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Much stricter coding standards for phpstan, phpstan and psalm.

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This commit is contained in:
Jens True
2025-04-15 08:14:08 +00:00
parent 3c617e9869
commit b38a9656eb
63 changed files with 137 additions and 134 deletions
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14
src/Numerics/GaussianDistribution.php
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@ -10,7 +10,7 @@ namespace DNW\Skills\Numerics;
* @author Jeff Moser <jeff@moserware.com>
* @copyright 2010 Jeff Moser
*/
class GaussianDistribution
final class GaussianDistribution
{
private const float DEFAULT_STANDARD_DEVIATION = 1.0;
@ -171,7 +171,7 @@ class GaussianDistribution
$meanDifference = $numerator->mean - $denominator->mean;
return log($denominator->variance) + self::M_LOG_SQRT_2_PI - log($varianceDifference) / 2.0 +
BasicMath::square($meanDifference) / (2 * $varianceDifference);
BasicMath::square($meanDifference) / (2.0 * $varianceDifference);
}
public static function at(float $var, float $mean = 0.0, float $standardDeviation = 1.0): float
@ -182,7 +182,7 @@ class GaussianDistribution
// stdDev * sqrt(2*pi)
$multiplier = 1.0 / ($standardDeviation * self::M_SQRT_2_PI);
$expPart = exp((-1.0 * BasicMath::square($var - $mean)) / (2 * BasicMath::square($standardDeviation)));
$expPart = exp((-1.0 * BasicMath::square($var - $mean)) / (2.0 * BasicMath::square($standardDeviation)));
return $multiplier * $expPart;
}
@ -200,7 +200,7 @@ class GaussianDistribution
$z = abs($var);
$t = 2.0 / (2.0 + $z);
$ty = 4 * $t - 2;
$ty = 4.0 * $t - 2.0;
$coefficients = [
-1.3026537197817094,
@ -259,8 +259,8 @@ class GaussianDistribution
return 100;
}
$pp = ($p < 1.0) ? $p : 2 - $p;
$t = sqrt(-2 * log($pp / 2.0)); // Initial guess
$pp = ($p < 1.0) ? $p : 2.0 - $p;
$t = sqrt(-2.0 * log($pp / 2.0)); // Initial guess
$x = -M_SQRT1_2 * ((2.30753 + $t * 0.27061) / (1.0 + $t * (0.99229 + $t * 0.04481)) - $t);
for ($j = 0; $j < 2; ++$j) {
@ -274,6 +274,6 @@ class GaussianDistribution
public static function inverseCumulativeTo(float $var, float $mean = 0.0, float $standardDeviation = 1.0): float
{
// From numerical recipes, page 320
return $mean - M_SQRT2 * $standardDeviation * GaussianDistribution::inverseErrorFunctionCumulativeTo(2 * $var);
return $mean - M_SQRT2 * $standardDeviation * GaussianDistribution::inverseErrorFunctionCumulativeTo(2.0 * $var);
}
}