/home/kueuepay/www/vendor/phpoffice/phpspreadsheet/src/PhpSpreadsheet/Shared/Trend/PowerBestFit.php
<?php

namespace PhpOffice\PhpSpreadsheet\Shared\Trend;

class PowerBestFit extends BestFit
{
    /**
     * Algorithm type to use for best-fit
     * (Name of this Trend class).
     *
     * @var string
     */
    protected $bestFitType = 'power';

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

    /**
     * Return the X-Value for a specified value of Y.
     *
     * @param float $yValue Y-Value
     *
     * @return float X-Value
     */
    public function getValueOfXForY($yValue)
    {
        return (($yValue + $this->yOffset) / $this->getIntersect()) ** (1 / $this->getSlope());
    }

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

        return 'Y = ' . $intersect . ' * X^' . $slope;
    }

    /**
     * Return the Value of X where it intersects Y = 0.
     *
     * @param int $dp Number of places of decimal precision to display
     *
     * @return float
     */
    public function getIntersect($dp = 0)
    {
        if ($dp != 0) {
            return round(exp($this->intersect), $dp);
        }

        return exp($this->intersect);
    }

    /**
     * Execute the regression and calculate the goodness of fit for a set of X and Y data values.
     *
     * @param float[] $yValues The set of Y-values for this regression
     * @param float[] $xValues The set of X-values for this regression
     */
    private function powerRegression(array $yValues, array $xValues, bool $const): void
    {
        $adjustedYValues = array_map(
            function ($value) {
                return ($value < 0.0) ? 0 - log(abs($value)) : log($value);
            },
            $yValues
        );
        $adjustedXValues = array_map(
            function ($value) {
                return ($value < 0.0) ? 0 - log(abs($value)) : log($value);
            },
            $xValues
        );

        $this->leastSquareFit($adjustedYValues, $adjustedXValues, $const);
    }

    /**
     * Define the regression and calculate the goodness of fit for a set of X and Y data values.
     *
     * @param float[] $yValues The set of Y-values for this regression
     * @param float[] $xValues The set of X-values for this regression
     * @param bool $const
     */
    public function __construct($yValues, $xValues = [], $const = true)
    {
        parent::__construct($yValues, $xValues);

        if (!$this->error) {
            $this->powerRegression($yValues, $xValues, (bool) $const);
        }
    }
}
Best Practice

Best Practices

To ensure a smooth integration process and optimal performance, follow these best practices:

  1. Use secure HTTPS connections for all API requests.
  2. Implement robust error handling to handle potential issues gracefully.
  3. Regularly update your integration to stay current with any API changes or enhancements.