jct/trueskill
1
0
Fork 0
mirror of https://github.com/furyfire/trueskill.git synced 2025-01-16 01:47:39 +00:00
Code Issues Packages Projects Releases Wiki Activity

No more use of _ to mark private variables.

Browse Source
This commit is contained in:
Jens True
2023-08-01 14:02:12 +00:00
parent c8c126962d
commit f0aa9413e1
8 changed files with 87 additions and 94 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
src/FactorGraphs/FactorGraphLayer.php
View File

@ -4,26 +4,26 @@ namespace DNW\Skills\FactorGraphs;
abstract class FactorGraphLayer
{
private array $_localFactors = [];
private array $localFactors = [];
private array $_outputVariablesGroups = [];
private array $outputVariablesGroups = [];
private $_inputVariablesGroups = [];
private $inputVariablesGroups = [];
protected function __construct(private readonly FactorGraph $_parentFactorGraph)
protected function __construct(private readonly FactorGraph $parentFactorGraph)
{
}
protected function getInputVariablesGroups()
{
return $this->_inputVariablesGroups;
return $this->inputVariablesGroups;
}
// HACK
public function getParentFactorGraph()
{
return $this->_parentFactorGraph;
return $this->parentFactorGraph;
}
/**
@ -31,17 +31,17 @@ abstract class FactorGraphLayer
*/
public function &getOutputVariablesGroups(): array
{
return $this->_outputVariablesGroups;
return $this->outputVariablesGroups;
}
public function getLocalFactors(): array
{
return $this->_localFactors;
return $this->localFactors;
}
public function setInputVariablesGroups(array $value): void
{
$this->_inputVariablesGroups = $value;
$this->inputVariablesGroups = $value;
}
protected function scheduleSequence(array $itemsToSequence, string $name): ScheduleSequence
@ -51,7 +51,7 @@ abstract class FactorGraphLayer
protected function addLayerFactor(Factor $factor): void
{
$this->_localFactors[] = $factor;
$this->localFactors[] = $factor;
}
abstract public function buildLayer();

12
src/FactorGraphs/FactorList.php
View File

@ -7,21 +7,21 @@ namespace DNW\Skills\FactorGraphs;
*/
class FactorList
{
private array $_list = [];
private array $list = [];
public function getLogNormalization()
{
$list = $this->_list;
$list = $this->list;
foreach ($list as &$currentFactor) {
$currentFactor->resetMarginals();
}
$sumLogZ = 0.0;
$listCount = count($this->_list);
$listCount = count($this->list);
for ($i = 0; $i < $listCount; $i++) {
$f = $this->_list[$i];
$f = $this->list[$i];
$numberOfMessages = $f->getNumberOfMessages();
@ -41,12 +41,12 @@ class FactorList
public function count()
{
return count($this->_list);
return count($this->list);
}
public function addFactor(Factor $factor)
{
$this->_list[] = $factor;
$this->list[] = $factor;
return $factor;
}

84
src/Numerics/GaussianDistribution.php
View File

@ -12,65 +12,65 @@ class GaussianDistribution implements \Stringable
{
// precision and precisionMean are used because they make multiplying and dividing simpler
// (the the accompanying math paper for more details)
private $_precision;
private $precision;
private $_precisionMean;
private $precisionMean;
private $_variance;
private $variance;
public function __construct(private float $_mean = 0.0, private float $_standardDeviation = 1.0)
public function __construct(private float $mean = 0.0, private float $standardDeviation = 1.0)
{
$this->_variance = BasicMath::square($_standardDeviation);
$this->variance = BasicMath::square($standardDeviation);
if ($this->_variance != 0) {
$this->_precision = 1.0 / $this->_variance;
$this->_precisionMean = $this->_precision * $this->_mean;
if ($this->variance != 0) {
$this->precision = 1.0 / $this->variance;
$this->precisionMean = $this->precision * $this->mean;
} else {
$this->_precision = \INF;
$this->precision = \INF;
$this->_precisionMean = $this->_mean == 0 ? 0 : \INF;
$this->precisionMean = $this->mean == 0 ? 0 : \INF;
}
}
public function getMean(): float
{
return $this->_mean;
return $this->mean;
}
public function getVariance(): float
{
return $this->_variance;
return $this->variance;
}
public function getStandardDeviation(): float
{
return $this->_standardDeviation;
return $this->standardDeviation;
}
public function getPrecision(): float
{
return $this->_precision;
return $this->precision;
}
public function getPrecisionMean(): float
{
return $this->_precisionMean;
return $this->precisionMean;
}
public function getNormalizationConstant(): float
{
// Great derivation of this is at http://www.astro.psu.edu/~mce/A451_2/A451/downloads/notes0.pdf
return 1.0 / (sqrt(2 * M_PI) * $this->_standardDeviation);
return 1.0 / (sqrt(2 * M_PI) * $this->standardDeviation);
}
public function __clone()
{
$result = new GaussianDistribution();
$result->_mean = $this->_mean;
$result->_standardDeviation = $this->_standardDeviation;
$result->_variance = $this->_variance;
$result->_precision = $this->_precision;
$result->_precisionMean = $this->_precisionMean;
$result->mean = $this->mean;
$result->standardDeviation = $this->standardDeviation;
$result->variance = $this->variance;
$result->precision = $this->precision;
$result->precisionMean = $this->precisionMean;
return $result;
}
@ -78,17 +78,17 @@ class GaussianDistribution implements \Stringable
public static function fromPrecisionMean(float $precisionMean, float $precision): self
{
$result = new GaussianDistribution();
$result->_precision = $precision;
$result->_precisionMean = $precisionMean;
$result->precision = $precision;
$result->precisionMean = $precisionMean;
if ($precision != 0) {
$result->_variance = 1.0 / $precision;
$result->_standardDeviation = sqrt($result->_variance);
$result->_mean = $result->_precisionMean / $result->_precision;
$result->variance = 1.0 / $precision;
$result->standardDeviation = sqrt($result->variance);
$result->mean = $result->precisionMean / $result->precision;
} else {
$result->_variance = \INF;
$result->_standardDeviation = \INF;
$result->_mean = \NAN;
$result->variance = \INF;
$result->standardDeviation = \INF;
$result->mean = \NAN;
}
return $result;
@ -98,15 +98,15 @@ class GaussianDistribution implements \Stringable
// for multiplication, the precision mean ones are easier to write :)
public static function multiply(GaussianDistribution $left, GaussianDistribution $right): self
{
return GaussianDistribution::fromPrecisionMean($left->_precisionMean + $right->_precisionMean, $left->_precision + $right->_precision);
return GaussianDistribution::fromPrecisionMean($left->precisionMean + $right->precisionMean, $left->precision + $right->precision);
}
// Computes the absolute difference between two Gaussians
public static function absoluteDifference(GaussianDistribution $left, GaussianDistribution $right): float
{
return max(
abs($left->_precisionMean - $right->_precisionMean),
sqrt(abs($left->_precision - $right->_precision))
abs($left->precisionMean - $right->precisionMean),
sqrt(abs($left->precision - $right->precision))
);
}
@ -118,12 +118,12 @@ class GaussianDistribution implements \Stringable
public static function logProductNormalization(GaussianDistribution $left, GaussianDistribution $right): float
{
if (($left->_precision == 0) || ($right->_precision == 0)) {
if (($left->precision == 0) || ($right->precision == 0)) {
return 0;
}
$varianceSum = $left->_variance + $right->_variance;
$meanDifference = $left->_mean - $right->_mean;
$varianceSum = $left->variance + $right->variance;
$meanDifference = $left->mean - $right->mean;
$logSqrt2Pi = log(sqrt(2 * M_PI));
@ -133,23 +133,23 @@ class GaussianDistribution implements \Stringable
public static function divide(GaussianDistribution $numerator, GaussianDistribution $denominator): self
{
return GaussianDistribution::fromPrecisionMean(
$numerator->_precisionMean - $denominator->_precisionMean,
$numerator->_precision - $denominator->_precision
$numerator->precisionMean - $denominator->precisionMean,
$numerator->precision - $denominator->precision
);
}
public static function logRatioNormalization(GaussianDistribution $numerator, GaussianDistribution $denominator): float
{
if (($numerator->_precision == 0) || ($denominator->_precision == 0)) {
if (($numerator->precision == 0) || ($denominator->precision == 0)) {
return 0;
}
$varianceDifference = $denominator->_variance - $numerator->_variance;
$meanDifference = $numerator->_mean - $denominator->_mean;
$varianceDifference = $denominator->variance - $numerator->variance;
$meanDifference = $numerator->mean - $denominator->mean;
$logSqrt2Pi = log(sqrt(2 * M_PI));
return log($denominator->_variance) + $logSqrt2Pi - log($varianceDifference) / 2.0 +
return log($denominator->variance) + $logSqrt2Pi - log($varianceDifference) / 2.0 +
BasicMath::square($meanDifference) / (2 * $varianceDifference);
}
@ -258,6 +258,6 @@ class GaussianDistribution implements \Stringable
public function __toString(): string
{
return sprintf('mean=%.4f standardDeviation=%.4f', $this->_mean, $this->_standardDeviation);
return sprintf('mean=%.4f standardDeviation=%.4f', $this->mean, $this->standardDeviation);
}
}

15
src/Numerics/Range.php
View File

@ -9,28 +9,21 @@ use Exception;
class Range
{
private int $_min;
private int $_max;
public function __construct(int $min, int $max)
public function __construct(private int $min, private int $max)
{
if ($min > $max) {
throw new Exception('min > max');
}
$this->_min = $min;
$this->_max = $max;
}
public function getMin(): int
{
return $this->_min;
return $this->min;
}
public function getMax(): int
{
return $this->_max;
return $this->max;
}
protected static function create(int $min, int $max): self
@ -57,6 +50,6 @@ class Range
public function isInRange(int $value): bool
{
return ($this->_min <= $value) && ($value <= $this->_max);
return ($this->min <= $value) && ($value <= $this->max);
}
}

24
src/Player.php
View File

@ -7,31 +7,31 @@ namespace DNW\Skills;
*/
class Player implements ISupportPartialPlay, ISupportPartialUpdate, \Stringable
{
final const DEFAULT_PARTIAL_PLAY_PERCENTAGE = 1.0; // = 100% play time
private const DEFAULT_PARTIAL_PLAY_PERCENTAGE = 1.0; // = 100% play time
final const DEFAULT_PARTIAL_UPDATE_PERCENTAGE = 1.0;
private const DEFAULT_PARTIAL_UPDATE_PERCENTAGE = 1.0;
private $_PartialPlayPercentage;
private $PartialPlayPercentage;
private $_PartialUpdatePercentage;
private $PartialUpdatePercentage;
/**
* Constructs a player.
*
* @param mixed $_Id The identifier for the player, such as a name.
* @param mixed $Id The identifier for the player, such as a name.
* @param number $partialPlayPercentage The weight percentage to give this player when calculating a new rank.
* @param number $partialUpdatePercentage Indicated how much of a skill update a player should receive where 0 represents no update and 1.0 represents 100% of the update.
*/
public function __construct(
private $_Id,
private $Id,
$partialPlayPercentage = self::DEFAULT_PARTIAL_PLAY_PERCENTAGE,
$partialUpdatePercentage = self::DEFAULT_PARTIAL_UPDATE_PERCENTAGE
) {
// If they don't want to give a player an id, that's ok...
Guard::argumentInRangeInclusive($partialPlayPercentage, 0.0, 1.0, 'partialPlayPercentage');
Guard::argumentInRangeInclusive($partialUpdatePercentage, 0, 1.0, 'partialUpdatePercentage');
$this->_PartialPlayPercentage = $partialPlayPercentage;
$this->_PartialUpdatePercentage = $partialUpdatePercentage;
$this->PartialPlayPercentage = $partialPlayPercentage;
$this->PartialUpdatePercentage = $partialUpdatePercentage;
}
/**
@ -39,7 +39,7 @@ class Player implements ISupportPartialPlay, ISupportPartialUpdate, \Stringable
*/
public function getId()
{
return $this->_Id;
return $this->Id;
}
/**
@ -47,7 +47,7 @@ class Player implements ISupportPartialPlay, ISupportPartialUpdate, \Stringable
*/
public function getPartialPlayPercentage()
{
return $this->_PartialPlayPercentage;
return $this->PartialPlayPercentage;
}
/**
@ -55,11 +55,11 @@ class Player implements ISupportPartialPlay, ISupportPartialUpdate, \Stringable
*/
public function getPartialUpdatePercentage()
{
return $this->_PartialUpdatePercentage;
return $this->PartialUpdatePercentage;
}
public function __toString(): string
{
return (string) $this->_Id;
return (string) $this->Id;
}
}

2
src/Rating.php
View File

@ -7,7 +7,7 @@ use DNW\Skills\Numerics\GaussianDistribution;
class Rating implements \Stringable
{
final const CONSERVATIVE_STANDARD_DEVIATION_MULTIPLIER = 3;
private const CONSERVATIVE_STANDARD_DEVIATION_MULTIPLIER = 3;
/**
* Constructs a rating.

14
src/RatingContainer.php
View File

@ -4,35 +4,35 @@ namespace DNW\Skills;
class RatingContainer
{
private HashMap $_playerToRating;
private HashMap $playerToRating;
public function __construct()
{
$this->_playerToRating = new HashMap();
$this->playerToRating = new HashMap();
}
public function getRating(Player $player): mixed
{
return $this->_playerToRating->getValue($player);
return $this->playerToRating->getValue($player);
}
public function setRating(Player $player, Rating $rating): HashMap
{
return $this->_playerToRating->setValue($player, $rating);
return $this->playerToRating->setValue($player, $rating);
}
public function getAllPlayers(): array
{
return $this->_playerToRating->getAllKeys();
return $this->playerToRating->getAllKeys();
}
public function getAllRatings(): array
{
return $this->_playerToRating->getAllValues();
return $this->playerToRating->getAllValues();
}
public function count(): int
{
return $this->_playerToRating->count();
return $this->playerToRating->count();
}
}

10
src/TrueSkill/Factors/GaussianPriorFactor.php
View File

@ -13,12 +13,12 @@ use DNW\Skills\Numerics\GaussianDistribution;
*/
class GaussianPriorFactor extends GaussianFactor
{
private $_newMessage;
private $newMessage;
public function __construct(float $mean, float $variance, Variable $variable)
{
parent::__construct(sprintf('Prior value going to %s', $variable));
$this->_newMessage = new GaussianDistribution($mean, sqrt($variance));
$this->newMessage = new GaussianDistribution($mean, sqrt($variance));
$newMessage = new Message(
GaussianDistribution::fromPrecisionMean(0, 0),
sprintf('message from %s to %s', $this, $variable)
@ -32,12 +32,12 @@ class GaussianPriorFactor extends GaussianFactor
$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()
$oldMarginal->getPrecisionMean() + $this->newMessage->getPrecisionMean() - $oldMessage->getValue()->getPrecisionMean(),
$oldMarginal->getPrecision() + $this->newMessage->getPrecision() - $oldMessage->getValue()->getPrecision()
);
$variable->setValue($newMarginal);
$message->setValue($this->_newMessage);
$message->setValue($this->newMessage);
return GaussianDistribution::subtract($oldMarginal, $newMarginal);
}