Current Path : /var/www/ljmtc/cbt/lib/mlbackend/php/phpml/src/Phpml/Clustering/ |
Current File : /var/www/ljmtc/cbt/lib/mlbackend/php/phpml/src/Phpml/Clustering/DBSCAN.php |
<?php declare(strict_types=1); namespace Phpml\Clustering; use Phpml\Math\Distance; use Phpml\Math\Distance\Euclidean; class DBSCAN implements Clusterer { private const NOISE = -1; /** * @var float */ private $epsilon; /** * @var int */ private $minSamples; /** * @var Distance */ private $distanceMetric; public function __construct(float $epsilon = 0.5, int $minSamples = 3, ?Distance $distanceMetric = null) { if ($distanceMetric === null) { $distanceMetric = new Euclidean(); } $this->epsilon = $epsilon; $this->minSamples = $minSamples; $this->distanceMetric = $distanceMetric; } public function cluster(array $samples): array { $labels = []; $n = 0; foreach ($samples as $index => $sample) { if (isset($labels[$index])) { continue; } $neighborIndices = $this->getIndicesInRegion($sample, $samples); if (count($neighborIndices) < $this->minSamples) { $labels[$index] = self::NOISE; continue; } $labels[$index] = $n; $this->expandCluster($samples, $neighborIndices, $labels, $n); ++$n; } return $this->groupByCluster($samples, $labels, $n); } private function expandCluster(array $samples, array $seeds, array &$labels, int $n): void { while (($index = array_pop($seeds)) !== null) { if (isset($labels[$index])) { if ($labels[$index] === self::NOISE) { $labels[$index] = $n; } continue; } $labels[$index] = $n; $sample = $samples[$index]; $neighborIndices = $this->getIndicesInRegion($sample, $samples); if (count($neighborIndices) >= $this->minSamples) { $seeds = array_unique(array_merge($seeds, $neighborIndices)); } } } private function getIndicesInRegion(array $center, array $samples): array { $indices = []; foreach ($samples as $index => $sample) { if ($this->distanceMetric->distance($center, $sample) < $this->epsilon) { $indices[] = $index; } } return $indices; } private function groupByCluster(array $samples, array $labels, int $n): array { $clusters = array_fill(0, $n, []); foreach ($samples as $index => $sample) { if ($labels[$index] !== self::NOISE) { $clusters[$labels[$index]][$index] = $sample; } } // Reindex (i.e. to 0, 1, 2, ...) integer indices for backword compatibility foreach ($clusters as $index => $cluster) { $clusters[$index] = array_merge($cluster, []); } return $clusters; } }