Issue #351: Replace pow() and sqrt() with double stars notation. (#352)

src/Classification/DecisionTree.php

@@ -137,7 +137,7 @@ class DecisionTree implements Classifier
             $sum = array_sum(array_column($countMatrix, $i));
             if ($sum > 0) {
                 foreach ($this->labels as $label) {
-                    $part += pow($countMatrix[$label][$i] / (float) $sum, 2);
+                    $part += ($countMatrix[$label][$i] / (float) $sum) ** 2;
                 }
             }
 

src/Classification/Ensemble/RandomForest.php

@@ -131,7 +131,7 @@ class RandomForest extends Bagging
         if (is_float($this->featureSubsetRatio)) {
             $featureCount = (int) ($this->featureSubsetRatio * $this->featureCount);
         } elseif ($this->featureSubsetRatio === 'sqrt') {
-            $featureCount = (int) sqrt($this->featureCount) + 1;
+            $featureCount = (int) ($this->featureCount ** .5) + 1;
         } else {
             $featureCount = (int) log($this->featureCount, 2) + 1;
         }

src/Classification/NaiveBayes.php

@@ -162,7 +162,7 @@ class NaiveBayes implements Classifier
         // scikit-learn did.
         // (See : https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/naive_bayes.py)
         $pdf = -0.5 * log(2.0 * M_PI * $std * $std);
-        $pdf -= 0.5 * pow($value - $mean, 2) / ($std * $std);
+        $pdf -= 0.5 * (($value - $mean) ** 2) / ($std * $std);
 
         return $pdf;
     }

src/Clustering/KMeans/Point.php

@@ -49,7 +49,7 @@ class Point implements ArrayAccess, \Countable
             $distance += $difference * $difference;
         }
 
-        return $precise ? sqrt((float) $distance) : $distance;
+        return $precise ? $distance ** .5 : $distance;
     }
 
     /**

src/Math/LinearAlgebra/EigenvalueDecomposition.php

@@ -128,12 +128,13 @@ class EigenvalueDecomposition
         $vectors = new Matrix($vectors);
         $vectors = array_map(function ($vect) {
             $sum = 0;
-            for ($i = 0; $i < count($vect); ++$i) {
+            $count = count($vect);
+            for ($i = 0; $i < $count; ++$i) {
                 $sum += $vect[$i] ** 2;
             }
 
-            $sum = sqrt($sum);
-            for ($i = 0; $i < count($vect); ++$i) {
+            $sum **= .5;
+            for ($i = 0; $i < $count; ++$i) {
                 $vect[$i] /= $sum;
             }
 
@@ -208,11 +209,11 @@ class EigenvalueDecomposition
                 // Generate Householder vector.
                 for ($k = 0; $k < $i; ++$k) {
                     $this->d[$k] /= $scale;
-                    $h += pow($this->d[$k], 2);
+                    $h += $this->d[$k] ** 2;
                 }
 
                 $f = $this->d[$i_];
-                $g = sqrt($h);
+                $g = $h ** .5;
                 if ($f > 0) {
                     $g = -$g;
                 }
@@ -320,7 +321,7 @@ class EigenvalueDecomposition
         $this->e[$this->n - 1] = 0.0;
         $f = 0.0;
         $tst1 = 0.0;
-        $eps = pow(2.0, -52.0);
+        $eps = 2.0 ** -52.0;
 
         for ($l = 0; $l < $this->n; ++$l) {
             // Find small subdiagonal element
@@ -443,7 +444,7 @@ class EigenvalueDecomposition
                     $h += $this->ort[$i] * $this->ort[$i];
                 }
 
-                $g = sqrt($h);
+                $g = $h ** .5;
                 if ($this->ort[$m] > 0) {
                     $g *= -1;
                 }
@@ -548,7 +549,7 @@ class EigenvalueDecomposition
         $n = $nn - 1;
         $low = 0;
         $high = $nn - 1;
-        $eps = pow(2.0, -52.0);
+        $eps = 2.0 ** -52.0;
         $exshift = 0.0;
         $p = $q = $r = $s = $z = 0;
         // Store roots isolated by balanc and compute matrix norm
@@ -596,7 +597,7 @@ class EigenvalueDecomposition
                 $w = $this->H[$n][$n - 1] * $this->H[$n - 1][$n];
                 $p = ($this->H[$n - 1][$n - 1] - $this->H[$n][$n]) / 2.0;
                 $q = $p * $p + $w;
-                $z = sqrt(abs($q));
+                $z = abs($q) ** .5;
                 $this->H[$n][$n] += $exshift;
                 $this->H[$n - 1][$n - 1] += $exshift;
                 $x = $this->H[$n][$n];
@@ -620,7 +621,7 @@ class EigenvalueDecomposition
                     $s = abs($x) + abs($z);
                     $p = $x / $s;
                     $q = $z / $s;
-                    $r = sqrt($p * $p + $q * $q);
+                    $r = ($p * $p + $q * $q) ** .5;
                     $p /= $r;
                     $q /= $r;
                     // Row modification
@@ -682,7 +683,7 @@ class EigenvalueDecomposition
                     $s = ($y - $x) / 2.0;
                     $s *= $s + $w;
                     if ($s > 0) {
-                        $s = sqrt($s);
+                        $s **= .5;
                         if ($y < $x) {
                             $s = -$s;
                         }
@@ -750,7 +751,7 @@ class EigenvalueDecomposition
                         break;
                     }
 
-                    $s = sqrt($p * $p + $q * $q + $r * $r);
+                    $s = ($p * $p + $q * $q + $r * $r) ** .5;
                     if ($p < 0) {
                         $s = -$s;
                     }

src/Math/Matrix.php

@@ -271,7 +271,7 @@ class Matrix
             }
         }
 
-        return sqrt($squareSum);
+        return $squareSum ** .5;
     }
 
     /**

src/Math/Statistic/Correlation.php

@@ -32,10 +32,10 @@ class Correlation
             $a = $x[$i] - $meanX;
             $b = $y[$i] - $meanY;
             $axb += ($a * $b);
-            $a2 += pow($a, 2);
-            $b2 += pow($b, 2);
+            $a2 += $a ** 2;
+            $b2 += $b ** 2;
         }
 
-        return $axb / sqrt((float) ($a2 * $b2));
+        return $axb / ($a2 * $b2) ** .5;
     }
 }

src/Math/Statistic/Gaussian.php

@@ -34,7 +34,7 @@ class Gaussian
         $std2 = $this->std ** 2;
         $mean = $this->mean;
 
-        return exp(-(($value - $mean) ** 2) / (2 * $std2)) / sqrt(2 * $std2 * M_PI);
+        return exp(-(($value - $mean) ** 2) / (2 * $std2)) / ((2 * $std2 * M_PI) ** .5);
     }
 
     /**

src/Math/Statistic/StandardDeviation.php

@@ -32,7 +32,7 @@ class StandardDeviation
             --$n;
         }
 
-        return sqrt($carry / $n);
+        return ($carry / $n) ** .5;
     }
 
     /**

src/NeuralNetwork/ActivationFunction/Gaussian.php

@@ -13,7 +13,7 @@ class Gaussian implements ActivationFunction
      */
     public function compute($value): float
     {
-        return exp(-pow($value, 2));
+        return exp(- $value ** 2);
     }
 
     /**

src/NeuralNetwork/ActivationFunction/HyperbolicTangent.php

@@ -32,6 +32,6 @@ class HyperbolicTangent implements ActivationFunction
      */
     public function differentiate($value, $computedvalue): float
     {
-        return 1 - pow($computedvalue, 2);
+        return 1 - $computedvalue ** 2;
     }
 }

src/Preprocessing/Normalizer.php

@@ -106,7 +106,7 @@ class Normalizer implements Preprocessor
             $norm2 += $feature * $feature;
         }
 
-        $norm2 = sqrt((float) $norm2);
+        $norm2 **= .5;
 
         if ($norm2 == 0) {
             $sample = array_fill(0, count($sample), 1);