| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120 | <?php/** * PHPExcel * * Copyright (c) 2006 - 2014 PHPExcel * * This library is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * This library is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this library; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA * * @category   PHPExcel * @package    PHPExcel_Shared_Trend * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel) * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL * @version    1.8.0, 2014-03-02 */require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');/** * PHPExcel_Logarithmic_Best_Fit * * @category   PHPExcel * @package    PHPExcel_Shared_Trend * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel) */class PHPExcel_Logarithmic_Best_Fit extends PHPExcel_Best_Fit{	/**	 * Algorithm type to use for best-fit	 * (Name of this trend class)	 *	 * @var	string	 **/	protected $_bestFitType		= 'logarithmic';	/**	 * 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() + $this->getSlope() * log($xValue - $this->_Xoffset);	}	//	function getValueOfYForX()	/**	 * 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());	}	//	function getValueOfXForY()	/**	 * 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)';	}	//	function getEquation()	/**	 * 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	$const	 */	private function _logarithmic_regression($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);	}	//	function _logarithmic_regression()	/**	 * 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		$const	 */	function __construct($yValues, $xValues=array(), $const=True) {		if (parent::__construct($yValues, $xValues) !== False) {			$this->_logarithmic_regression($yValues, $xValues, $const);		}	}	//	function __construct()}	//	class logarithmicBestFit
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