jct/trueskill
1
0
Fork 0
mirror of https://github.com/furyfire/trueskill.git synced 2025-04-19 20:34:28 +00:00
Code Issues Packages Projects Releases Wiki Activity

PHPMD reintroduced.

Browse Source
This commit is contained in:
Jens True
2024-07-04 09:38:03 +00:00
parent 5dc0c7058d
commit cf588f3fc2
28 changed files with 56692 additions and 165 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
src/TrueSkill/Factors/GaussianWeightedSumFactor.php
View File

@ -19,9 +19,9 @@ use DNW\Skills\Numerics\GaussianDistribution;
class GaussianWeightedSumFactor extends GaussianFactor
{
/**
* @var array<int[]> $variableIndexOrdersForWeights
* @var array<int[]> $varIndexOrdersForWeights
*/
private array $variableIndexOrdersForWeights = [];
private array $varIndexOrdersForWeights = [];
/**
* This following is used for convenience, for example, the first entry is [0, 1, 2]
@ -58,9 +58,9 @@ class GaussianWeightedSumFactor extends GaussianFactor
$variablesToSumLength = count($variablesToSum);
// 0..n-1
$this->variableIndexOrdersForWeights[0] = [];
$this->varIndexOrdersForWeights[0] = [];
for ($i = 0; $i < ($variablesToSumLength + 1); ++$i) {
$this->variableIndexOrdersForWeights[0][] = $i;
$this->varIndexOrdersForWeights[0][] = $i;
}
$variableWeightsLength = count($variableWeights);
@ -113,7 +113,7 @@ class GaussianWeightedSumFactor extends GaussianFactor
$currentWeights[$currentDestinationWeightIndex] = $finalWeight;
$currentWeightsSquared[$currentDestinationWeightIndex] = BasicMath::square($finalWeight);
$variableIndices[count($variableWeights)] = 0;
$this->variableIndexOrdersForWeights[] = $variableIndices;
$this->varIndexOrdersForWeights[] = $variableIndices;
$this->weights[$weightsIndex] = $currentWeights;
$this->weightsSquared[$weightsIndex] = $currentWeightsSquared;
@ -160,9 +160,7 @@ class GaussianWeightedSumFactor extends GaussianFactor
// 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);
@ -172,16 +170,11 @@ class GaussianWeightedSumFactor extends GaussianFactor
$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;
@ -214,7 +207,7 @@ class GaussianWeightedSumFactor extends GaussianFactor
$updatedMessages = [];
$updatedVariables = [];
$indicesToUse = $this->variableIndexOrdersForWeights[$messageIndex];
$indicesToUse = $this->varIndexOrdersForWeights[$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