# tablepress/3.4/libraries/vendor/PhpSpreadsheet/Shared/Trend/PolynomialBestFit.php

TablePress – Tables in WordPress made easy, version 3.4. 212 lines.

- Page: https://pluginprobe.com/plugins/tablepress/3.4/code/libraries/vendor/PhpSpreadsheet/Shared/Trend/PolynomialBestFit.php
- Raw: https://pluginprobe.com/plugins/tablepress/3.4/raw/libraries/vendor/PhpSpreadsheet/Shared/Trend/PolynomialBestFit.php
- Modified: 2026-09-30T03:50:46+00:00

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```php
<?php

namespace TablePress\PhpOffice\PhpSpreadsheet\Shared\Trend;

use TablePress\Matrix\Matrix;
use TablePress\PhpOffice\PhpSpreadsheet\Exception as SpreadsheetException;

// Phpstan and Scrutinizer seem to have legitimate complaints.
// $this->slope is specified where an array is expected in several places.
// But it seems that it should always be float.
// This code is probably not exercised at all in unit tests.
// Private bool property $implemented is set to indicate
//     whether this implementation is correct.
class PolynomialBestFit extends BestFit
{
	/**
	 * Algorithm type to use for best-fit
	 * (Name of this Trend class).
	 */
	protected string $bestFitType = 'polynomial';

	/**
	 * Polynomial order.
	 */
	protected int $order = 0;

	private bool $implemented = false;

	/**
	 * Return the order of this polynomial.
	 */
	public function getOrder(): int
	{
		return $this->order;
	}

	/**
	 * Return the Y-Value for a specified value of X.
	 *
	 * @param float $xValue X-Value
	 *
	 * @return float Y-Value
	 */
	public function getValueOfYForX(float $xValue): float
	{
		$retVal = $this->getIntersect();
		$slope = $this->getSlope();
		foreach ($slope as $key => $value) { //* @phpstan-ignore foreach.nonIterable (this whole class is a mess)
			/** @var float $value */
			if ($value != 0.0) {
				/** @var int $key */
				$retVal += $value * $xValue ** ($key + 1);
			}
		}

		return $retVal;
	}

	/**
	 * Return the X-Value for a specified value of Y.
	 *
	 * @param float $yValue Y-Value
	 *
	 * @return float X-Value
	 */
	public function getValueOfXForY(float $yValue): float
	{
		return ($yValue - $this->getIntersect()) / $this->getSlope();
	}

	/**
	 * Return the Equation of the best-fit line.
	 *
	 * @param int $dp Number of places of decimal precision to display
	 */
	public function getEquation(int $dp = 0): string
	{
		$slope = $this->getSlope($dp);
		$intersect = $this->getIntersect($dp);

		$equation = 'Y = ' . $intersect;
		// Phpstan and Scrutinizer are both correct - getSlope returns float, not array.
		foreach ($slope as $key => $value) { //* @phpstan-ignore foreach.nonIterable (this whole class is a mess)
			/** @var float|int $value */
			if ($value != 0.0) {
				$equation .= ' + ' . $value . ' * X';
				/** @var int $key */
				if ($key > 0) {
					$equation .= '^' . ($key + 1);
				}
			}
		}

		return $equation;
	}

	/**
	 * Return the Slope of the line.
	 *
	 * @param int $dp Number of places of decimal precision to display
	 */
	public function getSlope(int $dp = 0): float
	{
		if ($dp != 0) {
			$coefficients = [];
			foreach ($this->slope as $coefficient) { //* @phpstan-ignore foreach.nonIterable (this whole class is a mess)
				/** @var float|int $coefficient */
				$coefficients[] = round($coefficient, $dp);
			}

			return $coefficients; //* @phpstan-ignore return.type (this whole class is a mess)
		}

		return $this->slope;
	}

	/** @return array<float|int> */
	public function getCoefficients(int $dp = 0): array
	{
		return array_merge([$this->getIntersect($dp)], $this->getSlope($dp)); //* @phpstan-ignore return.type (this whole class is a mess), argument.type (ditto)
	}

	/**
	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values.
	 *
	 * @param int $order Order of Polynomial for this regression
	 * @param float[] $yValues The set of Y-values for this regression
	 * @param float[] $xValues The set of X-values for this regression
	 */
	private function polynomialRegression(int $order, array $yValues, array $xValues): void
	{
		// calculate sums
		$x_sum = array_sum($xValues);
		$y_sum = array_sum($yValues);
		$xx_sum = $xy_sum = $yy_sum = 0;
		for ($i = 0; $i < $this->valueCount; ++$i) {
			$xy_sum += $xValues[$i] * $yValues[$i];
			$xx_sum += $xValues[$i] * $xValues[$i];
			$yy_sum += $yValues[$i] * $yValues[$i];
		}
		/*
		 *    This routine uses logic from the PHP port of polyfit version 0.1
		 *    written by Michael Bommarito and Paul Meagher
		 *
		 *    The function fits a polynomial function of order $order through
		 *    a series of x-y data points using least squares.
		 *
		 */
		$A = [];
		$B = [];
		for ($i = 0; $i < $this->valueCount; ++$i) {
			for ($j = 0; $j <= $order; ++$j) {
				$A[$i][$j] = $xValues[$i] ** $j;
			}
		}
		for ($i = 0; $i < $this->valueCount; ++$i) {
			$B[$i] = [$yValues[$i]];
		}
		$matrixA = new Matrix($A);
		$matrixB = new Matrix($B);
		$C = $matrixA->solve($matrixB);

		$coefficients = [];
		for ($i = 0; $i < $C->rows; ++$i) {
			$r = $C->getValue($i + 1, 1); // row and column are origin-1
			if (!is_numeric($r) || abs($r + 0) <= 10 ** (-9)) {
				$r = 0;
			} else {
				$r += 0;
			}
			$coefficients[] = $r;
		}

		$this->intersect = (float) array_shift($coefficients);
		$this->slope = $coefficients; //* @phpstan-ignore assign.propertyType (this whole class is a mess)

		$this->calculateGoodnessOfFit($x_sum, $y_sum, $xx_sum, $yy_sum, $xy_sum, 0, 0, 0);
		foreach ($this->xValues as $xKey => $xValue) {
			$this->yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
		}
	}

	/**
	 * Define the regression and calculate the goodness of fit for a set of X and Y data values.
	 *
	 * @param int $order Order of Polynomial for this regression
	 * @param float[] $yValues The set of Y-values for this regression
	 * @param float[] $xValues The set of X-values for this regression
	 */
	public function __construct(int $order, array $yValues, array $xValues = [])
	{
		if (!$this->implemented) {
			throw new SpreadsheetException('Polynomial Best Fit not yet implemented');
		}

		parent::__construct($yValues, $xValues);

		if (!$this->error) {
			if ($order < $this->valueCount) {
				$this->bestFitType .= '_' . $order;
				$this->order = $order;
				$this->polynomialRegression($order, $yValues, $xValues);
				if (($this->getGoodnessOfFit() < 0.0) || ($this->getGoodnessOfFit() > 1.0)) {
					$this->error = true;
				}
			} else {
				$this->error = true;
			}
		}
	}
}

```