diff --git a/src/PhpSpreadsheet/Shared/trend/logarithmicBestFit.php b/src/PhpSpreadsheet/Shared/trend/logarithmicBestFit.php deleted file mode 100644 index a0bfc59f..00000000 --- a/src/PhpSpreadsheet/Shared/trend/logarithmicBestFit.php +++ /dev/null @@ -1,110 +0,0 @@ -getIntersect() + $this->getSlope() * log($xValue - $this->xOffset); - } - - /** - * Return the X-Value for a specified value of Y - * - * @param float $yValue Y-Value - * @return float X-Value - **/ - public function getValueOfXForY($yValue) - { - return exp(($yValue - $this->getIntersect()) / $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 = '.$intersect.' + '.$slope.' * log(X)'; - } - - /** - * 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 - * @param boolean $const - */ - private function logarithmicRegression($yValues, $xValues, $const) - { - foreach ($xValues as &$value) { - if ($value < 0.0) { - $value = 0 - log(abs($value)); - } elseif ($value > 0.0) { - $value = log($value); - } - } - unset($value); - - $this->leastSquareFit($yValues, $xValues, $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 boolean $const - */ - public function __construct($yValues, $xValues = array(), $const = true) - { - if (parent::__construct($yValues, $xValues) !== false) { - $this->logarithmicRegression($yValues, $xValues, $const); - } - } -}