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							- <?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_Power_Best_Fit
 
-  *
 
-  * @category   PHPExcel
 
-  * @package    PHPExcel_Shared_Trend
 
-  * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
 
-  */
 
- class PHPExcel_Power_Best_Fit extends PHPExcel_Best_Fit
 
- {
 
- 	/**
 
- 	 * 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 $this->getIntersect() * pow(($xValue - $this->_Xoffset),$this->getSlope());
 
- 	}	//	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 pow((($yValue + $this->_Yoffset) / $this->getIntersect()),(1 / $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 = '.$intersect.' * X^'.$slope;
 
- 	}	//	function getEquation()
 
- 	/**
 
- 	 * Return the Value of X where it intersects Y = 0
 
- 	 *
 
- 	 * @param	 int		$dp		Number of places of decimal precision to display
 
- 	 * @return	 string
 
- 	 **/
 
- 	public function getIntersect($dp=0) {
 
- 		if ($dp != 0) {
 
- 			return round(exp($this->_intersect),$dp);
 
- 		}
 
- 		return exp($this->_intersect);
 
- 	}	//	function getIntersect()
 
- 	/**
 
- 	 * 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 _power_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);
 
- 		foreach($yValues as &$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 _power_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) {
 
- 			$this->_power_regression($yValues, $xValues, $const);
 
- 		}
 
- 	}	//	function __construct()
 
- }	//	class powerBestFit
 
 
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