mirror of
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84 lines
2.6 KiB
PHP
84 lines
2.6 KiB
PHP
<?php
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declare(strict_types=1);
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namespace DNW\Skills\TrueSkill\Factors;
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use DNW\Skills\FactorGraphs\Message;
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use DNW\Skills\FactorGraphs\Variable;
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use DNW\Skills\Numerics\GaussianDistribution;
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use DNW\Skills\TrueSkill\TruncatedGaussianCorrectionFunctions;
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/**
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* Factor representing a team difference that has exceeded the draw margin.
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*
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* See the accompanying math paper for more details.
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*/
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class GaussianGreaterThanFactor extends GaussianFactor
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{
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public function __construct(private readonly float $epsilon, Variable $variable)
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{
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parent::__construct('%s > %.2f');
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$this->createVariableToMessageBinding($variable);
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}
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public function getLogNormalization(): float
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{
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$vars = $this->getVariables();
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$marginal = $vars[0]->getValue();
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$messages = $this->getMessages();
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$message = $messages[0]->getValue();
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$messageFromVariable = GaussianDistribution::divide($marginal, $message);
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return -GaussianDistribution::logProductNormalization($messageFromVariable, $message)
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+
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log(
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GaussianDistribution::cumulativeTo(
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($messageFromVariable->getMean() - $this->epsilon) /
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$messageFromVariable->getStandardDeviation()
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)
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);
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}
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protected function updateMessageVariable(Message $message, Variable $variable): float
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{
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$oldMarginal = clone $variable->getValue();
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$oldMessage = clone $message->getValue();
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$messageFromVar = GaussianDistribution::divide($oldMarginal, $oldMessage);
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$c = $messageFromVar->getPrecision();
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$d = $messageFromVar->getPrecisionMean();
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$sqrtC = sqrt($c);
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$dOnSqrtC = $d / $sqrtC;
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$epsilsonTimesSqrtC = $this->epsilon * $sqrtC;
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$d = $messageFromVar->getPrecisionMean();
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$denom = 1.0 - TruncatedGaussianCorrectionFunctions::wExceedsMargin($dOnSqrtC, $epsilsonTimesSqrtC);
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$newPrecision = $c / $denom;
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$newPrecisionMean = ($d +
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$sqrtC *
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TruncatedGaussianCorrectionFunctions::vExceedsMargin($dOnSqrtC, $epsilsonTimesSqrtC)) / $denom;
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$newMarginal = GaussianDistribution::fromPrecisionMean($newPrecisionMean, $newPrecision);
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$newMessage = GaussianDistribution::divide(
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GaussianDistribution::multiply($oldMessage, $newMarginal),
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$oldMarginal
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);
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// Update the message and marginal
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$message->setValue($newMessage);
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$variable->setValue($newMarginal);
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// Return the difference in the new marginal
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return GaussianDistribution::subtract($newMarginal, $oldMarginal);
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}
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}
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