Naming tweak

This commit is contained in:
Jeff Moser
2010-10-14 21:51:43 -04:00
parent 110463ad49
commit 455f2b3061
66 changed files with 24 additions and 26 deletions

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<?php
namespace Moserware\Skills\TrueSkill;
require_once(dirname(__FILE__) . "/../Numerics/GaussianDistribution.php");
use Moserware\Numerics\GaussianDistribution;
final class DrawMargin
{
public static function getDrawMarginFromDrawProbability($drawProbability, $beta)
{
// Derived from TrueSkill technical report (MSR-TR-2006-80), page 6
// draw probability = 2 * CDF(margin/(sqrt(n1+n2)*beta)) -1
// implies
//
// margin = inversecdf((draw probability + 1)/2) * sqrt(n1+n2) * beta
// n1 and n2 are the number of players on each team
$margin = GaussianDistribution::inverseCumulativeTo(.5*($drawProbability + 1), 0, 1)*sqrt(1 + 1)*
$beta;
return $margin;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill;
require_once(dirname(__FILE__) . "/../GameInfo.php");
require_once(dirname(__FILE__) . "/../Guard.php");
require_once(dirname(__FILE__) . "/../ISupportPartialPlay.php");
require_once(dirname(__FILE__) . "/../ISupportPartialUpdate.php");
require_once(dirname(__FILE__) . "/../PartialPlay.php");
require_once(dirname(__FILE__) . "/../PlayersRange.php");
require_once(dirname(__FILE__) . "/../RankSorter.php");
require_once(dirname(__FILE__) . "/../SkillCalculator.php");
require_once(dirname(__FILE__) . "/../TeamsRange.php");
require_once(dirname(__FILE__) . "/../Numerics/BasicMath.php");
require_once(dirname(__FILE__) . "/../Numerics/Matrix.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraph.php");
use Moserware\Numerics\DiagonalMatrix;
use Moserware\Numerics\Matrix;
use Moserware\Numerics\Vector;
use Moserware\Skills\GameInfo;
use Moserware\Skills\Guard;
use Moserware\Skills\ISupportPartialPlay;
use Moserware\Skills\ISupportPartialUpdate;
use Moserware\Skills\PartialPlay;
use Moserware\Skills\PlayersRange;
use Moserware\Skills\RankSorter;
use Moserware\Skills\SkillCalculator;
use Moserware\Skills\SkillCalculatorSupportedOptions;
use Moserware\Skills\TeamsRange;
/**
* Calculates TrueSkill using a full factor graph.
*/
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;
$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(self::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(
self::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->getAllRatings() 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);
$currentColumn = 0;
for ($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
$playerAssignments[$currentColumn] = ($totalPreviousPlayers > 0) ? \array_fill(0, $totalPreviousPlayers, 0) : array();
foreach ($currentTeam->getAllPlayers() as $currentPlayer)
{
$playerAssignments[$currentColumn][] = PartialPlay::getPartialPlayPercentage($currentPlayer);
// indicates the player is on the team
$totalPreviousPlayers++;
}
$rowsRemaining = $totalPlayers - $totalPreviousPlayers;
$nextTeam = $teamAssignmentsList[$i + 1];
foreach ($nextTeam->getAllPlayers() as $nextTeamPlayer)
{
// Add a -1 * playing time to represent the difference
$playerAssignments[$currentColumn][] = -1 * PartialPlay::getPartialPlayPercentage($nextTeamPlayer);
$rowsRemaining--;
}
for ($ixAdditionalRow = 0; $ixAdditionalRow < $rowsRemaining; $ixAdditionalRow++)
{
// Pad with zeros
$playerAssignments[$currentColumn][] = 0;
}
$currentColumn++;
}
$playerTeamAssignmentsMatrix = Matrix::fromColumnValues($totalPlayers, $teamAssignmentsListCount - 1, $playerAssignments);
return $playerTeamAssignmentsMatrix;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Factor.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Message.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/GaussianDistribution.php");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\FactorGraphs\Factor;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
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);
$variable->setValue(GaussianDistribution::multiply($marginal, $messageValue));
return $logZ;
}
public function &createVariableToMessageBinding(Variable &$variable)
{
$newDistribution = GaussianDistribution::fromPrecisionMean(0, 0);
$binding = &parent::createVariableToMessageBindingWithMessage($variable,
new Message(
$newDistribution,
sprintf("message from %s to %s", $this, $variable)));
return $binding;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Message.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/GaussianDistribution.php");
require_once(dirname(__FILE__) . "/../TruncatedGaussianCorrectionFunctions.php");
require_once(dirname(__FILE__) . "/GaussianFactor.php");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\TrueSkill\TruncatedGaussianCorrectionFunctions;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
/**
* Factor representing a team difference that has exceeded the draw margin.
*
* See the accompanying math paper for more details.
*/
class GaussianGreaterThanFactor extends GaussianFactor
{
private $_epsilon;
public function __construct($epsilon, Variable &$variable)
{
parent::__construct(\sprintf("%s > %.2f", $variable, $epsilon));
$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();
$denom = 1.0 - TruncatedGaussianCorrectionFunctions::wExceedsMargin($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);
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Message.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/GaussianDistribution.php");
require_once(dirname(__FILE__) . "/GaussianFactor.php");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
/**
* Connects two variables and adds uncertainty.
*
* See the accompanying math paper for more details.
*/
class GaussianLikelihoodFactor extends GaussianFactor
{
private $_precision;
public function __construct($betaSquared, Variable &$variable1, Variable &$variable2)
{
parent::__construct(sprintf("Likelihood of %s going to %s", $variable2, $variable1));
$this->_precision = 1.0/$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();
}
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Message.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/GaussianDistribution.php");
require_once(dirname(__FILE__) . "/GaussianFactor.php");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
/**
* Supplies the factor graph with prior information.
*
* See the accompanying math paper for more details.
*/
class GaussianPriorFactor extends GaussianFactor
{
private $_newMessage;
public function __construct($mean, $variance, Variable &$variable)
{
parent::__construct(sprintf("Prior value going to %s", $variable));
$this->_newMessage = new GaussianDistribution($mean, sqrt($variance));
$newMessage = new Message(GaussianDistribution::fromPrecisionMean(0, 0),
sprintf("message from %s to %s", $this, $variable));
$this->createVariableToMessageBindingWithMessage($variable, $newMessage);
}
protected function updateMessageVariable(Message &$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);
$newMessage = &$this->_newMessage;
$message->setValue($newMessage);
return GaussianDistribution::subtract($oldMarginal, $newMarginal);
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/../../Guard.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Message.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/GaussianDistribution.php");
require_once(dirname(__FILE__) . "/../../Numerics/BasicMath.php");
require_once(dirname(__FILE__) . "/GaussianFactor.php");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\Guard;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
/**
* Factor that sums together multiple Gaussians.
*
* See the accompanying math paper for more details.s
*/
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(self::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
$variableWeightsLength = count($variableWeights);
$this->_weights[0] = \array_fill(0, count($variableWeights), 0);
for($i = 0; $i < $variableWeightsLength; $i++)
{
$weight = &$variableWeights[$i];
$this->_weights[0][$i] = $weight;
$this->_weightsSquared[0][$i] = square($weight);
}
$variablesToSumLength = count($variablesToSum);
// 0..n-1
$this->_variableIndexOrdersForWeights[0] = array();
for($i = 0; $i < ($variablesToSumLength + 1); $i++)
{
$this->_variableIndexOrdersForWeights[0][] = $i;
}
$variableWeightsLength = count($variableWeights);
// 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++)
{
$currentWeights = \array_fill(0, $variableWeightsLength, 0);
$variableIndices = \array_fill(0, $variableWeightsLength + 1, 0);
$variableIndices[0] = $weightsIndex;
$currentWeightsSquared = \array_fill(0, $variableWeightsLength, 0);
// 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 < $variableWeightsLength;
$currentWeightSourceIndex++)
{
if ($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] = square($finalWeight);
$variableIndices[count($variableWeights)] = 0;
$this->_variableIndexOrdersForWeights[] = $variableIndices;
$this->_weights[$weightsIndex] = $currentWeights;
$this->_weightsSquared[$weightsIndex] = $currentWeightsSquared;
}
$this->createVariableToMessageBinding($sumVariable);
foreach ($variablesToSum as &$currentVariable)
{
$localCurrentVariable = &$currentVariable;
$this->createVariableToMessageBinding($localCurrentVariable);
}
}
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
$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 $this->updateHelper($this->_weights[$messageIndex],
$this->_weightsSquared[$messageIndex],
$updatedMessages,
$updatedVariables);
}
private static function createName($sumVariable, $variablesToSum, $weights)
{
// TODO: Perf? Use PHP equivalent of StringBuilder? implode on arrays?
$result = (string)$sumVariable;
$result .= ' = ';
$totalVars = count($variablesToSum);
for($i = 0; $i < $totalVars; $i++)
{
$isFirst = ($i == 0);
if($isFirst && ($weights[$i] < 0))
{
$result .= '-';
}
$absValue = sprintf("%.2f", \abs($weights[$i])); // 0.00?
$result .= $absValue;
$result .= "*[";
$result .= (string)$variablesToSum[$i];
$result .= ']';
$isLast = ($i == ($totalVars - 1));
if(!$isLast)
{
if($weights[$i + 1] >= 0)
{
$result .= ' + ';
}
else
{
$result .= ' - ';
}
}
}
return $result;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/../TruncatedGaussianCorrectionFunctions.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Message.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/GaussianDistribution.php");
require_once(dirname(__FILE__) . "/GaussianFactor.php");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\TrueSkill\TruncatedGaussianCorrectionFunctions;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
/**
* Factor representing a team difference that has not exceeded the draw margin.
*
* See the accompanying math paper for more details.
*/
class GaussianWithinFactor extends GaussianFactor
{
private $_epsilon;
public function __construct($epsilon, Variable &$variable)
{
parent::__construct(sprintf("%s <= %.2f", $variable, $epsilon));
$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 updateMessageVariable(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);
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Schedule.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraphLayer.php");
require_once(dirname(__FILE__) . "/TeamPerformancesToTeamPerformanceDifferencesLayer.php");
require_once(dirname(__FILE__) . "/TeamDifferencesComparisonLayer.php");
use Moserware\Skills\FactorGraphs\ScheduleLoop;
use Moserware\Skills\FactorGraphs\ScheduleSequence;
use Moserware\Skills\FactorGraphs\ScheduleStep;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
// 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 &getLocalFactors()
{
$localFactors =
\array_merge($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors(),
$this->_TeamDifferencesComparisonLayer->getLocalFactors());
return $localFactors;
}
public function buildLayer()
{
$inputVariablesGroups = &$this->getInputVariablesGroups();
$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->setInputVariablesGroups($inputVariablesGroups);
$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->buildLayer();
$teamDifferencesOutputVariablesGroups = &$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getOutputVariablesGroups();
$this->_TeamDifferencesComparisonLayer->setInputVariablesGroups($teamDifferencesOutputVariablesGroups);
$this->_TeamDifferencesComparisonLayer->buildLayer();
}
public function createPriorSchedule()
{
switch (count($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;
$localFactors = &$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors();
$firstDifferencesFactor = &$localFactors[0];
$lastDifferencesFactor = &$localFactors[$totalTeamDifferences - 1];
$innerSchedule = new ScheduleSequence(
"inner schedule",
array(
$loop,
new ScheduleStep(
"teamPerformanceToPerformanceDifferenceFactors[0] @ 1",
$firstDifferencesFactor, 1),
new ScheduleStep(
sprintf("teamPerformanceToPerformanceDifferenceFactors[teamTeamDifferences = %d - 1] @ 2", $totalTeamDifferences),
$lastDifferencesFactor, 2)
)
);
return $innerSchedule;
}
private function createTwoTeamInnerPriorLoopSchedule()
{
$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors = &$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors();
$teamDifferencesComparisonLayerLocalFactors = &$this->_TeamDifferencesComparisonLayer->getLocalFactors();
$firstPerfToTeamDiff = &$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors[0];
$firstTeamDiffComparison = &$teamDifferencesComparisonLayerLocalFactors[0];
$itemsToSequence = array(
new ScheduleStep(
"send team perf to perf differences",
$firstPerfToTeamDiff,
0),
new ScheduleStep(
"send to greater than or within factor",
$firstTeamDiffComparison,
0)
);
return $this->scheduleSequence(
$itemsToSequence,
"loop of just two teams inner sequence");
}
private function createMultipleTeamInnerPriorLoopSchedule()
{
$totalTeamDifferences = count($this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors());
$forwardScheduleList = array();
for ($i = 0; $i < $totalTeamDifferences - 1; $i++)
{
$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors = &$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors();
$teamDifferencesComparisonLayerLocalFactors = &$this->_TeamDifferencesComparisonLayer->getLocalFactors();
$currentTeamPerfToTeamPerfDiff = &$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors[$i];
$currentTeamDiffComparison = &$teamDifferencesComparisonLayerLocalFactors[$i];
$currentForwardSchedulePiece =
$this->scheduleSequence(
array(
new ScheduleStep(
sprintf("team perf to perf diff %d", $i),
$currentTeamPerfToTeamPerfDiff, 0),
new ScheduleStep(
sprintf("greater than or within result factor %d", $i),
$currentTeamDiffComparison, 0),
new ScheduleStep(
sprintf("team perf to perf diff factors [%d], 2", $i),
$currentTeamPerfToTeamPerfDiff, 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++)
{
$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors = &$this->_TeamPerformancesToTeamPerformanceDifferencesLayer->getLocalFactors();
$teamDifferencesComparisonLayerLocalFactors = &$this->_TeamDifferencesComparisonLayer->getLocalFactors();
$differencesFactor = &$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors[$totalTeamDifferences - 1 - $i];
$comparisonFactor = &$teamDifferencesComparisonLayerLocalFactors[$totalTeamDifferences - 1 - $i];
$performancesToDifferencesFactor = &$teamPerformancesToTeamPerformanceDifferencesLayerLocalFactors[$totalTeamDifferences - 1 - $i];
$currentBackwardSchedulePiece = new ScheduleSequence(
"current backward schedule piece",
array(
new ScheduleStep(
sprintf("teamPerformanceToPerformanceDifferenceFactors[totalTeamDifferences - 1 - %d] @ 0", $i),
$differencesFactor, 0),
new ScheduleStep(
sprintf("greaterThanOrWithinResultFactors[totalTeamDifferences - 1 - %d] @ 0", $i),
$comparisonFactor, 0),
new ScheduleStep(
sprintf("teamPerformanceToPerformanceDifferenceFactors[totalTeamDifferences - 1 - %d] @ 1", $i),
$performancesToDifferencesFactor, 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;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../../PartialPlay.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Schedule.php");
require_once(dirname(__FILE__) . "/../Factors/GaussianWeightedSumFactor.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraphLayer.php");
require_once(dirname(__FILE__) . "/TeamPerformancesToTeamPerformanceDifferencesLayer.php");
require_once(dirname(__FILE__) . "/TeamDifferencesComparisonLayer.php");
use Moserware\Skills\PartialPlay;
use Moserware\Skills\FactorGraphs\ScheduleLoop;
use Moserware\Skills\FactorGraphs\ScheduleSequence;
use Moserware\Skills\FactorGraphs\ScheduleStep;
use Moserware\Skills\TrueSkill\Factors\GaussianWeightedSumFactor;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
class PlayerPerformancesToTeamPerformancesLayer extends TrueSkillFactorGraphLayer
{
public function __construct(TrueSkillFactorGraph &$parentGraph)
{
parent::__construct($parentGraph);
}
public function buildLayer()
{
$inputVariablesGroups = &$this->getInputVariablesGroups();
foreach ($inputVariablesGroups as &$currentTeam)
{
$localCurrentTeam = &$currentTeam;
$teamPerformance = &$this->createOutputVariable($localCurrentTeam);
$newSumFactor = $this->createPlayerToTeamSumFactor($localCurrentTeam, $teamPerformance);
$this->addLayerFactor($newSumFactor);
// REVIEW: Does it make sense to have groups of one?
$outputVariablesGroups = &$this->getOutputVariablesGroups();
$outputVariablesGroups[] = array($teamPerformance);
}
}
public function createPriorSchedule()
{
$localFactors = &$this->getLocalFactors();
$sequence = &$this->scheduleSequence(
array_map(
function($weightedSumFactor)
{
return new ScheduleStep("Perf to Team Perf Step", $weightedSumFactor, 0);
},
$localFactors),
"all player perf to team perf schedule");
return $sequence;
}
protected function createPlayerToTeamSumFactor(&$teamMembers, &$sumVariable)
{
$weights = array_map(
function($v)
{
$player = &$v->getKey();
return PartialPlay::getPartialPlayPercentage($player);
},
$teamMembers);
return new GaussianWeightedSumFactor(
$sumVariable,
$teamMembers,
$weights);
}
public function createPosteriorSchedule()
{
$allFactors = array();
$localFactors = &$this->getLocalFactors();
foreach($localFactors as &$currentFactor)
{
$localCurrentFactor = &$currentFactor;
$numberOfMessages = $localCurrentFactor->getNumberOfMessages();
for($currentIteration = 1; $currentIteration < $numberOfMessages; $currentIteration++)
{
$allFactors[] = new ScheduleStep("team sum perf @" . $currentIteration,
$localCurrentFactor, $currentIteration);
}
}
return $this->scheduleSequence($allFactors, "all of the team's sum iterations");
}
private function &createOutputVariable(&$team)
{
$memberNames = \array_map(function ($currentPlayer)
{
return (string)($currentPlayer->getKey());
},
$team);
$teamMemberNames = \join(", ", $memberNames);
$outputVariable = &$this->getParentFactorGraph()->getVariableFactory()->createBasicVariable("Team[" . $teamMemberNames . "]'s performance");
return $outputVariable;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../../Rating.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Schedule.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/BasicMath.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
require_once(dirname(__FILE__) . "/../Factors/GaussianPriorFactor.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraphLayer.php");
use Moserware\Skills\Rating;
use Moserware\Skills\FactorGraphs\ScheduleLoop;
use Moserware\Skills\FactorGraphs\ScheduleSequence;
use Moserware\Skills\FactorGraphs\ScheduleStep;
use Moserware\Skills\FactorGraphs\Variable;
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
use Moserware\Skills\TrueSkill\Factors\GaussianPriorFactor;
// We intentionally have no Posterior schedule since the only purpose here is to
// start the process.
class PlayerPriorValuesToSkillsLayer extends TrueSkillFactorGraphLayer
{
private $_teams;
public function __construct(TrueSkillFactorGraph &$parentGraph, array &$teams)
{
parent::__construct($parentGraph);
$this->_teams = $teams;
}
public function buildLayer()
{
$teams = &$this->_teams;
foreach ($teams as &$currentTeam)
{
$localCurrentTeam = &$currentTeam;
$currentTeamSkills = array();
$currentTeamAllPlayers = $localCurrentTeam->getAllPlayers();
foreach ($currentTeamAllPlayers as &$currentTeamPlayer)
{
$localCurrentTeamPlayer = &$currentTeamPlayer;
$currentTeamPlayerRating = $currentTeam->getRating($localCurrentTeamPlayer);
$playerSkill = &$this->createSkillOutputVariable($localCurrentTeamPlayer);
$priorFactor = &$this->createPriorFactor($localCurrentTeamPlayer, $currentTeamPlayerRating, $playerSkill);
$this->addLayerFactor($priorFactor);
$currentTeamSkills[] = $playerSkill;
}
$outputVariablesGroups = &$this->getOutputVariablesGroups();
$outputVariablesGroups[] = $currentTeamSkills;
}
}
public function createPriorSchedule()
{
$localFactors = &$this->getLocalFactors();
return $this->scheduleSequence(
array_map(
function(&$prior)
{
return new ScheduleStep("Prior to Skill Step", $prior, 0);
},
$localFactors),
"All priors");
}
private function createPriorFactor(&$player, Rating &$priorRating, Variable &$skillsVariable)
{
return new GaussianPriorFactor($priorRating->getMean(),
square($priorRating->getStandardDeviation()) +
square($this->getParentFactorGraph()->getGameInfo()->getDynamicsFactor()),
$skillsVariable);
}
private function &createSkillOutputVariable(&$key)
{
$parentFactorGraph = &$this->getParentFactorGraph();
$variableFactory = &$parentFactorGraph->getVariableFactory();
$skillOutputVariable = &$variableFactory->createKeyedVariable($key, $key . "'s skill");
return $skillOutputVariable;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Schedule.php");
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../../Numerics/BasicMath.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
require_once(dirname(__FILE__) . "/../Factors/GaussianLikelihoodFactor.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraphLayer.php");
use Moserware\Skills\FactorGraphs\ScheduleStep;
use Moserware\Skills\FactorGraphs\KeyedVariable;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
use Moserware\Skills\TrueSkill\Factors\GaussianLikelihoodFactor;
class PlayerSkillsToPerformancesLayer extends TrueSkillFactorGraphLayer
{
public function __construct(TrueSkillFactorGraph &$parentGraph)
{
parent::__construct($parentGraph);
}
public function buildLayer()
{
$inputVariablesGroups = &$this->getInputVariablesGroups();
$outputVariablesGroups = &$this->getOutputVariablesGroups();
foreach ($inputVariablesGroups as &$currentTeam)
{
$currentTeamPlayerPerformances = array();
foreach ($currentTeam as &$playerSkillVariable)
{
$localPlayerSkillVariable = &$playerSkillVariable;
$currentPlayer = &$localPlayerSkillVariable->getKey();
$playerPerformance = &$this->createOutputVariable($currentPlayer);
$newLikelihoodFactor = $this->createLikelihood($localPlayerSkillVariable, $playerPerformance);
$this->addLayerFactor($newLikelihoodFactor);
$currentTeamPlayerPerformances[] = $playerPerformance;
}
$outputVariablesGroups[] = $currentTeamPlayerPerformances;
}
}
private function createLikelihood(KeyedVariable &$playerSkill, KeyedVariable &$playerPerformance)
{
return new GaussianLikelihoodFactor(square($this->getParentFactorGraph()->getGameInfo()->getBeta()), $playerPerformance, $playerSkill);
}
private function &createOutputVariable(&$key)
{
$outputVariable = &$this->getParentFactorGraph()->getVariableFactory()->createKeyedVariable($key, $key . "'s performance");
return $outputVariable;
}
public function createPriorSchedule()
{
$localFactors = &$this->getLocalFactors();
return $this->scheduleSequence(
array_map(
function($likelihood)
{
return new ScheduleStep("Skill to Perf step", $likelihood, 0);
},
$localFactors),
"All skill to performance sending");
}
public function createPosteriorSchedule()
{
$localFactors = &$this->getLocalFactors();
return $this->scheduleSequence(
array_map(
function($likelihood)
{
return new ScheduleStep("name", $likelihood, 1);
},
$localFactors),
"All skill to performance sending");
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../DrawMargin.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
require_once(dirname(__FILE__) . "/../Factors/GaussianGreaterThanFactor.php");
require_once(dirname(__FILE__) . "/../Factors/GaussianWithinFactor.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraphLayer.php");
use Moserware\Skills\TrueSkill\DrawMargin;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
use Moserware\Skills\TrueSkill\Factors\GaussianGreaterThanFactor;
use Moserware\Skills\TrueSkill\Factors\GaussianWithinFactor;
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);
}
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../../FactorGraphs/Variable.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
require_once(dirname(__FILE__) . "/../Factors/GaussianWeightedSumFactor.php");
require_once(dirname(__FILE__) . "/TrueSkillFactorGraphLayer.php");
use Moserware\Skills\FactorGraphs\Variable;
use Moserware\Skills\TrueSkill\DrawMargin;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
use Moserware\Skills\TrueSkill\Factors\GaussianWeightedSumFactor;
class TeamPerformancesToTeamPerformanceDifferencesLayer extends TrueSkillFactorGraphLayer
{
public function __construct(TrueSkillFactorGraph &$parentGraph)
{
parent::__construct($parentGraph);
}
public function buildLayer()
{
$inputVariablesGroups = &$this->getInputVariablesGroups();
$inputVariablesGroupsCount = count($inputVariablesGroups);
$outputVariablesGroup = &$this->getOutputVariablesGroups();
for ($i = 0; $i < $inputVariablesGroupsCount - 1; $i++)
{
$strongerTeam = &$inputVariablesGroups[$i][0];
$weakerTeam = &$inputVariablesGroups[$i + 1][0];
$currentDifference = &$this->createOutputVariable();
$newDifferencesFactor = $this->createTeamPerformanceToDifferenceFactor($strongerTeam, $weakerTeam, $currentDifference);
$this->addLayerFactor($newDifferencesFactor);
// REVIEW: Does it make sense to have groups of one?
$outputVariablesGroup[] = array($currentDifference);
}
}
private function createTeamPerformanceToDifferenceFactor(
Variable &$strongerTeam, Variable &$weakerTeam, Variable &$output)
{
$teams = array($strongerTeam, $weakerTeam);
$weights = array(1.0, -1.0);
return new GaussianWeightedSumFactor($output, $teams, $weights);
}
private function &createOutputVariable()
{
$outputVariable = &$this->getParentFactorGraph()->getVariableFactory()->createBasicVariable("Team performance difference");
return $outputVariable;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill\Layers;
require_once(dirname(__FILE__) . "/../../FactorGraphs/FactorGraphLayer.php");
require_once(dirname(__FILE__) . "/../TrueSkillFactorGraph.php");
use Moserware\Skills\FactorGraphs\FactorGraphLayer;
use Moserware\Skills\TrueSkill\TrueSkillFactorGraph;
abstract class TrueSkillFactorGraphLayer extends FactorGraphLayer
{
public function __construct(TrueSkillFactorGraph &$parentGraph)
{
parent::__construct($parentGraph);
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill;
require_once(dirname(__FILE__) . '/../GameInfo.php');
require_once(dirname(__FILE__) . '/../Rating.php');
require_once(dirname(__FILE__) . '/../RatingContainer.php');
require_once(dirname(__FILE__) . '/../FactorGraphs/FactorGraph.php');
require_once(dirname(__FILE__) . '/../FactorGraphs/FactorList.php');
require_once(dirname(__FILE__) . '/../FactorGraphs/Schedule.php');
require_once(dirname(__FILE__) . '/../FactorGraphs/VariableFactory.php');
require_once(dirname(__FILE__) . '/../Numerics/GaussianDistribution.php');
require_once(dirname(__FILE__) . '/Layers/IteratedTeamDifferencesInnerLayer.php');
require_once(dirname(__FILE__) . '/Layers/PlayerPerformancesToTeamPerformancesLayer.php');
require_once(dirname(__FILE__) . '/Layers/PlayerPriorValuesToSkillsLayer.php');
require_once(dirname(__FILE__) . '/Layers/PlayerSkillsToPerformancesLayer.php');
require_once(dirname(__FILE__) . '/Layers/TeamDifferencesComparisonLayer.php');
require_once(dirname(__FILE__) . '/Layers/TeamPerformancesToTeamPerformanceDifferencesLayer.php');
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\GameInfo;
use Moserware\Skills\Rating;
use Moserware\Skills\RatingContainer;
use Moserware\Skills\FactorGraphs\FactorGraph;
use Moserware\Skills\FactorGraphs\FactorList;
use Moserware\Skills\FactorGraphs\ScheduleSequence;
use Moserware\Skills\FactorGraphs\VariableFactory;
use Moserware\Skills\TrueSkill\Layers\IteratedTeamDifferencesInnerLayer;
use Moserware\Skills\TrueSkill\Layers\PlayerPerformancesToTeamPerformancesLayer;
use Moserware\Skills\TrueSkill\Layers\PlayerPriorValuesToSkillsLayer;
use Moserware\Skills\TrueSkill\Layers\PlayerSkillsToPerformancesLayer;
use Moserware\Skills\TrueSkill\Layers\TeamDifferencesComparisonLayer;
use Moserware\Skills\TrueSkill\Layers\TeamPerformancesToTeamPerformanceDifferencesLayer;
class TrueSkillFactorGraph extends FactorGraph
{
private $_gameInfo;
private $_layers;
private $_priorLayer;
public function __construct(GameInfo &$gameInfo, array &$teams, array $teamRanks)
{
$this->_priorLayer = new PlayerPriorValuesToSkillsLayer($this, $teams);
$this->_gameInfo = $gameInfo;
$newFactory = new VariableFactory(
function()
{
return GaussianDistribution::fromPrecisionMean(0, 0);
});
$this->setVariableFactory($newFactory);
$this->_layers = array(
$this->_priorLayer,
new PlayerSkillsToPerformancesLayer($this),
new PlayerPerformancesToTeamPerformancesLayer($this),
new IteratedTeamDifferencesInnerLayer(
$this,
new TeamPerformancesToTeamPerformanceDifferencesLayer($this),
new TeamDifferencesComparisonLayer($this, $teamRanks))
);
}
public function getGameInfo()
{
return $this->_gameInfo;
}
public function buildGraph()
{
$lastOutput = null;
$layers = &$this->_layers;
foreach ($layers as &$currentLayer)
{
if ($lastOutput != null)
{
$currentLayer->setInputVariablesGroups($lastOutput);
}
$currentLayer->buildLayer();
$lastOutput = &$currentLayer->getOutputVariablesGroups();
}
}
public function runSchedule()
{
$fullSchedule = $this->createFullSchedule();
$fullScheduleDelta = $fullSchedule->visit();
}
public function getProbabilityOfRanking()
{
$factorList = new FactorList();
$layers = &$this->_layers;
foreach ($layers as &$currentLayer)
{
$localFactors = &$currentLayer->getLocalFactors();
foreach ($localFactors as &$currentFactor)
{
$localCurrentFactor = &$currentFactor;
$factorList->addFactor($localCurrentFactor);
}
}
$logZ = $factorList->getLogNormalization();
return exp($logZ);
}
private function createFullSchedule()
{
$fullSchedule = array();
$layers = &$this->_layers;
foreach ($layers as &$currentLayer)
{
$currentPriorSchedule = $currentLayer->createPriorSchedule();
if ($currentPriorSchedule != null)
{
$fullSchedule[] = $currentPriorSchedule;
}
}
$allLayersReverse = \array_reverse($this->_layers);
foreach ($allLayersReverse as &$currentLayer)
{
$currentPosteriorSchedule = $currentLayer->createPosteriorSchedule();
if ($currentPosteriorSchedule != null)
{
$fullSchedule[] = $currentPosteriorSchedule;
}
}
return new ScheduleSequence("Full schedule", $fullSchedule);
}
public function getUpdatedRatings()
{
$result = new RatingContainer();
$priorLayerOutputVariablesGroups = &$this->_priorLayer->getOutputVariablesGroups();
foreach ($priorLayerOutputVariablesGroups as &$currentTeam)
{
foreach ($currentTeam as &$currentPlayer)
{
$localCurrentPlayer = &$currentPlayer->getKey();
$newRating = new Rating($currentPlayer->getValue()->getMean(),
$currentPlayer->getValue()->getStandardDeviation());
$result->setRating($localCurrentPlayer, $newRating);
}
}
return $result;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill;
require_once(dirname(__FILE__) . '/../Numerics/GaussianDistribution.php');
use Moserware\Numerics\GaussianDistribution;
class TruncatedGaussianCorrectionFunctions
{
// These functions from the bottom of page 4 of the TrueSkill paper.
/**
* The "V" function where the team performance difference is greater than the draw margin.
*
* In the reference F# implementation, this is referred to as "the additive
* correction of a single-sided truncated Gaussian with unit variance."
*
* @param number $drawMargin In the paper, it's referred to as just "ε".
*/
public static function vExceedsMarginScaled($teamPerformanceDifference, $drawMargin, $c)
{
return self::vExceedsMargin($teamPerformanceDifference/$c, $drawMargin/$c);
}
public static function vExceedsMargin($teamPerformanceDifference, $drawMargin)
{
$denominator = GaussianDistribution::cumulativeTo($teamPerformanceDifference - $drawMargin);
if ($denominator < 2.222758749e-162)
{
return -$teamPerformanceDifference + $drawMargin;
}
return GaussianDistribution::at($teamPerformanceDifference - $drawMargin)/$denominator;
}
/**
* The "W" function where the team performance difference is greater than the draw margin.
*
* In the reference F# implementation, this is referred to as "the multiplicative
* correction of a single-sided truncated Gaussian with unit variance."
*/
public static function wExceedsMarginScaled($teamPerformanceDifference, $drawMargin, $c)
{
return self::wExceedsMargin($teamPerformanceDifference/$c, $drawMargin/$c);
}
public static function wExceedsMargin($teamPerformanceDifference, $drawMargin)
{
$denominator = GaussianDistribution::cumulativeTo($teamPerformanceDifference - $drawMargin);
if ($denominator < 2.222758749e-162)
{
if ($teamPerformanceDifference < 0.0)
{
return 1.0;
}
return 0.0;
}
$vWin = self::vExceedsMargin($teamPerformanceDifference, $drawMargin);
return $vWin*($vWin + $teamPerformanceDifference - $drawMargin);
}
// the additive correction of a double-sided truncated Gaussian with unit variance
public static function vWithinMarginScaled($teamPerformanceDifference, $drawMargin, $c)
{
return self::vWithinMargin($teamPerformanceDifference/$c, $drawMargin/$c);
}
// from F#:
public static function vWithinMargin($teamPerformanceDifference, $drawMargin)
{
$teamPerformanceDifferenceAbsoluteValue = abs($teamPerformanceDifference);
$denominator =
GaussianDistribution::cumulativeTo($drawMargin - $teamPerformanceDifferenceAbsoluteValue) -
GaussianDistribution::cumulativeTo(-$drawMargin - $teamPerformanceDifferenceAbsoluteValue);
if ($denominator < 2.222758749e-162)
{
if ($teamPerformanceDifference < 0.0)
{
return -$teamPerformanceDifference - $drawMargin;
}
return -$teamPerformanceDifference + $drawMargin;
}
$numerator = GaussianDistribution::at(-$drawMargin - $teamPerformanceDifferenceAbsoluteValue) -
GaussianDistribution::at($drawMargin - $teamPerformanceDifferenceAbsoluteValue);
if ($teamPerformanceDifference < 0.0)
{
return -$numerator/$denominator;
}
return $numerator/$denominator;
}
// the multiplicative correction of a double-sided truncated Gaussian with unit variance
public static function wWithinMarginScaled($teamPerformanceDifference, $drawMargin, $c)
{
return self::wWithinMargin($teamPerformanceDifference/$c, $drawMargin/$c);
}
// From F#:
public static function wWithinMargin($teamPerformanceDifference, $drawMargin)
{
$teamPerformanceDifferenceAbsoluteValue = abs($teamPerformanceDifference);
$denominator = GaussianDistribution::cumulativeTo($drawMargin - $teamPerformanceDifferenceAbsoluteValue)
-
GaussianDistribution::cumulativeTo(-$drawMargin - $teamPerformanceDifferenceAbsoluteValue);
if ($denominator < 2.222758749e-162)
{
return 1.0;
}
$vt = self::vWithinMargin($teamPerformanceDifferenceAbsoluteValue, $drawMargin);
return $vt*$vt +
(
($drawMargin - $teamPerformanceDifferenceAbsoluteValue)
*
GaussianDistribution::at(
$drawMargin - $teamPerformanceDifferenceAbsoluteValue)
- (-$drawMargin - $teamPerformanceDifferenceAbsoluteValue)
*
GaussianDistribution::at(-$drawMargin - $teamPerformanceDifferenceAbsoluteValue))/$denominator;
}
}
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<?php
namespace Moserware\Skills\TrueSkill;
require_once(dirname(__FILE__) . "/../GameInfo.php");
require_once(dirname(__FILE__) . "/../Guard.php");
require_once(dirname(__FILE__) . "/../PairwiseComparison.php");
require_once(dirname(__FILE__) . "/../RankSorter.php");
require_once(dirname(__FILE__) . "/../Rating.php");
require_once(dirname(__FILE__) . "/../RatingContainer.php");
require_once(dirname(__FILE__) . "/../SkillCalculator.php");
require_once(dirname(__FILE__) . "/../PlayersRange.php");
require_once(dirname(__FILE__) . "/../TeamsRange.php");
require_once(dirname(__FILE__) . "/../Numerics/BasicMath.php");
require_once(dirname(__FILE__) . "/DrawMargin.php");
require_once(dirname(__FILE__) . "/TruncatedGaussianCorrectionFunctions.php");
use Moserware\Skills\GameInfo;
use Moserware\Skills\Guard;
use Moserware\Skills\PairwiseComparison;
use Moserware\Skills\RankSorter;
use Moserware\Skills\Rating;
use Moserware\Skills\RatingContainer;
use Moserware\Skills\SkillCalculator;
use Moserware\Skills\SkillCalculatorSupportedOptions;
use Moserware\Skills\PlayersRange;
use Moserware\Skills\TeamsRange;
/**
* Calculates the new ratings for only two players.
*
* When you only have two players, a lot of the math simplifies. The main purpose of this class
* is to show the bare minimum of what a TrueSkill implementation should have.
*/
class TwoPlayerTrueSkillCalculator extends SkillCalculator
{
public function __construct()
{
parent::__construct(SkillCalculatorSupportedOptions::NONE, TeamsRange::exactly(2), PlayersRange::exactly(1));
}
public function calculateNewRatings(GameInfo &$gameInfo,
array $teams,
array $teamRanks)
{
// Basic argument checking
Guard::argumentNotNull($gameInfo, "gameInfo");
$this->validateTeamCountAndPlayersCountPerTeam($teams);
// Make sure things are in order
RankSorter::sort($teams, $teamRanks);
// Since we verified that each team has one player, we know the player is the first one
$winningTeamPlayers = $teams[0]->getAllPlayers();
$winner = $winningTeamPlayers[0];
$winnerPreviousRating = $teams[0]->getRating($winner);
$losingTeamPlayers = $teams[1]->getAllPlayers();
$loser = $losingTeamPlayers[0];
$loserPreviousRating = $teams[1]->getRating($loser);
$wasDraw = ($teamRanks[0] == $teamRanks[1]);
$results = new RatingContainer();
$results->setRating($winner, self::calculateNewRating($gameInfo,
$winnerPreviousRating,
$loserPreviousRating,
$wasDraw ? PairwiseComparison::DRAW
: PairwiseComparison::WIN));
$results->setRating($loser, self::calculateNewRating($gameInfo,
$loserPreviousRating,
$winnerPreviousRating,
$wasDraw ? PairwiseComparison::DRAW
: PairwiseComparison::LOSE));
// And we're done!
return $results;
}
private static function calculateNewRating(GameInfo $gameInfo, Rating $selfRating, Rating $opponentRating, $comparison)
{
$drawMargin = DrawMargin::getDrawMarginFromDrawProbability($gameInfo->getDrawProbability(),
$gameInfo->getBeta());
$c =
sqrt(
square($selfRating->getStandardDeviation())
+
square($opponentRating->getStandardDeviation())
+
2*square($gameInfo->getBeta()));
$winningMean = $selfRating->getMean();
$losingMean = $opponentRating->getMean();
switch ($comparison)
{
case PairwiseComparison::WIN:
case PairwiseComparison::DRAW:
// NOP
break;
case PairwiseComparison::LOSE:
$winningMean = $opponentRating->getMean();
$losingMean = $selfRating->getMean();
break;
}
$meanDelta = $winningMean - $losingMean;
if ($comparison != PairwiseComparison::DRAW)
{
// non-draw case
$v = TruncatedGaussianCorrectionFunctions::vExceedsMarginScaled($meanDelta, $drawMargin, $c);
$w = TruncatedGaussianCorrectionFunctions::wExceedsMarginScaled($meanDelta, $drawMargin, $c);
$rankMultiplier = (int) $comparison;
}
else
{
$v = TruncatedGaussianCorrectionFunctions::vWithinMarginScaled($meanDelta, $drawMargin, $c);
$w = TruncatedGaussianCorrectionFunctions::wWithinMarginScaled($meanDelta, $drawMargin, $c);
$rankMultiplier = 1;
}
$meanMultiplier = (square($selfRating->getStandardDeviation()) + square($gameInfo->getDynamicsFactor()))/$c;
$varianceWithDynamics = square($selfRating->getStandardDeviation()) + square($gameInfo->getDynamicsFactor());
$stdDevMultiplier = $varianceWithDynamics/square($c);
$newMean = $selfRating->getMean() + ($rankMultiplier*$meanMultiplier*$v);
$newStdDev = sqrt($varianceWithDynamics*(1 - $w*$stdDevMultiplier));
return new Rating($newMean, $newStdDev);
}
/**
* {@inheritdoc }
*/
public function calculateMatchQuality(GameInfo &$gameInfo, array &$teams)
{
Guard::argumentNotNull($gameInfo, "gameInfo");
$this->validateTeamCountAndPlayersCountPerTeam($teams);
$team1 = $teams[0];
$team2 = $teams[1];
$team1Ratings = $team1->getAllRatings();
$team2Ratings = $team2->getAllRatings();
$player1Rating = $team1Ratings[0];
$player2Rating = $team2Ratings[0];
// We just use equation 4.1 found on page 8 of the TrueSkill 2006 paper:
$betaSquared = square($gameInfo->getBeta());
$player1SigmaSquared = square($player1Rating->getStandardDeviation());
$player2SigmaSquared = square($player2Rating->getStandardDeviation());
// This is the square root part of the equation:
$sqrtPart =
sqrt(
(2*$betaSquared)
/
(2*$betaSquared + $player1SigmaSquared + $player2SigmaSquared));
// This is the exponent part of the equation:
$expPart =
exp(
(-1*square($player1Rating->getMean() - $player2Rating->getMean()))
/
(2*(2*$betaSquared + $player1SigmaSquared + $player2SigmaSquared)));
return $sqrtPart*$expPart;
}
}
?>

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<?php
namespace Moserware\Skills\TrueSkill;
require_once(dirname(__FILE__) . "/../GameInfo.php");
require_once(dirname(__FILE__) . "/../Guard.php");
require_once(dirname(__FILE__) . "/../PairwiseComparison.php");
require_once(dirname(__FILE__) . "/../RankSorter.php");
require_once(dirname(__FILE__) . "/../Rating.php");
require_once(dirname(__FILE__) . "/../RatingContainer.php");
require_once(dirname(__FILE__) . "/../SkillCalculator.php");
require_once(dirname(__FILE__) . "/../Team.php");
require_once(dirname(__FILE__) . "/../PlayersRange.php");
require_once(dirname(__FILE__) . "/../TeamsRange.php");
require_once(dirname(__FILE__) . "/../Numerics/BasicMath.php");
require_once(dirname(__FILE__) . "/DrawMargin.php");
require_once(dirname(__FILE__) . "/TruncatedGaussianCorrectionFunctions.php");
use Moserware\Skills\GameInfo;
use Moserware\Skills\Guard;
use Moserware\Skills\PairwiseComparison;
use Moserware\Skills\RankSorter;
use Moserware\Skills\Rating;
use Moserware\Skills\RatingContainer;
use Moserware\Skills\SkillCalculator;
use Moserware\Skills\SkillCalculatorSupportedOptions;
use Moserware\Skills\PlayersRange;
use Moserware\Skills\TeamsRange;
use Moserware\Skills\Team;
/**
* Calculates new ratings for only two teams where each team has 1 or more players.
*
* When you only have two teams, the math is still simple: no factor graphs are used yet.
*/
class TwoTeamTrueSkillCalculator extends SkillCalculator
{
public function __construct()
{
parent::__construct(SkillCalculatorSupportedOptions::NONE, TeamsRange::exactly(2), PlayersRange::atLeast(1));
}
public function calculateNewRatings(GameInfo &$gameInfo,
array $teams,
array $teamRanks)
{
Guard::argumentNotNull($gameInfo, "gameInfo");
$this->validateTeamCountAndPlayersCountPerTeam($teams);
RankSorter::sort($teams, $teamRanks);
$team1 = $teams[0];
$team2 = $teams[1];
$wasDraw = ($teamRanks[0] == $teamRanks[1]);
$results = new RatingContainer();
self::updatePlayerRatings($gameInfo,
$results,
$team1,
$team2,
$wasDraw ? PairwiseComparison::DRAW : PairwiseComparison::WIN);
self::updatePlayerRatings($gameInfo,
$results,
$team2,
$team1,
$wasDraw ? PairwiseComparison::DRAW : PairwiseComparison::LOSE);
return $results;
}
private static function updatePlayerRatings(GameInfo $gameInfo,
RatingContainer &$newPlayerRatings,
Team $selfTeam,
Team $otherTeam,
$selfToOtherTeamComparison)
{
$drawMargin = DrawMargin::getDrawMarginFromDrawProbability($gameInfo->getDrawProbability(),
$gameInfo->getBeta());
$betaSquared = square($gameInfo->getBeta());
$tauSquared = square($gameInfo->getDynamicsFactor());
$totalPlayers = $selfTeam->count() + $otherTeam->count();
$meanGetter =
function($currentRating)
{
return $currentRating->getMean();
};
$selfMeanSum = sum($selfTeam->getAllRatings(), $meanGetter);
$otherTeamMeanSum = sum($otherTeam->getAllRatings(), $meanGetter);
$varianceGetter =
function($currentRating)
{
return square($currentRating->getStandardDeviation());
};
$c = sqrt(
sum($selfTeam->getAllRatings(), $varianceGetter)
+
sum($otherTeam->getAllRatings(), $varianceGetter)
+
$totalPlayers*$betaSquared);
$winningMean = $selfMeanSum;
$losingMean = $otherTeamMeanSum;
switch ($selfToOtherTeamComparison)
{
case PairwiseComparison::WIN:
case PairwiseComparison::DRAW:
// NOP
break;
case PairwiseComparison::LOSE:
$winningMean = $otherTeamMeanSum;
$losingMean = $selfMeanSum;
break;
}
$meanDelta = $winningMean - $losingMean;
if ($selfToOtherTeamComparison != PairwiseComparison::DRAW)
{
// non-draw case
$v = TruncatedGaussianCorrectionFunctions::vExceedsMarginScaled($meanDelta, $drawMargin, $c);
$w = TruncatedGaussianCorrectionFunctions::wExceedsMarginScaled($meanDelta, $drawMargin, $c);
$rankMultiplier = (int) $selfToOtherTeamComparison;
}
else
{
// assume draw
$v = TruncatedGaussianCorrectionFunctions::vWithinMarginScaled($meanDelta, $drawMargin, $c);
$w = TruncatedGaussianCorrectionFunctions::wWithinMarginScaled($meanDelta, $drawMargin, $c);
$rankMultiplier = 1;
}
$selfTeamAllPlayers = &$selfTeam->getAllPlayers();
foreach ($selfTeamAllPlayers as &$selfTeamCurrentPlayer)
{
$localSelfTeamCurrentPlayer = &$selfTeamCurrentPlayer;
$previousPlayerRating = $selfTeam->getRating($localSelfTeamCurrentPlayer);
$meanMultiplier = (square($previousPlayerRating->getStandardDeviation()) + $tauSquared)/$c;
$stdDevMultiplier = (square($previousPlayerRating->getStandardDeviation()) + $tauSquared)/square($c);
$playerMeanDelta = ($rankMultiplier*$meanMultiplier*$v);
$newMean = $previousPlayerRating->getMean() + $playerMeanDelta;
$newStdDev =
sqrt((square($previousPlayerRating->getStandardDeviation()) + $tauSquared)*(1 - $w*$stdDevMultiplier));
$newPlayerRatings->setRating($localSelfTeamCurrentPlayer, new Rating($newMean, $newStdDev));
}
}
/**
* {@inheritdoc }
*/
public function calculateMatchQuality(GameInfo &$gameInfo,
array &$teams)
{
Guard::argumentNotNull($gameInfo, "gameInfo");
$this->validateTeamCountAndPlayersCountPerTeam($teams);
// We've verified that there's just two teams
$team1Ratings = $teams[0]->getAllRatings();
$team1Count = count($team1Ratings);
$team2Ratings = $teams[1]->getAllRatings();
$team2Count = count($team2Ratings);
$totalPlayers = $team1Count + $team2Count;
$betaSquared = square($gameInfo->getBeta());
$meanGetter =
function($currentRating)
{
return $currentRating->getMean();
};
$varianceGetter =
function($currentRating)
{
return square($currentRating->getStandardDeviation());
};
$team1MeanSum = sum($team1Ratings, $meanGetter);
$team1StdDevSquared = sum($team1Ratings, $varianceGetter);
$team2MeanSum = sum($team2Ratings, $meanGetter);
$team2SigmaSquared = sum($team2Ratings, $varianceGetter);
// This comes from equation 4.1 in the TrueSkill paper on page 8
// The equation was broken up into the part under the square root sign and
// the exponential part to make the code easier to read.
$sqrtPart
= sqrt(
($totalPlayers*$betaSquared)
/
($totalPlayers*$betaSquared + $team1StdDevSquared + $team2SigmaSquared)
);
$expPart
= exp(
(-1*square($team1MeanSum - $team2MeanSum))
/
(2*($totalPlayers*$betaSquared + $team1StdDevSquared + $team2SigmaSquared))
);
return $expPart*$sqrtPart;
}
}
?>