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Editing: IntervalDiscretizer.php

<?php

namespace Rubix\ML\Transformers;

use Rubix\ML\DataType;
use Rubix\ML\Persistable;
use Rubix\ML\Helpers\Stats;
use Rubix\ML\Datasets\Dataset;
use Rubix\ML\Traits\AutotrackRevisions;
use Rubix\ML\Specifications\SamplesAreCompatibleWithTransformer;
use Rubix\ML\Exceptions\InvalidArgumentException;
use Rubix\ML\Exceptions\RuntimeException;

use function Rubix\ML\linspace;
use function array_slice;
use function min;
use function max;

/**
 * Interval Discretizer
 *
 * Assigns continuous features to ordered categories using variable width per-feature histograms with a fixed
 * user-specified number of bins.
 *
 * @category    Machine Learning
 * @package     Rubix/ML
 * @author      Andrew DalPino
 */
class IntervalDiscretizer implements Transformer, Stateful, Persistable
{
    use AutotrackRevisions;

/**
     * The number of bins per histogram.
     *
     * @var int
     */
    protected int $bins;

/**
     * Should the bins be equal width?
     *
     * @var bool
     */
    protected bool $equiWidth;

/**
     * The bin intervals of the fitted data.
     *
     * @var array<(int|float)[]>|null
     */
    protected ?array $intervals = null;

/**
     * @param int $bins
     * @param bool $equiWidth
     * @throws InvalidArgumentException
     */
    public function __construct(int $bins = 5, bool $equiWidth = false)
    {
        if ($bins < 3) {
            throw new InvalidArgumentException('Number of bins must be'
                . " greater than 3, $bins given.");
        }

$this->bins = $bins;
        $this->equiWidth = $equiWidth;
    }

/**
     * Return the data types that this transformer is compatible with.
     *
     * @internal
     *
     * @return list<DataType>
     */
    public function compatibility() : array
    {
        return DataType::all();
    }

/**
     * Is the transformer fitted?
     *
     * @return bool
     */
    public function fitted() : bool
    {
        return isset($this->intervals);
    }

/**
     * Return the bin intervals of the fitted data.
     *
     * @return array<(int|float)[]>|null
     */
    public function intervals() : ?array
    {
        return $this->intervals;
    }

/**
     * Fit the transformer to a dataset.
     *
     * @param Dataset $dataset
     * @throws InvalidArgumentException
     */
    public function fit(Dataset $dataset) : void
    {
        SamplesAreCompatibleWithTransformer::with($dataset, $this)->check();

if (!$this->equiWidth) {
            $q = linspace(0.0, 1.0, $this->bins + 1);

$q = array_slice($q, 1, -1);
        }

$this->intervals = [];

foreach ($dataset->featureTypes() as $column => $type) {
            if ($type->isContinuous()) {
                $values = $dataset->feature($column);

if (isset($q)) {
                    $edges = Stats::quantiles($values, $q);
                } else {
                    $min = min($values);
                    $max = max($values);

$edges = linspace($min, $max, $this->bins + 1);

$edges = array_slice($edges, 1, -1);
                }

$edges[] = INF;

$this->intervals[$column] = $edges;
            }
        }
    }

/**
     * Transform the dataset in place.
     *
     * @param list<list<mixed>> $samples
     * @throws RuntimeException
     */
    public function transform(array &$samples) : void
    {
        if ($this->intervals === null) {
            throw new RuntimeException('Transformer has not been fitted.');
        }

foreach ($samples as &$sample) {
            foreach ($this->intervals as $column => $interval) {
                $value = &$sample[$column];

foreach ($interval as $ordinal => $edge) {
                    if ($value <= $edge) {
                        $value = "$ordinal";

break;
                    }
                }
            }
        }
    }

/**
     * Return the string representation of the object.
     *
     * @internal
     *
     * @return string
     */
    public function __toString() : string
    {
        return "Interval Discretizer (bins: {$this->bins})";
    }
}

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