php-ai / php-ml

src/Phpml/DimensionReduction/EigenTransformerBase.php

Spacing +2 added lines, -2 removed lines

@@ -1,4 +1,4 @@ 
-<?php declare(strict_types=1);
+<?php declare(strict_types = 1);
 
 namespace Phpml\DimensionReduction;
 
@@ -52,7 +52,7 @@ 
     {
         $eig = new EigenvalueDecomposition($matrix);
         $eigVals = $eig->getRealEigenvalues();
-        $eigVects= $eig->getEigenvectors();
+        $eigVects = $eig->getEigenvectors();
 
         $totalEigVal = array_sum($eigVals);
         // Sort eigenvalues in descending order

src/Phpml/DimensionReduction/PCA.php

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\DimensionReduction;
 
@@ -86,7 +86,7 @@ 
     {
         // Calculate means for each dimension
         $this->means = [];
-        for ($i=0; $i < $n; $i++) {
+        for ($i = 0; $i < $n; $i++) {
             $column = array_column($data, $i);
             $this->means[] = Mean::arithmetic($column);
         }
@@ -109,7 +109,7 @@ 
 
         // Normalize data
         foreach ($data as $i => $row) {
-            for ($k=0; $k < $n; $k++) {
+            for ($k = 0; $k < $n; $k++) {
                 $data[$i][$k] -= $this->means[$k];
             }
         }
@@ -131,7 +131,7 @@ 
             throw new \Exception("PCA has not been fitted with respect to original dataset, please run PCA::fit() first");
         }
 
-        if (! is_array($sample[0])) {
+        if (!is_array($sample[0])) {
             $sample = [$sample];
         }
 

src/Phpml/DimensionReduction/LDA.php

Spacing +6 added lines, -6 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\DimensionReduction;
 
@@ -119,21 +119,21 @@ 
     protected function calculateMeans($data, $classes) : array
     {
         $means = [];
-        $counts= [];
+        $counts = [];
         $overallMean = array_fill(0, count($data[0]), 0.0);
 
         foreach ($data as $index => $row) {
             $label = array_search($classes[$index], $this->labels);
 
             foreach ($row as $col => $val) {
-                if (! isset($means[$label][$col])) {
+                if (!isset($means[$label][$col])) {
                     $means[$label][$col] = 0.0;
                 }
                 $means[$label][$col] += $val;
                 $overallMean[$col] += $val;
             }
 
-            if (! isset($counts[$label])) {
+            if (!isset($counts[$label])) {
                 $counts[$label] = 0;
             }
             $counts[$label]++;
@@ -147,7 +147,7 @@ 
 
         // Calculate overall mean of the dataset for each column
         $numElements = array_sum($counts);
-        $map = function ($el) use ($numElements) {
+        $map = function($el) use ($numElements) {
             return $el / $numElements;
         };
         $this->overallMean = array_map($map, $overallMean);
@@ -238,7 +238,7 @@ 
             throw new \Exception("LDA has not been fitted with respect to original dataset, please run LDA::fit() first");
         }
 
-        if (! is_array($sample[0])) {
+        if (!is_array($sample[0])) {
             $sample = [$sample];
         }