php-ai / php-ml

src/Phpml/DimensionReduction/KernelPCA.php

Spacing +6 added lines, -6 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\DimensionReduction;
 
@@ -161,20 +161,20 @@ 
         switch ($this->kernel) {
             case self::KERNEL_LINEAR:
                 // k(x,y) = xT.y
-                return function ($x, $y) {
+                return function($x, $y) {
                     return Matrix::dot($x, $y)[0];
                 };
             case self::KERNEL_RBF:
                 // k(x,y)=exp(-γ.|x-y|) where |..| is Euclidean distance
                 $dist = new Euclidean();
 
-                return function ($x, $y) use ($dist) {
+                return function($x, $y) use ($dist) {
                     return exp(-$this->gamma * $dist->sqDistance($x, $y));
                 };
 
             case self::KERNEL_SIGMOID:
                 // k(x,y)=tanh(γ.xT.y+c0) where c0=1
-                return function ($x, $y) {
+                return function($x, $y) {
                     $res = Matrix::dot($x, $y)[0] + 1.0;
 
                     return tanh($this->gamma * $res);
@@ -184,7 +184,7 @@ 
                 // k(x,y)=exp(-γ.|x-y|) where |..| is Manhattan distance
                 $dist = new Manhattan();
 
-                return function ($x, $y) use ($dist) {
+                return function($x, $y) use ($dist) {
                     return exp(-$this->gamma * $dist->distance($x, $y));
                 };
 
@@ -218,7 +218,7 @@ 
     protected function projectSample(array $pairs): array
     {
         // Normalize eigenvectors by eig = eigVectors / eigValues
-        $func = function ($eigVal, $eigVect) {
+        $func = function($eigVal, $eigVect) {
             $m = new Matrix($eigVect, false);
             $a = $m->divideByScalar($eigVal)->toArray();
 

src/Phpml/CrossValidation/Split.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\CrossValidation;
 
@@ -62,7 +62,7 @@ 
 
     abstract protected function splitDataset(Dataset $dataset, float $testSize);
 
-    protected function seedGenerator(?int $seed = null): void
+    protected function seedGenerator(?int $seed = null) : void
     {
         if ($seed === null) {
             mt_srand();

src/Phpml/FeatureExtraction/TfIdfTransformer.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\FeatureExtraction;
 
@@ -13,7 +13,7 @@ 
      */
     private $idf = [];
 
-    public function __construct(?array $samples = null)
+    public function __construct(? array $samples = null)
     {
         if ($samples) {
             $this->fit($samples);

src/Phpml/Metric/ConfusionMatrix.php

Spacing +2 added lines, -2 removed lines

@@ -1,12 +1,12 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Metric;
 
 class ConfusionMatrix
 {
-    public static function compute(array $actualLabels, array $predictedLabels, ?array $labels = null): array
+    public static function compute(array $actualLabels, array $predictedLabels, ? array $labels = null) : array
     {
         $labels = $labels ? array_flip($labels) : self::getUniqueLabels($actualLabels);
         $matrix = self::generateMatrixWithZeros($labels);

src/Phpml/Math/Matrix.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Math;
 
@@ -126,7 +126,7 @@ 
     public function transpose(): self
     {
         if ($this->rows == 1) {
-            $matrix = array_map(function ($el) {
+            $matrix = array_map(function($el) {
                 return [$el];
             }, $this->matrix[0]);
         } else {

src/Phpml/Math/Statistic/Covariance.php

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Math\Statistic;
 
@@ -14,7 +14,7 @@ 
      *
      * @throws InvalidArgumentException
      */
-    public static function fromXYArrays(array $x, array $y, bool $sample = true, ?float $meanX = null, ?float $meanY = null): float
+    public static function fromXYArrays(array $x, array $y, bool $sample = true, ?float $meanX = null, ?float $meanY = null) : float
     {
         if (empty($x) || empty($y)) {
             throw InvalidArgumentException::arrayCantBeEmpty();
@@ -52,7 +52,7 @@ 
      * @throws InvalidArgumentException
      * @throws \Exception
      */
-    public static function fromDataset(array $data, int $i, int $k, bool $sample = true, ?float $meanX = null, ?float $meanY = null): float
+    public static function fromDataset(array $data, int $i, int $k, bool $sample = true, ?float $meanX = null, ?float $meanY = null) : float
     {
         if (empty($data)) {
             throw InvalidArgumentException::arrayCantBeEmpty();
@@ -115,7 +115,7 @@ 
      *
      * @param array|null $means
      */
-    public static function covarianceMatrix(array $data, ?array $means = null): array
+    public static function covarianceMatrix(array $data, ? array $means = null) : array
     {
         $n = count($data[0]);
 

src/Phpml/Math/LinearAlgebra/LUDecomposition.php

Spacing +1 added lines, -1 removed lines

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 /**
  * @package JAMA

src/Phpml/Math/LinearAlgebra/EigenvalueDecomposition.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 /**
  *	Class to obtain eigenvalues and eigenvectors of a real matrix.
@@ -128,7 +128,7 @@ 
 
         // Always return the eigenvectors of length 1.0
         $vectors = new Matrix($vectors);
-        $vectors = array_map(function ($vect) {
+        $vectors = array_map(function($vect) {
             $sum = 0;
             for ($i = 0; $i < count($vect); ++$i) {
                 $sum += $vect[$i] ** 2;

src/Phpml/NeuralNetwork/Layer.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\NeuralNetwork;
 
@@ -44,7 +44,7 @@ 
     /**
      * @return Neuron
      */
-    private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null): Node
+    private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null) : Node
     {
         if ($nodeClass === Neuron::class) {
             return new Neuron($activationFunction);