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										 |  |  | <?php | 
					
						
							|  |  |  | /** | 
					
						
							|  |  |  |  * PHPExcel | 
					
						
							|  |  |  |  * | 
					
						
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										 |  |  |  * Copyright (c) 2006 - 2013 PHPExcel | 
					
						
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										 |  |  |  * | 
					
						
							|  |  |  |  * 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 | 
					
						
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										 |  |  |  * @package    PHPExcel_Shared_Trend | 
					
						
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										 |  |  |  * @copyright  Copyright (c) 2006 - 2013 PHPExcel (http://www.codeplex.com/PHPExcel) | 
					
						
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										 |  |  |  * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL | 
					
						
							|  |  |  |  * @version    ##VERSION##, ##DATE##
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							|  |  |  |  */ | 
					
						
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							|  |  |  | require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php'); | 
					
						
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							|  |  |  | /** | 
					
						
							|  |  |  |  * PHPExcel_Logarithmic_Best_Fit | 
					
						
							|  |  |  |  * | 
					
						
							|  |  |  |  * @category   PHPExcel | 
					
						
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											2012-03-19 00:25:29 +00:00
										 |  |  |  * @package    PHPExcel_Shared_Trend | 
					
						
							| 
									
										
										
										
											2013-05-14 11:20:28 +00:00
										 |  |  |  * @copyright  Copyright (c) 2006 - 2013 PHPExcel (http://www.codeplex.com/PHPExcel) | 
					
						
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										 |  |  |  */ | 
					
						
							|  |  |  | class PHPExcel_Logarithmic_Best_Fit extends PHPExcel_Best_Fit | 
					
						
							|  |  |  | { | 
					
						
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										 |  |  | 	/** | 
					
						
							|  |  |  | 	 * Algorithm type to use for best-fit | 
					
						
							|  |  |  | 	 * (Name of this trend class) | 
					
						
							|  |  |  | 	 * | 
					
						
							|  |  |  | 	 * @var	string | 
					
						
							|  |  |  | 	 **/ | 
					
						
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										 |  |  | 	protected $_bestFitType		= 'logarithmic'; | 
					
						
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										 |  |  | 	/** | 
					
						
							|  |  |  | 	 * Return the Y-Value for a specified value of X | 
					
						
							|  |  |  | 	 * | 
					
						
							|  |  |  | 	 * @param	 float		$xValue			X-Value | 
					
						
							|  |  |  | 	 * @return	 float						Y-Value | 
					
						
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										 |  |  | 	 **/ | 
					
						
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										 |  |  | 	public function getValueOfYForX($xValue) { | 
					
						
							|  |  |  | 		return $this->getIntersect() + $this->getSlope() * log($xValue - $this->_Xoffset); | 
					
						
							|  |  |  | 	}	//	function getValueOfYForX()
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										 |  |  | 	/** | 
					
						
							|  |  |  | 	 * Return the X-Value for a specified value of Y | 
					
						
							|  |  |  | 	 * | 
					
						
							|  |  |  | 	 * @param	 float		$yValue			Y-Value | 
					
						
							|  |  |  | 	 * @return	 float						X-Value | 
					
						
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										 |  |  | 	 **/ | 
					
						
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										 |  |  | 	public function getValueOfXForY($yValue) { | 
					
						
							|  |  |  | 		return exp(($yValue - $this->getIntersect()) / $this->getSlope()); | 
					
						
							|  |  |  | 	}	//	function getValueOfXForY()
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										 |  |  | 	/** | 
					
						
							|  |  |  | 	 * Return the Equation of the best-fit line | 
					
						
							|  |  |  | 	 * | 
					
						
							|  |  |  | 	 * @param	 int		$dp		Number of places of decimal precision to display | 
					
						
							|  |  |  | 	 * @return	 string | 
					
						
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										 |  |  | 	 **/ | 
					
						
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										 |  |  | 	public function getEquation($dp=0) { | 
					
						
							|  |  |  | 		$slope = $this->getSlope($dp); | 
					
						
							|  |  |  | 		$intersect = $this->getIntersect($dp); | 
					
						
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							|  |  |  | 		return 'Y = '.$intersect.' + '.$slope.' * log(X)'; | 
					
						
							|  |  |  | 	}	//	function getEquation()
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										 |  |  | 	/** | 
					
						
							|  |  |  | 	 * 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 | 
					
						
							|  |  |  | 	 */ | 
					
						
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										 |  |  | 	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); | 
					
						
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							|  |  |  | 		$this->_leastSquareFit($yValues, $xValues, $const); | 
					
						
							|  |  |  | 	}	//	function _logarithmic_regression()
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										 |  |  | 	/** | 
					
						
							|  |  |  | 	 * 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 | 
					
						
							|  |  |  | 	 */ | 
					
						
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										 |  |  | 	function __construct($yValues, $xValues=array(), $const=True) { | 
					
						
							|  |  |  | 		if (parent::__construct($yValues, $xValues) !== False) { | 
					
						
							|  |  |  | 			$this->_logarithmic_regression($yValues, $xValues, $const); | 
					
						
							|  |  |  | 		} | 
					
						
							|  |  |  | 	}	//	function __construct()
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							|  |  |  | }	//	class logarithmicBestFit
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