Add rules for new cs-fixer

.php_cs

@@ -0,0 +1,16 @@
+<?php
+
+return PhpCsFixer\Config::create()
+    ->setRules([
+        '@PSR2' => true,
+        'declare_strict_types' => true,
+        'array_syntax' => ['syntax' => 'short'],
+        'blank_line_after_opening_tag' => true,
+        'single_blank_line_before_namespace' => true,
+    ])
+    ->setFinder(
+        PhpCsFixer\Finder::create()
+            ->in(__DIR__ . '/src')
+            ->in(__DIR__ . '/tests')
+    )->setRiskyAllowed(true)
+    ->setUsingCache(false);

src/Phpml/Association/Apriori.php

@@ -160,7 +160,7 @@ class Apriori implements Associator
         $results = [[]];
         foreach ($sample as $item) {
             foreach ($results as $combination) {
-                $results[] = array_merge(array($item), $combination);
+                $results[] = array_merge([$item], $combination);
             }
         }
 

src/Phpml/Classification/DecisionTree.php

@@ -19,20 +19,23 @@ class DecisionTree implements Classifier
     /**
      * @var array
      */
-    private $samples = array();
+    private $samples = [];
 
     /**
      * @var array
      */
     private $columnTypes;
+
     /**
      * @var array
      */
-    private $labels = array();
+    private $labels = [];
+
     /**
      * @var int
      */
     private $featureCount = 0;
+
     /**
      * @var DecisionTreeLeaf
      */
@@ -201,7 +204,7 @@ class DecisionTree implements Classifier
     {
         // Detect and convert continuous data column values into
         // discrete values by using the median as a threshold value
-        $columns = array();
+        $columns = [];
         for ($i=0; $i<$this->featureCount; $i++) {
             $values = array_column($samples, $i);
             if ($this->columnTypes[$i] == self::CONTINUOS) {

src/Phpml/Classification/DecisionTree/DecisionTreeLeaf.php

@@ -1,4 +1,5 @@
 <?php
+
 declare(strict_types=1);
 
 namespace Phpml\Classification\DecisionTree;

src/Phpml/Classification/NaiveBayes.php

@@ -150,7 +150,7 @@ class NaiveBayes implements Classifier
      */
     private function getSamplesByLabel($label)
     {
-        $samples = array();
+        $samples = [];
         for ($i=0; $i<$this->sampleCount; $i++) {
             if ($this->targets[$i] == $label) {
                 $samples[] = $this->samples[$i];
@@ -168,7 +168,7 @@ class NaiveBayes implements Classifier
         // Use NaiveBayes assumption for each label using:
         //	P(label|features) = P(label) * P(feature0|label) * P(feature1|label) .... P(featureN|label)
         // Then compare probability for each class to determine which label is most likely
-        $predictions = array();
+        $predictions = [];
         foreach ($this->labels as $label) {
             $p = $this->p[$label];
             for ($i=0; $i<$this->featureCount; $i++) {

src/Phpml/Clustering/FuzzyCMeans.php

@@ -1,4 +1,5 @@
 <?php
+
 declare(strict_types=1);
 
 namespace Phpml\Clustering;

src/Phpml/Clustering/KMeans/Cluster.php

@@ -50,10 +50,10 @@ class Cluster extends Point implements IteratorAggregate, Countable
      */
     public function toArray()
     {
-        return array(
+        return [
             'centroid' => parent::toArray(),
             'points' => $this->getPoints(),
-        );
+        ];
     }
 
     /**
@@ -143,5 +143,5 @@ class Cluster extends Point implements IteratorAggregate, Countable
     public function setCoordinates(array $newCoordinates)
     {
         $this->coordinates = $newCoordinates;
-    }    
+    }
 }

src/Phpml/Clustering/KMeans/Space.php

@@ -104,7 +104,7 @@ class Space extends SplObjectStorage
             }
         }
 
-        return array($min, $max);
+        return [$min, $max];
     }
 
     /**

src/Phpml/Math/Matrix.php

@@ -212,7 +212,7 @@ class Matrix
      */
     public function divideByScalar($value)
     {
-        $newMatrix = array();
+        $newMatrix = [];
         for ($i = 0; $i < $this->rows; ++$i) {
             for ($j = 0; $j < $this->columns; ++$j) {
                 $newMatrix[$i][$j] = $this->matrix[$i][$j] / $value;
@@ -233,7 +233,7 @@ class Matrix
             throw MatrixException::notSquareMatrix();
         }
 
-        $newMatrix = array();
+        $newMatrix = [];
         for ($i = 0; $i < $this->rows; ++$i) {
             for ($j = 0; $j < $this->columns; ++$j) {
                 $minor = $this->crossOut($i, $j)->getDeterminant();

tests/Phpml/Association/AprioriTest.php

@@ -176,7 +176,7 @@ class AprioriTest extends \PHPUnit_Framework_TestCase
      *
      * @return mixed
      */
-    public function invoke(&$object, $method, array $params = array())
+    public function invoke(&$object, $method, array $params = [])
     {
         $reflection = new \ReflectionClass(get_class($object));
         $method = $reflection->getMethod($method);

tests/Phpml/Clustering/FuzzyCMeansTest.php

@@ -1,4 +1,5 @@
 <?php
+
 declare(strict_types=1);
 
 namespace tests\Clustering;
@@ -10,7 +11,7 @@ class FuzzyCMeansTest extends \PHPUnit_Framework_TestCase
     public function testFCMSamplesClustering()
     {
         $samples = [[1, 1], [8, 7], [1, 2], [7, 8], [2, 1], [8, 9]];
-        $fcm = new FuzzyCMeans(2); 
+        $fcm = new FuzzyCMeans(2);
         $clusters = $fcm->cluster($samples);
         $this->assertCount(2, $clusters);
         foreach ($samples as $index => $sample) {
@@ -40,4 +41,4 @@ class FuzzyCMeansTest extends \PHPUnit_Framework_TestCase
             $this->assertEquals(1, array_sum($col));
         }
     }
-}
+}

tests/Phpml/Math/SetTest.php

@@ -1,4 +1,4 @@
-<?php
+<?php declare(strict_types=1);
 
 namespace tests\Phpml\Math;