTeamPerformancesLayer.php Normal file
View File

@@ -0,0 +1,71 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
class PlayerPerformancesToTeamPerformancesLayer extends TrueSkillFactorGraphLayer
{
public function __construct(TrueSkillFactorGraph $parentGraph)
{
parent::__construct($parentGraph);
}
public function buildLayer()
{
foreach ($this->getInputVariablesGroups() as $currentTeam)
{
$teamPerformance = $this->createOutputVariable($currentTeam);
$this->addLayerFactor($this->createPlayerToTeamSumFactor($currentTeam, $teamPerformance));
// REVIEW: Does it make sense to have groups of one?
$this->getOutputVariablesGroups() = $teamPerformance;
}
}
public function createPriorSchedule()
{
return $this->scheduleSequence(
array_map(
function($weightedSumFactor)
{
return new ScheduleStep("Perf to Team Perf Step", $weightedSumFactor, 0);
},
$this->getLocalFactors()),
"all player perf to team perf schedule");
}
protected function createPlayerToTeamSumFactor($teamMembers, $sumVariable)
{
return new GaussianWeightedSumFactor(
$sumVariable,
$teamMembers,
array_map(
function($v)
{
return PartialPlay::getPartialPlayPercentage($v->getKey());
},
$teamMembers));
}
public function createPosteriorSchedule()
{
// BLOG
return $this->scheduleSequence(
from currentFactor in LocalFactors
from currentIteration in
Enumerable.Range(1, currentFactor.NumberOfMessages - 1)
select new ScheduleStep<GaussianDistribution>(
"team sum perf @" + currentIteration,
currentFactor,
currentIteration),
"all of the team's sum iterations");
}
private function createOutputVariable($team)
{
$teamMemberNames = String.Join(", ", team.Select(teamMember => teamMember.Key.ToString()).ToArray());
return ParentFactorGraph.VariableFactory.CreateBasicVariable("Team[{0}]'s performance", teamMemberNames);
}
}
?>

59
PHPSkills/TrueSkill/Layers/PlayerPriorValuesToSkillsLayer.php Normal file
View File

@@ -0,0 +1,59 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
// We intentionally have no Posterior schedule since the only purpose here is to
class PlayerPriorValuesToSkillsLayer extends TrueSkillFactorGraphLayer
{
private $_teams;
public function __construct(TrueSkillFactorGraph $parentGraph, $teams)
{
parent::__construct($parentGraph);
$this->_teams = $teams;
}
public function buildLayer()
{
foreach ($this->_teams as $currentTeam)
{
$currentTeamSkills = array();
foreach ($currentTeam as $currentTeamPlayer)
{
$playerSkill = $this->createSkillOutputVariable($currentTeamPlayer.Key);
$this->addLayerFactor($this->createPriorFactor($currentTeamPlayer.Key, $currentTeamPlayer.Value, $playerSkill));
$currentTeamSkills[] = $playerSkill;
}
OutputVariablesGroups.Add(currentTeamSkills);
}
}
public function createPriorSchedule()
{
return $this->scheduleSequence(
array_map(
function($prior)
{
return new ScheduleStep("Prior to Skill Step", $prior, 0);
},
$this->getLocalFactors()),
"All priors");
}
private function createPriorFactor($player, $priorRating, $skillsVariable)
{
return new GaussianPriorFactor($priorRating->getMean(),
square($priorRating->getStandardDeviation()) +
square($this->getParentFactorGraph()->getGameInfo()->getDynamicsFactor()),
$skillsVariable);
}
private function createSkillOutputVariable($key)
{
return $this->getParentFactorGraph()->getVariableFactory()->createKeyedVariable($key, "{0}'s skill", $key);
}
}
?>

64
PHPSkills/TrueSkill/Layers/PlayerSkillsToPerformancesLayer.php Normal file
View File

@@ -0,0 +1,64 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
class PlayerSkillsToPerformancesLayer extends TrueSkillFactorGraphLayer
{
public function __construct(TrueSkillFactorGraph $parentGraph)
{
parent::__construct($parentGraph);
}
public function buildLayer()
{
foreach ($this->getInputVariablesGroups() as $currentTeam)
{
$currentTeamPlayerPerformances = array();
foreach ($currentTeam as $playerSkillVariable)
{
$playerPerformance = $this->createOutputVariable($playerSkillVariable->getKey());
$this->addLayerFactor($this->createLikelihood($playerSkillVariable, $playerPerformance));
$currentTeamPlayerPerformances[] = $playerPerformance;
}
$this->getOutputVariablesGroups()[] = $currentTeamPlayerPerformances;
}
}
private function createLikelihood($playerSkill, $playerPerformance)
{
return new GaussianLikelihoodFactor(square($this->getParentFactorGraph()->getGameInfo()->getBeta()), $playerPerformance, $playerSkill);
}
private function createOutputVariable($key)
{
return $this->getParentFactorGraph()->getVariableFactory()->createKeyedVariable($key, "{0}'s performance", $key);
}
public function createPriorSchedule()
{
return $this->scheduleSequence(
array_map(
function($likelihood)
{
return $this->scheduleStep("Skill to Perf step", $likelihood, 0);
},
$this->getLocalFactors()),
"All skill to performance sending");
}
public function createPosteriorSchedule()
{
return $this->scheduleSequence(
array_map(
function($likelihood)
{
return new ScheduleStep("name", $likelihood, 1);
},
$this->getLocalFactors()),
"All skill to performance sending");
}
}
?>

38
PHPSkills/TrueSkill/Layers/TeamDifferencesComparisonLayer.php Normal file
View File

@@ -0,0 +1,38 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
class TeamDifferencesComparisonLayer extends TrueSkillFactorGraphLayer
{
private $_epsilon;
private $_teamRanks;
public function __construct(TrueSkillFactorGraph $parentGraph, array $teamRanks)
{
parent::__construct($parentGraph);
$this->_teamRanks = $teamRanks;
$gameInfo = $this->getParentFactorGraph()->getGameInfo();
$this->_epsilon = DrawMargin::getDrawMarginFromDrawProbability($gameInfo->getDrawProbability(), $gameInfo->getBeta());
}
public function buildLayer()
{
$inputVarGroups = $this->getInputVariablesGroups();
$inputVarGroupsCount = count($inputVarGroups);
for ($i = 0; $i < $inputVarGroupsCount; $i++)
{
$isDraw = ($this->_teamRanks[$i] == $this->_teamRanks[$i + 1]);
$teamDifference = $inputVarGroups[$i][0];
$factor =
$isDraw
? new GaussianWithinFactor($this->_epsilon, $teamDifference)
: new GaussianGreaterThanFactor($this->_epsilon, $teamDifference);
$this->addLayerFactor($factor);
}
}
}
?>

42
PHPSkills/TrueSkill/Layers/TeamPerformancesToTeamPerformanceDifferencesLayer.php Normal file
View File

@@ -0,0 +1,42 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
class TeamPerformancesToTeamPerformanceDifferencesLayer extends TrueSkillFactorGraphLayer
{
public function __construct(TrueSkillFactorGraph $parentGraph)
{
parent::__construct($parentGraph);
}
public function buildLayer()
{
$inputVariablesGroup = $this->getInputVariablesGroups();
$inputVariablesGroupCount = count($inputVariablesGroup);
for ($i = 0; $i < $inputVariablesGroupCount - 1; $i++)
{
$strongerTeam = $inputVariablesGroups[$i][0];
$weakerTeam = $inputVariablesGroups[$i + 1][0];
$currentDifference = $this->createOutputVariable();
$this->addLayerFactor($this->createTeamPerformanceToDifferenceFactor($strongerTeam, $weakerTeam, currentDifference));
// REVIEW: Does it make sense to have groups of one?
$this->getOutputVariablesGroups()[] = $currentDifference;
}
}
private function createTeamPerformanceToDifferenceFactor(
Variable $strongerTeam, Variable $weakerTeam, Variable $output)
{
return new GaussianWeightedSumFactor($output, array($strongerTeam, $weakerTeam), array(1.0, -1.0));
}
private function createOutputVariable()
{
return $this->getParentFactorGraph()->getVariableFactory()->createBasicVariable("Team performance difference");
}
}
?>

13
PHPSkills/TrueSkill/Layers/TrueSkillFactorGraphLayer.php Normal file
View File

@@ -0,0 +1,13 @@
<?php
namespace Moserware\Skills\TrueSkill\Layers;
abstract class TrueSkillFactorGraphLayer extends FactorGraphLayer
{
public function __construct(TrueSkillFactorGraph $parentGraph)
{
parent::__construct($parentGraph);
}
}
?>