111 lines
		
	
	
		
			3.3 KiB
		
	
	
	
		
			PHP
		
	
	
	
	
	
			
		
		
	
	
			111 lines
		
	
	
		
			3.3 KiB
		
	
	
	
		
			PHP
		
	
	
	
	
	
| <?php
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| /**
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|  * PHPExcel
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|  *
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|  * Copyright (c) 2006 - 2014 PHPExcel
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|  *
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|  * This library is free software; you can redistribute it and/or
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|  * modify it under the terms of the GNU Lesser General Public
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|  * License as published by the Free Software Foundation; either
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|  * version 2.1 of the License, or (at your option) any later version.
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|  *
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|  * This library is distributed in the hope that it will be useful,
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|  * but WITHOUT ANY WARRANTY; without even the implied warranty of
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|  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
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|  * Lesser General Public License for more details.
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|  *
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|  * You should have received a copy of the GNU Lesser General Public
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|  * License along with this library; if not, write to the Free Software
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|  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
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|  *
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|  * @category   PHPExcel
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|  * @package    PHPExcel_Shared_Trend
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|  * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
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|  * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
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|  * @version    ##VERSION##, ##DATE##
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|  */
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| 
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| 
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| require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
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| 
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| 
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| /**
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|  * PHPExcel_Linear_Best_Fit
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|  *
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|  * @category   PHPExcel
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|  * @package    PHPExcel_Shared_Trend
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|  * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
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|  */
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| class PHPExcel_Linear_Best_Fit extends PHPExcel_Best_Fit
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| {
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| 	/**
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| 	 * Algorithm type to use for best-fit
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| 	 * (Name of this trend class)
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| 	 *
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| 	 * @var	string
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| 	 **/
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| 	protected $_bestFitType		= 'linear';
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| 
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| 
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| 	/**
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| 	 * Return the Y-Value for a specified value of X
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| 	 *
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| 	 * @param	 float		$xValue			X-Value
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| 	 * @return	 float						Y-Value
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| 	 **/
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| 	public function getValueOfYForX($xValue) {
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| 		return $this->getIntersect() + $this->getSlope() * $xValue;
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| 	}	//	function getValueOfYForX()
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| 
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| 
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| 	/**
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| 	 * Return the X-Value for a specified value of Y
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| 	 *
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| 	 * @param	 float		$yValue			Y-Value
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| 	 * @return	 float						X-Value
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| 	 **/
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| 	public function getValueOfXForY($yValue) {
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| 		return ($yValue - $this->getIntersect()) / $this->getSlope();
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| 	}	//	function getValueOfXForY()
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| 
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| 
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| 	/**
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| 	 * Return the Equation of the best-fit line
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| 	 *
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| 	 * @param	 int		$dp		Number of places of decimal precision to display
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| 	 * @return	 string
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| 	 **/
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| 	public function getEquation($dp=0) {
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| 		$slope = $this->getSlope($dp);
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| 		$intersect = $this->getIntersect($dp);
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| 
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| 		return 'Y = '.$intersect.' + '.$slope.' * X';
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| 	}	//	function getEquation()
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| 
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| 
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| 	/**
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| 	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values
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| 	 *
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| 	 * @param	 float[]	$yValues	The set of Y-values for this regression
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| 	 * @param	 float[]	$xValues	The set of X-values for this regression
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| 	 * @param	 boolean	$const
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| 	 */
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| 	private function _linear_regression($yValues, $xValues, $const) {
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| 		$this->_leastSquareFit($yValues, $xValues,$const);
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| 	}	//	function _linear_regression()
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| 
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| 
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| 	/**
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| 	 * Define the regression and calculate the goodness of fit for a set of X and Y data values
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| 	 *
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| 	 * @param	float[]		$yValues	The set of Y-values for this regression
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| 	 * @param	float[]		$xValues	The set of X-values for this regression
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| 	 * @param	boolean		$const
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| 	 */
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| 	function __construct($yValues, $xValues=array(), $const=True) {
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| 		if (parent::__construct($yValues, $xValues) !== False) {
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| 			$this->_linear_regression($yValues, $xValues, $const);
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| 		}
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| 	}	//	function __construct()
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| 
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| }	//	class linearBestFit
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