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More type checks

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This commit is contained in:
Jens True
2023-08-01 12:13:24 +00:00
parent 068b6f18aa
commit d5bba04f4f
15 changed files with 72 additions and 73 deletions
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38
src/Numerics/GaussianDistribution.php
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@ -18,7 +18,7 @@ class GaussianDistribution implements \Stringable
private $_variance;
public function __construct(private $_mean = 0.0, private $_standardDeviation = 1.0)
public function __construct(private float $_mean = 0.0, private float $_standardDeviation = 1.0)
{
$this->_variance = BasicMath::square($_standardDeviation);
@ -32,32 +32,32 @@ class GaussianDistribution implements \Stringable
}
}
public function getMean()
public function getMean(): float
{
return $this->_mean;
}
public function getVariance()
public function getVariance(): float
{
return $this->_variance;
}
public function getStandardDeviation()
public function getStandardDeviation(): float
{
return $this->_standardDeviation;
}
public function getPrecision()
public function getPrecision(): float
{
return $this->_precision;
}
public function getPrecisionMean()
public function getPrecisionMean(): float
{
return $this->_precisionMean;
}
public function getNormalizationConstant()
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);
@ -75,7 +75,7 @@ class GaussianDistribution implements \Stringable
return $result;
}
public static function fromPrecisionMean($precisionMean, $precision)
public static function fromPrecisionMean(float $precisionMean, float $precision): self
{
$result = new GaussianDistribution();
$result->_precision = $precision;
@ -96,13 +96,13 @@ class GaussianDistribution implements \Stringable
// For details, see http://www.tina-vision.net/tina-knoppix/tina-memo/2003-003.pdf
// for multiplication, the precision mean ones are easier to write :)
public static function multiply(GaussianDistribution $left, GaussianDistribution $right)
public static function multiply(GaussianDistribution $left, GaussianDistribution $right): self
{
return GaussianDistribution::fromPrecisionMean($left->_precisionMean + $right->_precisionMean, $left->_precision + $right->_precision);
}
// Computes the absolute difference between two Gaussians
public static function absoluteDifference(GaussianDistribution $left, GaussianDistribution $right)
public static function absoluteDifference(GaussianDistribution $left, GaussianDistribution $right): float
{
return max(
abs($left->_precisionMean - $right->_precisionMean),
@ -111,12 +111,12 @@ class GaussianDistribution implements \Stringable
}
// Computes the absolute difference between two Gaussians
public static function subtract(GaussianDistribution $left, GaussianDistribution $right)
public static function subtract(GaussianDistribution $left, GaussianDistribution $right): float
{
return GaussianDistribution::absoluteDifference($left, $right);
}
public static function logProductNormalization(GaussianDistribution $left, GaussianDistribution $right)
public static function logProductNormalization(GaussianDistribution $left, GaussianDistribution $right): float
{
if (($left->_precision == 0) || ($right->_precision == 0)) {
return 0;
@ -130,7 +130,7 @@ class GaussianDistribution implements \Stringable
return -$logSqrt2Pi - (log($varianceSum) / 2.0) - (BasicMath::square($meanDifference) / (2.0 * $varianceSum));
}
public static function divide(GaussianDistribution $numerator, GaussianDistribution $denominator)
public static function divide(GaussianDistribution $numerator, GaussianDistribution $denominator): self
{
return GaussianDistribution::fromPrecisionMean(
$numerator->_precisionMean - $denominator->_precisionMean,
@ -138,7 +138,7 @@ class GaussianDistribution implements \Stringable
);
}
public static function logRatioNormalization(GaussianDistribution $numerator, GaussianDistribution $denominator)
public static function logRatioNormalization(GaussianDistribution $numerator, GaussianDistribution $denominator): float
{
if (($numerator->_precision == 0) || ($denominator->_precision == 0)) {
return 0;
@ -153,7 +153,7 @@ class GaussianDistribution implements \Stringable
BasicMath::square($meanDifference) / (2 * $varianceDifference);
}
public static function at($x, $mean = 0.0, $standardDeviation = 1.0)
public static function at(float $x, float $mean = 0.0, float $standardDeviation = 1.0): float
{
// See http://mathworld.wolfram.com/NormalDistribution.html
// 1 -(x-mean)^2 / (2*stdDev^2)
@ -166,7 +166,7 @@ class GaussianDistribution implements \Stringable
return $multiplier * $expPart;
}
public static function cumulativeTo($x, $mean = 0.0, $standardDeviation = 1.0)
public static function cumulativeTo(float $x, float $mean = 0.0, float $standardDeviation = 1.0): float
{
$invsqrt2 = -0.707106781186547524400844362104;
$result = GaussianDistribution::errorFunctionCumulativeTo($invsqrt2 * $x);
@ -174,7 +174,7 @@ class GaussianDistribution implements \Stringable
return 0.5 * $result;
}
private static function errorFunctionCumulativeTo($x)
private static function errorFunctionCumulativeTo($x): float
{
// Derived from page 265 of Numerical Recipes 3rd Edition
$z = abs($x);
@ -227,7 +227,7 @@ class GaussianDistribution implements \Stringable
return ($x >= 0.0) ? $ans : (2.0 - $ans);
}
private static function inverseErrorFunctionCumulativeTo($p)
private static function inverseErrorFunctionCumulativeTo(float $p): float
{
// From page 265 of numerical recipes
@ -250,7 +250,7 @@ class GaussianDistribution implements \Stringable
return ($p < 1.0) ? $x : -$x;
}
public static function inverseCumulativeTo($x, $mean = 0.0, $standardDeviation = 1.0)
public static function inverseCumulativeTo(float $x, float $mean = 0.0, float $standardDeviation = 1.0): float
{
// From numerical recipes, page 320
return $mean - sqrt(2) * $standardDeviation * GaussianDistribution::inverseErrorFunctionCumulativeTo(2 * $x);