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Some reference updates and adding the needed array(...) scope to existing data for single team values

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This commit is contained in:
Jeff Moser
2010-09-25 22:40:56 -04:00
parent 8e9e2d0d86
commit 04c911742d
8 changed files with 51 additions and 47 deletions

4
PHPSkills/TrueSkill/Factors/GaussianFactor.php

@ -22,8 +22,8 @@ abstract class GaussianFactor extends Factor
/// 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();
$marginal = &$variable->getValue();
$messageValue = &$message->getValue();
$logZ = GaussianDistribution::logProductNormalization($marginal, $messageValue);
$variable->setValue($marginal*$messageValue);
return $logZ;

10
PHPSkills/TrueSkill/Factors/GaussianGreaterThanFactor.php

@ -22,17 +22,17 @@ class GaussianGreaterThanFactor extends GaussianFactor
public function __construct($epsilon, Variable &$variable)
{
parent::_construct("{0} > {1:0.000}");
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();
$vars = &$this->getVariables();
$marginal = &$vars[0]->getValue();
$messages = &$this->getMessages();
$message = &$messages[0]->getValue();
$messageFromVariable = GaussianDistribution::divide($marginal, $message);
return -GaussianDistribution::logProductNormalization($messageFromVariable, $message)
+

32
PHPSkills/TrueSkill/Factors/GaussianWeightedSumFactor.php

@ -2,14 +2,16 @@
namespace Moserware\Skills\TrueSkill\Factors;
require_once(dirname(__FILE__) . "/GaussianFactor.php");
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");
use Moserware\Numerics\GaussianDistribution;
use Moserware\Skills\Guard;
use Moserware\Skills\FactorGraphs\Message;
use Moserware\Skills\FactorGraphs\Variable;
@ -40,9 +42,9 @@ class GaussianWeightedSumFactor extends GaussianFactor
for($i = 0; $i < $variableWeightsLength; $i++)
{
$weight = $variableWeights[$i];
$weight = &$variableWeights[$i];
$this->_weights[0][$i] = $weight;
$this->_weightsSquared[0][$i] = $weight * $weight;
$this->_weightsSquared[0][$i] = square($weight);
}
$variablesToSumLength = count($variablesToSum);
@ -123,8 +125,8 @@ class GaussianWeightedSumFactor extends GaussianFactor
public function getLogNormalization()
{
$vars = $this->getVariables();
$messages = $this->getMessages();
$vars = &$this->getVariables();
$messages = &$this->getMessages();
$result = 0.0;
@ -132,7 +134,7 @@ class GaussianWeightedSumFactor extends GaussianFactor
$varCount = count($vars);
for ($i = 1; $i < $varCount; $i++)
{
$result += GaussianDistribution::logRatioNormalization($vars[i]->getValue(), $messages[i]->getValue());
$result += GaussianDistribution::logRatioNormalization($vars[$i]->getValue(), $messages[$i]->getValue());
}
return $result;
@ -145,7 +147,7 @@ class GaussianWeightedSumFactor extends GaussianFactor
// Potentially look at http://mathworld.wolfram.com/NormalSumDistribution.html for clues as
// to what it's doing
$messages = $this->getMessages();
$messages = &$this->getMessages();
$message0 = clone $messages[0]->getValue();
$marginal0 = clone $variables[0]->getValue();
@ -161,13 +163,13 @@ class GaussianWeightedSumFactor extends GaussianFactor
{
// These flow directly from the paper
$inverseOfNewPrecisionSum += $weightsSquared[i]/
$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();
$anotherInverseOfNewPrecisionSum += $weightsSquared[$i]/$diff->getPrecision();
$weightedMeanSum += $weights[i]
$weightedMeanSum += $weights[$i]
*
($variables[$i + 1]->getValue()->getPrecisionMean() - $messages[$i + 1]->getValue()->getPrecisionMean())
/
@ -199,21 +201,21 @@ class GaussianWeightedSumFactor extends GaussianFactor
public function updateMessageIndex($messageIndex)
{
$allMessages = $this->getMessages();
$allVariables = $this->getVariables();
$allMessages = &$this->getMessages();
$allVariables = &$this->getVariables();
Guard::argumentIsValidIndex($messageIndex, count($allMessages),"messageIndex");
Guard::argumentIsValidIndex($messageIndex, count($allMessages), "messageIndex");
$updatedMessages = array();
$updatedVariables = array();
$indicesToUse = $this->_variableIndexOrdersForWeights[$messageIndex];
$indicesToUse = &$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; $i++)
for ($i = 0; $i < $allMessagesCount; $i++)
{
$updatedMessages[] =$allMessages[$indicesToUse[$i]];
$updatedVariables[] = $allVariables[$indicesToUse[$i]];

8
PHPSkills/TrueSkill/Factors/GaussianWithinFactor.php

@ -28,11 +28,11 @@ class GaussianWithinFactor extends GaussianFactor
public function getLogNormalization()
{
$variables = $this->getVariables();
$marginal = $variables[0]->getValue();
$variables = &$this->getVariables();
$marginal = &$variables[0]->getValue();
$messages = $this->getMessages();
$message = $messages[0]->getValue();
$messages = &$this->getMessages();
$message = &$messages[0]->getValue();
$messageFromVariable = GaussianDistribution::divide($marginal, $message);
$mean = $messageFromVariable->getMean();
$std = $messageFromVariable->getStandardDeviation();