Proyectos de Subversion Moodle

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