php-ai / php-ml

src/Phpml/Classification/Linear/Adaline.php

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Linear;
 
@@ -9,12 +9,12 @@ 
     /**
      * Batch training is the default Adaline training algorithm
      */
-    const BATCH_TRAINING    = 1;
+    const BATCH_TRAINING = 1;
 
     /**
      * Online training: Stochastic gradient descent learning
      */
-    const ONLINE_TRAINING    = 2;
+    const ONLINE_TRAINING = 2;
 
     /**
      * Training type may be either 'Batch' or 'Online' learning
@@ -61,7 +61,7 @@ 
     protected function runTraining(array $samples, array $targets)
     {
         // The cost function is the sum of squares
-        $callback = function ($weights, $sample, $target) {
+        $callback = function($weights, $sample, $target) {
             $this->weights = $weights;
 
             $output = $this->output($sample);

src/Phpml/Classification/Linear/Perceptron.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Linear;
 
@@ -170,7 +170,7 @@ 
     protected function runTraining(array $samples, array $targets)
     {
         // The cost function is the sum of squares
-        $callback = function ($weights, $sample, $target) {
+        $callback = function($weights, $sample, $target) {
             $this->weights = $weights;
 
             $prediction = $this->outputClass($sample);

Indentation +4 added lines, -4 removed lines

@@ -100,10 +100,10 @@
     }
 
     /**
-      * @param array $samples
-      * @param array $targets
-      * @param array $labels
-      */
+     * @param array $samples
+     * @param array $targets
+     * @param array $labels
+     */
     public function trainBinary(array $samples, array $targets, array $labels)
     {
         if ($this->normalizer) {

src/Phpml/Classification/Ensemble/AdaBoost.php

Spacing +5 added lines, -5 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 
@@ -175,14 +175,14 @@ 
     {
         $weights = $this->weights;
         $std = StandardDeviation::population($weights);
-        $mean= Mean::arithmetic($weights);
+        $mean = Mean::arithmetic($weights);
         $min = min($weights);
-        $minZ= (int)round(($min - $mean) / $std);
+        $minZ = (int) round(($min - $mean) / $std);
 
         $samples = [];
         $targets = [];
         foreach ($weights as $index => $weight) {
-            $z = (int)round(($weight - $mean) / $std) - $minZ + 1;
+            $z = (int) round(($weight - $mean) / $std) - $minZ + 1;
             for ($i = 0; $i < $z; ++$i) {
                 if (rand(0, 1) == 0) {
                     continue;
@@ -264,6 +264,6 @@ 
             $sum += $h * $alpha;
         }
 
-        return $this->labels[ $sum > 0 ? 1 : -1];
+        return $this->labels[$sum > 0 ? 1 : -1];
     }
 }

src/Phpml/Classification/Ensemble/Bagging.php

Spacing +1 added lines, -1 removed lines

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 

src/Phpml/Classification/Ensemble/RandomForest.php

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 
@@ -137,11 +137,11 @@ 
     protected function initSingleClassifier($classifier)
     {
         if (is_float($this->featureSubsetRatio)) {
-            $featureCount = (int)($this->featureSubsetRatio * $this->featureCount);
+            $featureCount = (int) ($this->featureSubsetRatio * $this->featureCount);
         } elseif ($this->featureCount == 'sqrt') {
-            $featureCount = (int)sqrt($this->featureCount) + 1;
+            $featureCount = (int) sqrt($this->featureCount) + 1;
         } else {
-            $featureCount = (int)log($this->featureCount, 2) + 1;
+            $featureCount = (int) log($this->featureCount, 2) + 1;
         }
 
         if ($featureCount >= $this->featureCount) {

src/Phpml/Classification/DecisionTree/DecisionTreeLeaf.php

Spacing +13 added lines, -13 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\DecisionTree;
 
@@ -34,7 +34,7 @@ 
     /**
      * @var DecisionTreeLeaf
      */
-    public $rightLeaf= null;
+    public $rightLeaf = null;
 
     /**
      * @var array
@@ -79,7 +79,7 @@ 
 
         if ($this->isContinuous) {
             $op = $this->operator;
-            $value= $this->numericValue;
+            $value = $this->numericValue;
             $recordField = strval($recordField);
             eval("\$result = $recordField $op $value;");
             return $result;
@@ -102,16 +102,16 @@ 
             return 0.0;
         }
 
-        $nodeSampleCount = (float)count($this->records);
+        $nodeSampleCount = (float) count($this->records);
         $iT = $this->giniIndex;
 
         if ($this->leftLeaf) {
-            $pL = count($this->leftLeaf->records)/$nodeSampleCount;
+            $pL = count($this->leftLeaf->records) / $nodeSampleCount;
             $iT -= $pL * $this->leftLeaf->giniIndex;
         }
 
         if ($this->rightLeaf) {
-            $pR = count($this->rightLeaf->records)/$nodeSampleCount;
+            $pR = count($this->rightLeaf->records) / $nodeSampleCount;
             $iT -= $pR * $this->rightLeaf->giniIndex;
         }
 
@@ -138,22 +138,22 @@ 
             if (!preg_match("/^[<>=]{1,2}/", $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;'>
 				$value</td></tr>";
         if ($this->leftLeaf || $this->rightLeaf) {
-            $str .='<tr>';
+            $str .= '<tr>';
             if ($this->leftLeaf) {
-                $str .="<td valign=top><b>| Yes</b><br>" . $this->leftLeaf->getHTML($columnNames) . "</td>";
+                $str .= "<td valign=top><b>| Yes</b><br>".$this->leftLeaf->getHTML($columnNames)."</td>";
             } else {
-                $str .='<td></td>';
+                $str .= '<td></td>';
             }
-            $str .='<td>&nbsp;</td>';
+            $str .= '<td>&nbsp;</td>';
             if ($this->rightLeaf) {
-                $str .="<td valign=top align=right><b>No |</b><br>" . $this->rightLeaf->getHTML($columnNames) . "</td>";
+                $str .= "<td valign=top align=right><b>No |</b><br>".$this->rightLeaf->getHTML($columnNames)."</td>";
             } else {
-                $str .='<td></td>';
+                $str .= '<td></td>';
             }
             $str .= '</tr>';
         }

src/Phpml/Classification/DecisionTree.php

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification;
 
@@ -143,7 +143,7 @@ 
         // otherwise group the records so that we can classify the leaf
         // in case maximum depth is reached
         $leftRecords = [];
-        $rightRecords= [];
+        $rightRecords = [];
         $remainingTargets = [];
         $prevRecord = null;
         $allSame = true;
@@ -161,7 +161,7 @@ 
             if ($split->evaluate($record)) {
                 $leftRecords[] = $recordNo;
             } else {
-                $rightRecords[]= $recordNo;
+                $rightRecords[] = $recordNo;
             }
 
             // Group remaining targets
@@ -182,7 +182,7 @@ 
                 $split->leftLeaf = $this->getSplitLeaf($leftRecords, $depth + 1);
             }
             if ($rightRecords) {
-                $split->rightLeaf= $this->getSplitLeaf($rightRecords, $depth + 1);
+                $split->rightLeaf = $this->getSplitLeaf($rightRecords, $depth + 1);
             }
         }
 

src/Phpml/Clustering/FuzzyCMeans.php

Spacing +3 added lines, -3 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Clustering;
 
@@ -101,7 +101,7 @@ 
                 $total += $val;
             }
 
-            $this->membership[] = array_map(function ($val) use ($total) {
+            $this->membership[] = array_map(function($val) use ($total) {
                 return $val / $total;
             }, $row);
         }
@@ -218,7 +218,7 @@ 
     {
         // Initialize variables, clusters and membership matrix
         $this->sampleCount = count($samples);
-        $this->samples =& $samples;
+        $this->samples = & $samples;
         $this->space = new Space(count($samples[0]));
         $this->initClusters();
 

src/Phpml/Helper/Optimizer/GD.php

Spacing +3 added lines, -3 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Helper\Optimizer;
 
@@ -42,7 +42,7 @@ 
 
             $this->updateWeightsWithUpdates($updates, $totalPenalty);
 
-            $this->costValues[] = array_sum($errors)/$this->sampleCount;
+            $this->costValues[] = array_sum($errors) / $this->sampleCount;
 
             if ($this->earlyStop($theta)) {
                 break;
@@ -65,7 +65,7 @@ 
     protected function gradient(array $theta)
     {
         $costs = [];
-        $gradient= [];
+        $gradient = [];
         $totalPenalty = 0;
 
         foreach ($this->samples as $index => $sample) {