Update dev dependencies (#187)

* composer: update dev dependencies

* phpstan fixes

* phpstan fixes

* phpstan fixes

* phpstan fixes

* drop probably forgotten humbug configs

* apply cs

* fix cs bug

* compsoer: add coding standard and phsptan dev friendly scripts

* ecs: add skipped errors

* cs: fix PHP 7.1

* fix cs

* ecs: exclude strict fixer that break code

* ecs: cleanup commented sets

* travis: use composer scripts for testing to prevent duplicated setup

.gitignore

@@ -1,4 +1,3 @@
 /vendor/
-humbuglog.*
 .php_cs.cache
 /build

.travis.yml

@@ -30,8 +30,8 @@ install:
 
 script:
   - vendor/bin/phpunit $PHPUNIT_FLAGS
-  - if [[ $STATIC_ANALYSIS != "" ]]; then vendor/bin/ecs check src tests; fi
+  - if [[ $STATIC_ANALYSIS != "" ]]; then composer check-cs; fi
-  - if [[ $STATIC_ANALYSIS != "" ]]; then vendor/bin/phpstan.phar analyse src tests --level max --configuration phpstan.neon; fi
+  - if [[ $STATIC_ANALYSIS != "" ]]; then composer phpstan; fi
 
 after_success:
   - |

composer.json

@@ -15,11 +15,10 @@
         "php": "^7.1"
     },
     "require-dev": {
-        "phpunit/phpunit": "^6.4",
+        "phpunit/phpunit": "^6.5",
-        "symplify/easy-coding-standard": "v3.0.0-RC3",
+        "symplify/easy-coding-standard": "^3.1",
-        "symplify/coding-standard": "v3.0.0-RC3",
+        "symplify/coding-standard": "^3.1",
-        "symplify/package-builder": "v3.0.0-RC3",
+        "phpstan/phpstan-shim": "^0.9"
-        "phpstan/phpstan-shim": "^0.8"
     },
     "autoload": {
         "psr-4": {
@@ -30,5 +29,10 @@
         "psr-4": {
             "Phpml\\Tests\\": "tests/Phpml"
         }
+    },
+    "scripts": {
+        "check-cs": "vendor/bin/ecs check src tests bin",
+        "fix-cs": "vendor/bin/ecs check src tests bin --fix",
+        "phpstan": "vendor/bin/phpstan.phar analyse src tests bin --level max --configuration phpstan.neon"
     }
 }

easy-coding-standard.neon

@@ -1,14 +1,8 @@
 includes:
     - vendor/symplify/easy-coding-standard/config/psr2.neon
-    - vendor/symplify/easy-coding-standard/config/php70.neon
+    - vendor/symplify/easy-coding-standard/config/php71.neon
     - vendor/symplify/easy-coding-standard/config/clean-code.neon
-    - vendor/symplify/easy-coding-standard/config/common/array.neon
+    - vendor/symplify/easy-coding-standard/config/common.neon
-    - vendor/symplify/easy-coding-standard/config/common/docblock.neon
-    - vendor/symplify/easy-coding-standard/config/common/namespaces.neon
-    - vendor/symplify/easy-coding-standard/config/common/control-structures.neon
-
-    # many errors, need help
-    #- vendor/symplify/easy-coding-standard/config/common/strict.neon
 
 checkers:
     # spacing
@@ -33,13 +27,16 @@ checkers:
     - Symplify\CodingStandard\Fixer\Import\ImportNamespacedNameFixer
     - Symplify\CodingStandard\Fixer\Php\ClassStringToClassConstantFixer
     - Symplify\CodingStandard\Fixer\Property\ArrayPropertyDefaultValueFixer
-    - Symplify\CodingStandard\Fixer\ClassNotation\PropertyAndConstantSeparationFixer
     - Symplify\CodingStandard\Fixer\ArrayNotation\StandaloneLineInMultilineArrayFixer
 
 parameters:
     exclude_checkers:
         # from strict.neon
         - PhpCsFixer\Fixer\PhpUnit\PhpUnitStrictFixer
+        - PhpCsFixer\Fixer\Strict\StrictComparisonFixer
+        # personal prefference
+        - PhpCsFixer\Fixer\Operator\NotOperatorWithSuccessorSpaceFixer
+
     skip:
         PhpCsFixer\Fixer\Alias\RandomApiMigrationFixer:
             # random_int() breaks code
@@ -47,6 +44,15 @@ parameters:
         SlevomatCodingStandard\Sniffs\Classes\UnusedPrivateElementsSniff:
             # magic calls
             - src/Phpml/Preprocessing/Normalizer.php
+        PhpCsFixer\Fixer\StringNotation\ExplicitStringVariableFixer:
+            # bugged
+            - src/Phpml/Classification/DecisionTree/DecisionTreeLeaf.php
+        Symplify\CodingStandard\Fixer\Commenting\RemoveUselessDocBlockFixer:
+            # bug in fixer
+            - src/Phpml/Math/LinearAlgebra/LUDecomposition.php
+        PhpCsFixer\Fixer\FunctionNotation\VoidReturnFixer:
+            # covariant return types
+            - src/Phpml/Classification/Linear/Perceptron.php
 
     skip_codes:
         # missing typehints
@@ -56,3 +62,4 @@ parameters:
         - SlevomatCodingStandard\Sniffs\TypeHints\TypeHintDeclarationSniff.MissingTraversableReturnTypeHintSpecification
         - SlevomatCodingStandard\Sniffs\TypeHints\TypeHintDeclarationSniff.MissingPropertyTypeHint
         - SlevomatCodingStandard\Sniffs\TypeHints\TypeHintDeclarationSniff.MissingTraversablePropertyTypeHintSpecification
+        - PHP_CodeSniffer\Standards\Generic\Sniffs\CodeAnalysis\AssignmentInConditionSniff.Found

humbug.json.dist

@@ -1,11 +0,0 @@
-{
-    "source": {
-        "directories": [
-            "src"
-        ]
-    },
-    "timeout": 10,
-    "logs": {
-        "text": "humbuglog.txt"
-    }
-}

phpstan.neon

@@ -1,19 +1,15 @@
 parameters:
     ignoreErrors:
         - '#Phpml\\Dataset\\FilesDataset::__construct\(\) does not call parent constructor from Phpml\\Dataset\\ArrayDataset#'
-        - '#Parameter \#2 \$predictedLabels of static method Phpml\\Metric\\Accuracy::score\(\) expects mixed\[\], mixed\[\]\|string given#'
 
-        # should be always defined
+        # mocks
-        - '#Undefined variable: \$j#'
+        - '#PHPUnit_Framework_MockObject_MockObject#'
 
-        # bugged
+        # wide range cases
-        - '#expects [a-z\\\|\[\]]*, [a-z\\\|\(\)\[\]]*\[\] given#'
+        - '#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#'
-        # mock
-        - '#Parameter \#1 \$node of class Phpml\\NeuralNetwork\\Node\\Neuron\\Synapse constructor expects Phpml\\NeuralNetwork\\Node, Phpml\\NeuralNetwork\\Node\\Neuron\|PHPUnit_Framework_MockObject_MockObject given#'
-        - '#Parameter \#1 \$(activationFunction|synapse) of class Phpml\\NeuralNetwork\\Node\\Neuron constructor expects Phpml\\NeuralNetwork\\ActivationFunction|null, Phpml\\NeuralNetwork\\ActivationFunction\\BinaryStep|PHPUnit_Framework_MockObject_MockObject 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#'
-        - '#Method Phpml\\Classification\\Linear\\DecisionStump::getBestNumericalSplit\(\) should return mixed\[\] but returns \(float\|int\|mixed\|string\)\[\]\|null#'
+        - '#Call to an undefined method Phpml\\Helper\\Optimizer\\Optimizer::getCostValues\(\)#'
-        - '#Method Phpml\\Classification\\Linear\\DecisionStump::getBestNominalSplit\(\) should return mixed\[\] but returns mixed\[\]\|null#'

src/Phpml/Classification/DecisionTree.php

@@ -64,9 +64,9 @@ class DecisionTree implements Classifier
     private $featureImportances;
 
     /**
-     * @var array|null
+     * @var array
      */
-    private $columnNames;
+    private $columnNames = [];
 
     public function __construct(int $maxDepth = 10)
     {
@@ -89,7 +89,7 @@ class DecisionTree implements Classifier
 
         // If column names are given or computed before, then there is no
         // need to init it and accidentally remove the previous given names
-        if ($this->columnNames === null) {
+        if ($this->columnNames === []) {
             $this->columnNames = range(0, $this->featureCount - 1);
         } elseif (count($this->columnNames) > $this->featureCount) {
             $this->columnNames = array_slice($this->columnNames, 0, $this->featureCount);
@@ -380,9 +380,9 @@ class DecisionTree implements Classifier
                 $median = Mean::median($values);
                 foreach ($values as &$value) {
                     if ($value <= $median) {
-                        $value = "<= $median";
+                        $value = "<= ${median}";
                     } else {
-                        $value = "> $median";
+                        $value = "> ${median}";
                     }
                 }
             }

src/Phpml/Classification/DecisionTree/DecisionTreeLeaf.php

@@ -122,7 +122,7 @@ class DecisionTreeLeaf
     public function getHTML($columnNames = null): string
     {
         if ($this->isTerminal) {
-            $value = "<b>$this->classValue</b>";
+            $value = "<b>${this}->classValue</b>";
         } else {
             $value = $this->value;
             if ($columnNames !== null) {
@@ -132,13 +132,13 @@ class DecisionTreeLeaf
             }
 
             if (!preg_match('/^[<>=]{1,2}/', (string) $value)) {
-                $value = "=$value";
+                $value = "=${value}";
             }
 
-            $value = "<b>$col $value</b><br>Gini: ".number_format($this->giniIndex, 2);
+            $value = "<b>${col} ${value}</b><br>Gini: ".number_format($this->giniIndex, 2);
         }
 
-        $str = "<table ><tr><td colspan=3 align=center style='border:1px solid;'>$value</td></tr>";
+        $str = "<table ><tr><td colspan=3 align=center style='border:1px solid;'>${value}</td></tr>";
 
         if ($this->leftLeaf || $this->rightLeaf) {
             $str .= '<tr>';

src/Phpml/Classification/Linear/DecisionStump.php

@@ -86,7 +86,7 @@ class DecisionStump extends WeightedClassifier
 
     public function __toString(): string
     {
-        return "IF $this->column $this->operator $this->value ".
+        return "IF ${this}->column ${this}->operator ${this}->value ".
             'THEN '.$this->binaryLabels[0].' '.
             'ELSE '.$this->binaryLabels[1];
     }
@@ -176,14 +176,14 @@ class DecisionStump extends WeightedClassifier
         $maxValue = max($values);
         $stepSize = ($maxValue - $minValue) / $this->numSplitCount;
 
-        $split = null;
+        $split = [];
 
         foreach (['<=', '>'] as $operator) {
             // Before trying all possible split points, let's first try
             // the average value for the cut point
             $threshold = array_sum($values) / (float) count($values);
             [$errorRate, $prob] = $this->calculateErrorRate($targets, $threshold, $operator, $values);
-            if ($split == null || $errorRate < $split['trainingErrorRate']) {
+            if ($split === [] || $errorRate < $split['trainingErrorRate']) {
                 $split = [
                     'value' => $threshold,
                     'operator' => $operator,
@@ -218,13 +218,13 @@ class DecisionStump extends WeightedClassifier
         $valueCounts = array_count_values($values);
         $distinctVals = array_keys($valueCounts);
 
-        $split = null;
+        $split = [];
 
         foreach (['=', '!='] as $operator) {
             foreach ($distinctVals as $val) {
                 [$errorRate, $prob] = $this->calculateErrorRate($targets, $val, $operator, $values);
 
-                if ($split === null || $split['trainingErrorRate'] < $errorRate) {
+                if ($split === [] || $split['trainingErrorRate'] < $errorRate) {
                     $split = [
                         'value' => $val,
                         'operator' => $operator,

src/Phpml/Classification/Linear/Perceptron.php

@@ -34,7 +34,7 @@ class Perceptron implements Classifier, IncrementalEstimator
     protected $featureCount = 0;
 
     /**
-     * @var array|null
+     * @var array
      */
     protected $weights = [];
 
@@ -146,7 +146,7 @@ class Perceptron implements Classifier, IncrementalEstimator
         $this->labels = [];
         $this->optimizer = null;
         $this->featureCount = 0;
-        $this->weights = null;
+        $this->weights = [];
         $this->costValues = [];
     }
 
@@ -174,7 +174,7 @@ class Perceptron implements Classifier, IncrementalEstimator
      * Executes a Gradient Descent algorithm for
      * the given cost function
      */
-    protected function runGradientDescent(array $samples, array $targets, Closure $gradientFunc, bool $isBatch = false): void
+    protected function runGradientDescent(array $samples, array $targets, Closure $gradientFunc, bool $isBatch = false)
     {
         $class = $isBatch ? GD::class : StochasticGD::class;
 

src/Phpml/Clustering/FuzzyCMeans.php

@@ -78,7 +78,7 @@ class FuzzyCMeans implements Clusterer
     }
 
     /**
-     * @param array|Point[] $samples
+     * @param Point[]|int[][] $samples
      */
     public function cluster(array $samples): array
     {

src/Phpml/FeatureExtraction/StopWords.php

@@ -25,7 +25,7 @@ class StopWords
 
     public static function factory(string $language = 'English'): self
     {
-        $className = __NAMESPACE__."\\StopWords\\$language";
+        $className = __NAMESPACE__."\\StopWords\\${language}";
 
         if (!class_exists($className)) {
             throw InvalidArgumentException::invalidStopWordsLanguage($language);

src/Phpml/Helper/OneVsRest.php

@@ -164,7 +164,7 @@ trait OneVsRest
      */
     private function binarizeTargets(array $targets, $label): array
     {
-        $notLabel = "not_$label";
+        $notLabel = "not_${label}";
         foreach ($targets as $key => $target) {
             $targets[$key] = $target == $label ? $label : $notLabel;
         }

src/Phpml/Helper/Optimizer/Optimizer.php

@@ -47,7 +47,7 @@ abstract class Optimizer
     public function setInitialTheta(array $theta)
     {
         if (count($theta) != $this->dimensions) {
-            throw new Exception("Number of values in the weights array should be $this->dimensions");
+            throw new Exception("Number of values in the weights array should be ${this}->dimensions");
         }
 
         $this->theta = $theta;

src/Phpml/Math/Set.php

@@ -10,7 +10,7 @@ use IteratorAggregate;
 class Set implements IteratorAggregate
 {
     /**
-     * @var string[]|int[]|float[]
+     * @var string[]|int[]|float[]|bool[]
      */
     private $elements = [];
 
@@ -135,7 +135,7 @@ class Set implements IteratorAggregate
     }
 
     /**
-     * @return string[]|int[]|float[]
+     * @return string[]|int[]|float[]|bool[]
      */
     public function toArray(): array
     {
@@ -160,9 +160,9 @@ class Set implements IteratorAggregate
     /**
      * Removes duplicates and rewrites index.
      *
-     * @param string[]|int[]|float[] $elements
+     * @param string[]|int[]|float[]|bool[] $elements
      *
-     * @return string[]|int[]|float[]
+     * @return string[]|int[]|float[]|bool[]
      */
     private static function sanitize(array $elements): array
     {

src/Phpml/NeuralNetwork/Training/Backpropagation.php

@@ -15,14 +15,14 @@ class Backpropagation
     private $learningRate;
 
     /**
-     * @var array|null
+     * @var array
      */
-    private $sigmas;
+    private $sigmas = [];
 
     /**
-     * @var array|null
+     * @var array
      */
-    private $prevSigmas;
+    private $prevSigmas = [];
 
     public function __construct(float $learningRate)
     {
@@ -57,8 +57,8 @@ class Backpropagation
         }
 
         // Clean some memory (also it helps make MLP persistency & children more maintainable).
-        $this->sigmas = null;
+        $this->sigmas = [];
-        $this->prevSigmas = null;
+        $this->prevSigmas = [];
     }
 
     private function getSigma(Neuron $neuron, int $targetClass, int $key, bool $lastLayer): float

src/Phpml/Regression/LeastSquares.php

@@ -10,6 +10,7 @@ use Phpml\Math\Matrix;
 class LeastSquares implements Regression
 {
     use Predictable;
+
     /**
      * @var array
      */

tests/Phpml/Classification/Linear/LogisticRegressionTest.php

@@ -2,7 +2,7 @@
 
 declare(strict_types=1);
 
-namespace tests\Phpml\Classification\Linear;
+namespace Phpml\Tests\Classification\Linear;
 
 use Phpml\Classification\Linear\LogisticRegression;
 use PHPUnit\Framework\TestCase;
@@ -55,12 +55,12 @@ class LogisticRegressionTest extends TestCase
 
         $zero = $method->invoke($predictor, [0.1, 0.1], 0);
         $one = $method->invoke($predictor, [0.1, 0.1], 1);
-        $this->assertEquals(1, $zero + $one, null, 1e-6);
+        $this->assertEquals(1, $zero + $one, '', 1e-6);
         $this->assertTrue($zero > $one);
 
         $zero = $method->invoke($predictor, [0.9, 0.9], 0);
         $one = $method->invoke($predictor, [0.9, 0.9], 1);
-        $this->assertEquals(1, $zero + $one, null, 1e-6);
+        $this->assertEquals(1, $zero + $one, '', 1e-6);
         $this->assertTrue($zero < $one);
     }
 
@@ -97,9 +97,9 @@ class LogisticRegressionTest extends TestCase
         $two = $method->invoke($predictor, [3.0, 9.5], 2);
         $not_two = $method->invoke($predictor, [3.0, 9.5], 'not_2');
 
-        $this->assertEquals(1, $zero + $not_zero, null, 1e-6);
+        $this->assertEquals(1, $zero + $not_zero, '', 1e-6);
-        $this->assertEquals(1, $one + $not_one, null, 1e-6);
+        $this->assertEquals(1, $one + $not_one, '', 1e-6);
-        $this->assertEquals(1, $two + $not_two, null, 1e-6);
+        $this->assertEquals(1, $two + $not_two, '', 1e-6);
         $this->assertTrue($zero < $two);
         $this->assertTrue($one < $two);
     }

tests/Phpml/Metric/AccuracyTest.php

@@ -45,7 +45,7 @@ class AccuracyTest extends TestCase
         $classifier = new SVC(Kernel::RBF);
         $classifier->train($dataset->getTrainSamples(), $dataset->getTrainLabels());
 
-        $predicted = $classifier->predict($dataset->getTestSamples());
+        $predicted = (array) $classifier->predict($dataset->getTestSamples());
 
         $accuracy = Accuracy::score($dataset->getTestLabels(), $predicted);
 

tests/Phpml/NeuralNetwork/Network/MultilayerPerceptronTest.php

@@ -2,7 +2,7 @@
 
 declare(strict_types=1);
 
-namespace tests\Phpml\NeuralNetwork\Network;
+namespace Phpml\Tests\NeuralNetwork\Network;
 
 use Phpml\NeuralNetwork\Network\MultilayerPerceptron;
 use PHPUnit\Framework\TestCase;
@@ -11,6 +11,7 @@ class MultilayerPerceptronTest extends TestCase
 {
     public function testLearningRateSetter(): void
     {
+        /** @var MultilayerPerceptron $mlp */
         $mlp = $this->getMockForAbstractClass(
             MultilayerPerceptron::class,
             [5, [3], [0, 1], 1000, null, 0.42]