Add phpstan strict rules (#233)

* Add phpstan strict rules

* Fix travis coveralls

* Add phpstan-phpunit strict rules

* Fix eigen decomposition test name and phpstan ingored error

.travis.yml

@@ -41,5 +41,5 @@ after_success:
   - |
     if [[ $PHPUNIT_FLAGS != "" ]]; then
       wget https://github.com/php-coveralls/php-coveralls/releases/download/v2.0.0/php-coveralls.phar
-      php coveralls.phar --verbose;
+      php php-coveralls.phar --verbose;
     fi

composer.json

@@ -23,7 +23,9 @@
         "php": "^7.1"
     },
     "require-dev": {
+        "phpstan/phpstan-phpunit": "^0.9.4",
         "phpstan/phpstan-shim": "^0.9",
+        "phpstan/phpstan-strict-rules": "^0.9.0",
         "phpunit/phpunit": "^7.0.0",
         "symplify/coding-standard": "^3.1",
         "symplify/easy-coding-standard": "^3.1"

composer.lock

@@ -4,7 +4,7 @@
         "Read more about it at https://getcomposer.org/doc/01-basic-usage.md#composer-lock-the-lock-file",
         "This file is @generated automatically"
     ],
-    "content-hash": "3e327a50a76dd6df905cef56cbc37e02",
+    "content-hash": "9135b3dece8c6938922f757123274e95",
     "packages": [],
     "packages-dev": [
         {
@@ -1287,6 +1287,51 @@
             ],
             "time": "2017-11-24T13:59:53+00:00"
         },
+        {
+            "name": "phpstan/phpstan-phpunit",
+            "version": "0.9.4",
+            "source": {
+                "type": "git",
+                "url": "https://github.com/phpstan/phpstan-phpunit.git",
+                "reference": "852411f841a37aeca2fa5af0002b0272c485c9bf"
+            },
+            "dist": {
+                "type": "zip",
+                "url": "https://api.github.com/repos/phpstan/phpstan-phpunit/zipball/852411f841a37aeca2fa5af0002b0272c485c9bf",
+                "reference": "852411f841a37aeca2fa5af0002b0272c485c9bf",
+                "shasum": ""
+            },
+            "require": {
+                "php": "~7.0",
+                "phpstan/phpstan": "^0.9.1",
+                "phpunit/phpunit": "^6.3 || ~7.0"
+            },
+            "require-dev": {
+                "consistence/coding-standard": "^2.0",
+                "jakub-onderka/php-parallel-lint": "^0.9.2",
+                "phing/phing": "^2.16.0",
+                "phpstan/phpstan-strict-rules": "^0.9",
+                "satooshi/php-coveralls": "^1.0",
+                "slevomat/coding-standard": "^3.3.0"
+            },
+            "type": "library",
+            "extra": {
+                "branch-alias": {
+                    "dev-master": "0.9-dev"
+                }
+            },
+            "autoload": {
+                "psr-4": {
+                    "PHPStan\\": "src/"
+                }
+            },
+            "notification-url": "https://packagist.org/downloads/",
+            "license": [
+                "MIT"
+            ],
+            "description": "PHPUnit extensions and rules for PHPStan",
+            "time": "2018-02-02T09:45:47+00:00"
+        },
         {
             "name": "phpstan/phpstan-shim",
             "version": "0.9.1",
@@ -1324,6 +1369,50 @@
             "description": "PHPStan Phar distribution",
             "time": "2017-12-02T20:14:45+00:00"
         },
+        {
+            "name": "phpstan/phpstan-strict-rules",
+            "version": "0.9",
+            "source": {
+                "type": "git",
+                "url": "https://github.com/phpstan/phpstan-strict-rules.git",
+                "reference": "15be9090622c6b85c079922308f831018d8d9e23"
+            },
+            "dist": {
+                "type": "zip",
+                "url": "https://api.github.com/repos/phpstan/phpstan-strict-rules/zipball/15be9090622c6b85c079922308f831018d8d9e23",
+                "reference": "15be9090622c6b85c079922308f831018d8d9e23",
+                "shasum": ""
+            },
+            "require": {
+                "php": "~7.0",
+                "phpstan/phpstan": "^0.9"
+            },
+            "require-dev": {
+                "consistence/coding-standard": "^2.0.0",
+                "jakub-onderka/php-parallel-lint": "^0.9.2",
+                "phing/phing": "^2.16.0",
+                "phpstan/phpstan-phpunit": "^0.9",
+                "phpunit/phpunit": "^6.4",
+                "slevomat/coding-standard": "^3.3.0"
+            },
+            "type": "library",
+            "extra": {
+                "branch-alias": {
+                    "dev-master": "0.9-dev"
+                }
+            },
+            "autoload": {
+                "psr-4": {
+                    "PHPStan\\": "src/"
+                }
+            },
+            "notification-url": "https://packagist.org/downloads/",
+            "license": [
+                "MIT"
+            ],
+            "description": "Extra strict and opinionated rules for PHPStan",
+            "time": "2017-11-26T20:12:30+00:00"
+        },
         {
             "name": "phpunit/php-code-coverage",
             "version": "6.0.1",

phpstan.neon

@@ -1,15 +1,17 @@
+includes:
+    - vendor/phpstan/phpstan-strict-rules/rules.neon
+    - vendor/phpstan/phpstan-phpunit/extension.neon
+    - vendor/phpstan/phpstan-phpunit/rules.neon
+    - vendor/phpstan/phpstan-phpunit/strictRules.neon
+
 parameters:
     ignoreErrors:
         - '#Phpml\\Dataset\\FilesDataset::__construct\(\) does not call parent constructor from Phpml\\Dataset\\ArrayDataset#'
 
-        # mocks
-        - '#PHPUnit_Framework_MockObject_MockObject#'
-
         # wide range cases
         - '#Call to function count\(\) with argument type array<int>\|Phpml\\Clustering\\KMeans\\Point will always result in number 1#'
         - '#Parameter \#1 \$coordinates of class Phpml\\Clustering\\KMeans\\Point constructor expects array, array<int>\|Phpml\\Clustering\\KMeans\\Point given#'
 
         # probably known value
-        - '#Variable \$j might not be defined#'
         - '#Method Phpml\\Classification\\DecisionTree::getBestSplit\(\) should return Phpml\\Classification\\DecisionTree\\DecisionTreeLeaf but returns Phpml\\Classification\\DecisionTree\\DecisionTreeLeaf\|null#'
         - '#Call to an undefined method Phpml\\Helper\\Optimizer\\Optimizer::getCostValues\(\)#'

src/Association/Apriori.php

@@ -63,11 +63,11 @@ class Apriori implements Associator
      */
     public function getRules(): array
     {
-        if (!$this->large) {
+        if (empty($this->large)) {
             $this->large = $this->apriori();
         }
 
-        if ($this->rules) {
+        if (!empty($this->rules)) {
             return $this->rules;
         }
 

src/Classification/DecisionTree.php

@@ -273,15 +273,15 @@ class DecisionTree implements Classifier
         }
 
         if ($allSame || $depth >= $this->maxDepth || count($remainingTargets) === 1) {
-            $split->isTerminal = 1;
+            $split->isTerminal = true;
             arsort($remainingTargets);
             $split->classValue = key($remainingTargets);
         } else {
-            if ($leftRecords) {
+            if (!empty($leftRecords)) {
                 $split->leftLeaf = $this->getSplitLeaf($leftRecords, $depth + 1);
             }
 
-            if ($rightRecords) {
+            if (!empty($rightRecords)) {
                 $split->rightLeaf = $this->getSplitLeaf($rightRecords, $depth + 1);
             }
         }
@@ -312,13 +312,13 @@ class DecisionTree implements Classifier
                 $split->value = $baseValue;
                 $split->giniIndex = $gini;
                 $split->columnIndex = $i;
-                $split->isContinuous = $this->columnTypes[$i] == self::CONTINUOUS;
+                $split->isContinuous = $this->columnTypes[$i] === self::CONTINUOUS;
                 $split->records = $records;
 
                 // If a numeric column is to be selected, then
                 // the original numeric value and the selected operator
                 // will also be saved into the leaf for future access
-                if ($this->columnTypes[$i] == self::CONTINUOUS) {
+                if ($this->columnTypes[$i] === self::CONTINUOUS) {
                     $matches = [];
                     preg_match("/^([<>=]{1,2})\s*(.*)/", (string) $split->value, $matches);
                     $split->operator = $matches[1];
@@ -349,11 +349,11 @@ class DecisionTree implements Classifier
     protected function getSelectedFeatures(): array
     {
         $allFeatures = range(0, $this->featureCount - 1);
-        if ($this->numUsableFeatures === 0 && !$this->selectedFeatures) {
+        if ($this->numUsableFeatures === 0 && empty($this->selectedFeatures)) {
             return $allFeatures;
         }
 
-        if ($this->selectedFeatures) {
+        if (!empty($this->selectedFeatures)) {
             return $this->selectedFeatures;
         }
 
@@ -363,7 +363,7 @@ class DecisionTree implements Classifier
         }
 
         shuffle($allFeatures);
-        $selectedFeatures = array_slice($allFeatures, 0, $numFeatures, false);
+        $selectedFeatures = array_slice($allFeatures, 0, $numFeatures);
         sort($selectedFeatures);
 
         return $selectedFeatures;
@@ -406,7 +406,7 @@ class DecisionTree implements Classifier
         //	  all values in that column (Lower than or equal to %20 of all values)
         $numericValues = array_filter($columnValues, 'is_numeric');
         $floatValues = array_filter($columnValues, 'is_float');
-        if ($floatValues) {
+        if (!empty($floatValues)) {
             return false;
         }
 
@@ -433,7 +433,7 @@ class DecisionTree implements Classifier
      */
     protected function getSplitNodesByColumn(int $column, DecisionTreeLeaf $node): array
     {
-        if (!$node || $node->isTerminal) {
+        if ($node->isTerminal) {
             return [];
         }
 
@@ -444,11 +444,11 @@ class DecisionTree implements Classifier
 
         $lNodes = [];
         $rNodes = [];
-        if ($node->leftLeaf) {
+        if ($node->leftLeaf !== null) {
             $lNodes = $this->getSplitNodesByColumn($column, $node->leftLeaf);
         }
 
-        if ($node->rightLeaf) {
+        if ($node->rightLeaf !== null) {
             $rNodes = $this->getSplitNodesByColumn($column, $node->rightLeaf);
         }
 
@@ -475,6 +475,6 @@ class DecisionTree implements Classifier
             }
         } while ($node);
 
-        return $node ? $node->classValue : $this->labels[0];
+        return $node !== null ? $node->classValue : $this->labels[0];
     }
 }

src/Classification/DecisionTree/DecisionTreeLeaf.php

@@ -29,14 +29,14 @@ class DecisionTreeLeaf
     public $columnIndex;
 
     /**
-     * @var DecisionTreeLeaf
+     * @var ?DecisionTreeLeaf
      */
-    public $leftLeaf = null;
+    public $leftLeaf;
 
     /**
-     * @var DecisionTreeLeaf
+     * @var ?DecisionTreeLeaf
      */
-    public $rightLeaf = null;
+    public $rightLeaf;
 
     /**
      * @var array
@@ -52,7 +52,7 @@ class DecisionTreeLeaf
     public $classValue = '';
 
     /**
-     * @var bool|int
+     * @var bool
      */
     public $isTerminal = false;
 
@@ -103,12 +103,12 @@ class DecisionTreeLeaf
         $nodeSampleCount = (float) count($this->records);
         $iT = $this->giniIndex;
 
-        if ($this->leftLeaf) {
+        if ($this->leftLeaf !== null) {
             $pL = count($this->leftLeaf->records) / $nodeSampleCount;
             $iT -= $pL * $this->leftLeaf->giniIndex;
         }
 
-        if ($this->rightLeaf) {
+        if ($this->rightLeaf !== null) {
             $pR = count($this->rightLeaf->records) / $nodeSampleCount;
             $iT -= $pR * $this->rightLeaf->giniIndex;
         }
@@ -140,16 +140,16 @@ class DecisionTreeLeaf
 
         $str = "<table ><tr><td colspan=3 align=center style='border:1px solid;'>${value}</td></tr>";
 
-        if ($this->leftLeaf || $this->rightLeaf) {
+        if ($this->leftLeaf !== null || $this->rightLeaf !== null) {
             $str .= '<tr>';
-            if ($this->leftLeaf) {
+            if ($this->leftLeaf !== null) {
                 $str .= '<td valign=top><b>| Yes</b><br>'.$this->leftLeaf->getHTML($columnNames).'</td>';
             } else {
                 $str .= '<td></td>';
             }
 
             $str .= '<td>&nbsp;</td>';
-            if ($this->rightLeaf) {
+            if ($this->rightLeaf !== null) {
                 $str .= '<td valign=top align=right><b>No |</b><br>'.$this->rightLeaf->getHTML($columnNames).'</td>';
             } else {
                 $str .= '<td></td>';

src/Classification/Ensemble/AdaBoost.php

@@ -158,7 +158,7 @@ class AdaBoost implements Classifier
     protected function getBestClassifier(): Classifier
     {
         $ref = new ReflectionClass($this->baseClassifier);
-        if ($this->classifierOptions) {
+        if (!empty($this->classifierOptions)) {
             $classifier = $ref->newInstanceArgs($this->classifierOptions);
         } else {
             $classifier = $ref->newInstance();

src/Classification/Ensemble/Bagging.php

@@ -145,7 +145,7 @@ class Bagging implements Classifier
         $classifiers = [];
         for ($i = 0; $i < $this->numClassifier; ++$i) {
             $ref = new ReflectionClass($this->classifier);
-            if ($this->classifierOptions) {
+            if (!empty($this->classifierOptions)) {
                 $obj = $ref->newInstanceArgs($this->classifierOptions);
             } else {
                 $obj = $ref->newInstance();

src/Classification/Linear/Adaline.php

@@ -42,7 +42,7 @@ class Adaline extends Perceptron
         bool $normalizeInputs = true,
         int $trainingType = self::BATCH_TRAINING
     ) {
-        if (!in_array($trainingType, [self::BATCH_TRAINING, self::ONLINE_TRAINING])) {
+        if (!in_array($trainingType, [self::BATCH_TRAINING, self::ONLINE_TRAINING], true)) {
             throw new Exception('Adaline can only be trained with batch and online/stochastic gradient descent algorithm');
         }
 

src/Classification/Linear/DecisionStump.php

@@ -118,7 +118,7 @@ class DecisionStump extends WeightedClassifier
 
         // Check the size of the weights given.
         // If none given, then assign 1 as a weight to each sample
-        if ($this->weights) {
+        if (!empty($this->weights)) {
             $numWeights = count($this->weights);
             if ($numWeights != count($samples)) {
                 throw new Exception('Number of sample weights does not match with number of samples');

src/Classification/Linear/LogisticRegression.php

@@ -71,13 +71,13 @@ class LogisticRegression extends Adaline
         string $penalty = 'L2'
     ) {
         $trainingTypes = range(self::BATCH_TRAINING, self::CONJUGATE_GRAD_TRAINING);
-        if (!in_array($trainingType, $trainingTypes)) {
+        if (!in_array($trainingType, $trainingTypes, true)) {
             throw new Exception('Logistic regression can only be trained with '.
                 'batch (gradient descent), online (stochastic gradient descent) '.
                 'or conjugate batch (conjugate gradients) algorithms');
         }
 
-        if (!in_array($cost, ['log', 'sse'])) {
+        if (!in_array($cost, ['log', 'sse'], true)) {
             throw new Exception("Logistic regression cost function can be one of the following: \n".
                 "'log' for log-likelihood and 'sse' for sum of squared errors");
         }

src/Classification/Linear/Perceptron.php

@@ -97,7 +97,7 @@ class Perceptron implements Classifier, IncrementalEstimator
 
     public function trainBinary(array $samples, array $targets, array $labels): void
     {
-        if ($this->normalizer) {
+        if ($this->normalizer !== null) {
             $this->normalizer->transform($samples);
         }
 
@@ -196,7 +196,7 @@ class Perceptron implements Classifier, IncrementalEstimator
      */
     protected function checkNormalizedSample(array $sample): array
     {
-        if ($this->normalizer) {
+        if ($this->normalizer !== null) {
             $samples = [$sample];
             $this->normalizer->transform($samples);
             $sample = $samples[0];

src/Classification/MLPClassifier.php

@@ -16,11 +16,11 @@ class MLPClassifier extends MultilayerPerceptron implements Classifier
      */
     public function getTargetClass($target): int
     {
-        if (!in_array($target, $this->classes)) {
+        if (!in_array($target, $this->classes, true)) {
             throw InvalidArgumentException::invalidTarget($target);
         }
 
-        return array_search($target, $this->classes);
+        return array_search($target, $this->classes, true);
     }
 
     /**

src/Clustering/FuzzyCMeans.php

@@ -20,7 +20,7 @@ class FuzzyCMeans implements Clusterer
     /**
      * @var array|Cluster[]
      */
-    private $clusters = null;
+    private $clusters = [];
 
     /**
      * @var Space
@@ -152,8 +152,7 @@ class FuzzyCMeans implements Clusterer
     protected function updateClusters(): void
     {
         $dim = $this->space->getDimension();
-        if (!$this->clusters) {
+        if (empty($this->clusters)) {
-            $this->clusters = [];
             for ($i = 0; $i < $this->clustersNumber; ++$i) {
                 $this->clusters[] = new Cluster($this->space, array_fill(0, $dim, 0.0));
             }

src/Clustering/KMeans/Cluster.php

@@ -76,8 +76,7 @@ class Cluster extends Point implements IteratorAggregate, Countable
 
     public function updateCentroid(): void
     {
-        $count = count($this->points);
+        if (empty($this->points)) {
-        if (!$count) {
             return;
         }
 
@@ -89,6 +88,7 @@ class Cluster extends Point implements IteratorAggregate, Countable
             }
         }
 
+        $count = count($this->points);
         for ($n = 0; $n < $this->dimension; ++$n) {
             $this->coordinates[$n] = $centroid->coordinates[$n] / $count;
         }

src/Clustering/KMeans/Space.php

@@ -16,7 +16,7 @@ class Space extends SplObjectStorage
      */
     protected $dimension;
 
-    public function __construct($dimension)
+    public function __construct(int $dimension)
     {
         if ($dimension < 1) {
             throw new LogicException('a space dimension cannot be null or negative');
@@ -75,7 +75,7 @@ class Space extends SplObjectStorage
      */
     public function getBoundaries()
     {
-        if (!count($this)) {
+        if (empty($this)) {
             return false;
         }
 
@@ -153,8 +153,8 @@ class Space extends SplObjectStorage
                 $closest = $point->getClosest($clusters);
 
                 if ($closest !== $cluster) {
-                    isset($attach[$closest]) || $attach[$closest] = new SplObjectStorage();
+                    $attach[$closest] ?? $attach[$closest] = new SplObjectStorage();
-                    isset($detach[$cluster]) || $detach[$cluster] = new SplObjectStorage();
+                    $detach[$cluster] ?? $detach[$cluster] = new SplObjectStorage();
 
                     $attach[$closest]->attach($point);
                     $detach[$cluster]->attach($point);

src/DimensionReduction/KernelPCA.php

@@ -58,7 +58,7 @@ class KernelPCA extends PCA
     public function __construct(int $kernel = self::KERNEL_RBF, ?float $totalVariance = null, ?int $numFeatures = null, ?float $gamma = null)
     {
         $availableKernels = [self::KERNEL_RBF, self::KERNEL_SIGMOID, self::KERNEL_LAPLACIAN, self::KERNEL_LINEAR];
-        if (!in_array($kernel, $availableKernels)) {
+        if (!in_array($kernel, $availableKernels, true)) {
             throw new Exception('KernelPCA can be initialized with the following kernels only: Linear, RBF, Sigmoid and Laplacian');
         }
 

src/DimensionReduction/LDA.php

@@ -130,7 +130,7 @@ class LDA extends EigenTransformerBase
         $overallMean = array_fill(0, count($data[0]), 0.0);
 
         foreach ($data as $index => $row) {
-            $label = array_search($classes[$index], $this->labels);
+            $label = array_search($classes[$index], $this->labels, true);
 
             foreach ($row as $col => $val) {
                 if (!isset($means[$label][$col])) {
@@ -177,7 +177,7 @@ class LDA extends EigenTransformerBase
         $sW = new Matrix($s, false);
 
         foreach ($data as $index => $row) {
-            $label = array_search($classes[$index], $this->labels);
+            $label = array_search($classes[$index], $this->labels, true);
             $means = $this->means[$label];
 
             $row = $this->calculateVar($row, $means);

src/FeatureExtraction/TfIdfTransformer.php

@@ -13,9 +13,9 @@ class TfIdfTransformer implements Transformer
      */
     private $idf = [];
 
-    public function __construct(?array $samples = null)
+    public function __construct(array $samples = [])
     {
-        if ($samples) {
+        if (!empty($samples)) {
             $this->fit($samples);
         }
     }

src/FeatureExtraction/TokenCountVectorizer.php

@@ -123,7 +123,7 @@ class TokenCountVectorizer implements Transformer
 
     private function isStopWord(string $token): bool
     {
-        return $this->stopWords && $this->stopWords->isStopWord($token);
+        return $this->stopWords !== null && $this->stopWords->isStopWord($token);
     }
 
     private function updateFrequency(string $token): void

src/Math/LinearAlgebra/EigenvalueDecomposition.php

@@ -274,6 +274,7 @@ class EigenvalueDecomposition
         }
 
         // Accumulate transformations.
+        $j = 0;
         for ($i = 0; $i < $this->n - 1; ++$i) {
             $this->V[$this->n - 1][$i] = $this->V[$i][$i];
             $this->V[$i][$i] = 1.0;

src/Math/Matrix.php

@@ -105,7 +105,7 @@ class Matrix
      */
     public function getDeterminant()
     {
-        if ($this->determinant) {
+        if ($this->determinant !== null) {
             return $this->determinant;
         }
 

src/Math/Statistic/Mean.php

@@ -50,7 +50,7 @@ class Mean
 
         $values = array_count_values($numbers);
 
-        return array_search(max($values), $values);
+        return array_search(max($values), $values, true);
     }
 
     /**

src/Metric/ClassificationReport.php

@@ -57,7 +57,7 @@ class ClassificationReport
     public function __construct(array $actualLabels, array $predictedLabels, int $average = self::MACRO_AVERAGE)
     {
         $averagingMethods = range(self::MICRO_AVERAGE, self::WEIGHTED_AVERAGE);
-        if (!in_array($average, $averagingMethods)) {
+        if (!in_array($average, $averagingMethods, true)) {
             throw new InvalidArgumentException('Averaging method must be MICRO_AVERAGE, MACRO_AVERAGE or WEIGHTED_AVERAGE');
         }
 

src/Metric/ConfusionMatrix.php

@@ -6,9 +6,9 @@ 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 = []): array
     {
-        $labels = $labels ? array_flip($labels) : self::getUniqueLabels($actualLabels);
+        $labels = !empty($labels) ? array_flip($labels) : self::getUniqueLabels($actualLabels);
         $matrix = self::generateMatrixWithZeros($labels);
 
         foreach ($actualLabels as $index => $actual) {

src/NeuralNetwork/Layer.php

@@ -19,7 +19,7 @@ class Layer
      */
     public function __construct(int $nodesNumber = 0, string $nodeClass = Neuron::class, ?ActivationFunction $activationFunction = null)
     {
-        if (!in_array(Node::class, class_implements($nodeClass))) {
+        if (!in_array(Node::class, class_implements($nodeClass), true)) {
             throw InvalidArgumentException::invalidLayerNodeClass();
         }
 

src/Preprocessing/Normalizer.php

@@ -41,7 +41,7 @@ class Normalizer implements Preprocessor
      */
     public function __construct(int $norm = self::NORM_L2)
     {
-        if (!in_array($norm, [self::NORM_L1, self::NORM_L2, self::NORM_STD])) {
+        if (!in_array($norm, [self::NORM_L1, self::NORM_L2, self::NORM_STD], true)) {
             throw NormalizerException::unknownNorm();
         }
 

src/SupportVectorMachine/DataTransformer.php

@@ -42,7 +42,7 @@ class DataTransformer
         $results = [];
         foreach (explode(PHP_EOL, $rawPredictions) as $result) {
             if (isset($result[0])) {
-                $results[] = array_search($result, $numericLabels);
+                $results[] = array_search((int) $result, $numericLabels, true);
             }
         }
 
@@ -61,7 +61,7 @@ class DataTransformer
 
         $columnLabels = [];
         foreach ($headerColumns as $numericLabel) {
-            $columnLabels[] = array_search($numericLabel, $numericLabels);
+            $columnLabels[] = array_search((int) $numericLabel, $numericLabels, true);
         }
 
         $results = [];

src/SupportVectorMachine/SupportVectorMachine.php

@@ -149,7 +149,7 @@ class SupportVectorMachine
         $this->samples = array_merge($this->samples, $samples);
         $this->targets = array_merge($this->targets, $targets);
 
-        $trainingSet = DataTransformer::trainingSet($this->samples, $this->targets, in_array($this->type, [Type::EPSILON_SVR, Type::NU_SVR]));
+        $trainingSet = DataTransformer::trainingSet($this->samples, $this->targets, in_array($this->type, [Type::EPSILON_SVR, Type::NU_SVR], true));
         file_put_contents($trainingSetFileName = $this->varPath.uniqid('phpml', true), $trainingSet);
         $modelFileName = $trainingSetFileName.'-model';
 
@@ -182,7 +182,7 @@ class SupportVectorMachine
     {
         $predictions = $this->runSvmPredict($samples, false);
 
-        if (in_array($this->type, [Type::C_SVC, Type::NU_SVC])) {
+        if (in_array($this->type, [Type::C_SVC, Type::NU_SVC], true)) {
             $predictions = DataTransformer::predictions($predictions, $this->targets);
         } else {
             $predictions = explode(PHP_EOL, trim($predictions));
@@ -208,7 +208,7 @@ class SupportVectorMachine
 
         $predictions = $this->runSvmPredict($samples, true);
 
-        if (in_array($this->type, [Type::C_SVC, Type::NU_SVC])) {
+        if (in_array($this->type, [Type::C_SVC, Type::NU_SVC], true)) {
             $predictions = DataTransformer::probabilities($predictions, $this->targets);
         } else {
             $predictions = explode(PHP_EOL, trim($predictions));

tests/Clustering/FuzzyCMeansTest.php

@@ -16,7 +16,7 @@ class FuzzyCMeansTest extends TestCase
         $clusters = $fcm->cluster($samples);
         $this->assertCount(2, $clusters);
         foreach ($samples as $index => $sample) {
-            if (in_array($sample, $clusters[0]) || in_array($sample, $clusters[1])) {
+            if (in_array($sample, $clusters[0], true) || in_array($sample, $clusters[1], true)) {
                 unset($samples[$index]);
             }
         }

tests/Clustering/KMeansTest.php

@@ -20,7 +20,7 @@ class KMeansTest extends TestCase
         $this->assertCount(2, $clusters);
 
         foreach ($samples as $index => $sample) {
-            if (in_array($sample, $clusters[0]) || in_array($sample, $clusters[1])) {
+            if (in_array($sample, $clusters[0], true) || in_array($sample, $clusters[1], true)) {
                 unset($samples[$index]);
             }
         }

tests/Math/LinearAlgebra/EigenvalueDecompositionTest.php

@@ -8,7 +8,7 @@ use Phpml\Math\LinearAlgebra\EigenvalueDecomposition;
 use Phpml\Math\Matrix;
 use PHPUnit\Framework\TestCase;
 
-class EigenDecompositionTest extends TestCase
+class EigenvalueDecompositionTest extends TestCase
 {
     public function testSymmetricMatrixEigenPairs(): void
     {