92 lines
1.9 KiB
PHP
92 lines
1.9 KiB
PHP
<?php
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declare(strict_types=1);
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namespace Phpml\Preprocessing;
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use Phpml\Exception\NormalizerException;
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class Normalizer implements Preprocessor
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{
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const NORM_L1 = 1;
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const NORM_L2 = 2;
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/**
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* @var int
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*/
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private $norm;
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/**
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* @param int $norm
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*
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* @throws NormalizerException
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*/
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public function __construct(int $norm = self::NORM_L2)
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{
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if (!in_array($norm, [self::NORM_L1, self::NORM_L2])) {
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throw NormalizerException::unknownNorm();
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}
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$this->norm = $norm;
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}
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/**
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* @param array $samples
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*/
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public function fit(array $samples)
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{
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// intentionally not implemented
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}
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/**
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* @param array $samples
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*/
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public function transform(array &$samples)
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{
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$method = sprintf('normalizeL%s', $this->norm);
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foreach ($samples as &$sample) {
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$this->$method($sample);
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}
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}
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/**
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* @param array $sample
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*/
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private function normalizeL1(array &$sample)
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{
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$norm1 = 0;
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foreach ($sample as $feature) {
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$norm1 += abs($feature);
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}
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if (0 == $norm1) {
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$count = count($sample);
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$sample = array_fill(0, $count, 1.0 / $count);
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} else {
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foreach ($sample as &$feature) {
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$feature = $feature / $norm1;
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}
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}
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}
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/**
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* @param array $sample
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*/
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private function normalizeL2(array &$sample)
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{
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$norm2 = 0;
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foreach ($sample as $feature) {
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$norm2 += $feature * $feature;
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}
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$norm2 = sqrt(floatval($norm2));
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if (0 == $norm2) {
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$sample = array_fill(0, count($sample), 1);
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} else {
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foreach ($sample as &$feature) {
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$feature = $feature / $norm2;
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}
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}
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}
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}
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