Differences Between: [Versions 311 and 400] [Versions 311 and 401] [Versions 311 and 402] [Versions 311 and 403]
1 <?php 2 3 declare(strict_types=1); 4 5 namespace Phpml\Preprocessing; 6 7 use Phpml\Exception\NormalizerException; 8 use Phpml\Math\Statistic\Mean; 9 use Phpml\Math\Statistic\StandardDeviation; 10 11 class Normalizer implements Preprocessor 12 { 13 public const NORM_L1 = 1; 14 15 public const NORM_L2 = 2; 16 17 public const NORM_STD = 3; 18 19 /** 20 * @var int 21 */ 22 private $norm; 23 24 /** 25 * @var bool 26 */ 27 private $fitted = false; 28 29 /** 30 * @var array 31 */ 32 private $std = []; 33 34 /** 35 * @var array 36 */ 37 private $mean = []; 38 39 /** 40 * @throws NormalizerException 41 */ 42 public function __construct(int $norm = self::NORM_L2) 43 { 44 if (!in_array($norm, [self::NORM_L1, self::NORM_L2, self::NORM_STD], true)) { 45 throw new NormalizerException('Unknown norm supplied.'); 46 } 47 48 $this->norm = $norm; 49 } 50 51 public function fit(array $samples, ?array $targets = null): void 52 { 53 if ($this->fitted) { 54 return; 55 } 56 57 if ($this->norm === self::NORM_STD) { 58 $features = range(0, count($samples[0]) - 1); 59 foreach ($features as $i) { 60 $values = array_column($samples, $i); 61 $this->std[$i] = StandardDeviation::population($values); 62 $this->mean[$i] = Mean::arithmetic($values); 63 } 64 } 65 66 $this->fitted = true; 67 } 68 69 public function transform(array &$samples): void 70 { 71 $methods = [ 72 self::NORM_L1 => 'normalizeL1', 73 self::NORM_L2 => 'normalizeL2', 74 self::NORM_STD => 'normalizeSTD', 75 ]; 76 $method = $methods[$this->norm]; 77 78 $this->fit($samples); 79 80 foreach ($samples as &$sample) { 81 $this->{$method}($sample); 82 } 83 } 84 85 private function normalizeL1(array &$sample): void 86 { 87 $norm1 = 0; 88 foreach ($sample as $feature) { 89 $norm1 += abs($feature); 90 } 91 92 if ($norm1 == 0) { 93 $count = count($sample); 94 $sample = array_fill(0, $count, 1.0 / $count); 95 } else { 96 array_walk($sample, function (&$feature) use ($norm1): void { 97 $feature /= $norm1; 98 }); 99 } 100 } 101 102 private function normalizeL2(array &$sample): void 103 { 104 $norm2 = 0; 105 foreach ($sample as $feature) { 106 $norm2 += $feature * $feature; 107 } 108 109 $norm2 **= .5; 110 111 if ($norm2 == 0) { 112 $sample = array_fill(0, count($sample), 1); 113 } else { 114 array_walk($sample, function (&$feature) use ($norm2): void { 115 $feature /= $norm2; 116 }); 117 } 118 } 119 120 private function normalizeSTD(array &$sample): void 121 { 122 foreach (array_keys($sample) as $i) { 123 if ($this->std[$i] != 0) { 124 $sample[$i] = ($sample[$i] - $this->mean[$i]) / $this->std[$i]; 125 } else { 126 // Same value for all samples. 127 $sample[$i] = 0; 128 } 129 } 130 } 131 }
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