111 lines
		
	
	
		
			3.6 KiB
		
	
	
	
		
			PHP
		
	
	
	
	
	
			
		
		
	
	
			111 lines
		
	
	
		
			3.6 KiB
		
	
	
	
		
			PHP
		
	
	
	
	
	
| <?php
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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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|  * PHPExcel_Logarithmic_Best_Fit
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|  *
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|  * Copyright (c) 2006 - 2015 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 - 2015 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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| class PHPExcel_Logarithmic_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        = 'logarithmic';
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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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|     {
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|         return $this->getIntersect() + $this->getSlope() * log($xValue - $this->xOffset);
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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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|     {
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|         return exp(($yValue - $this->getIntersect()) / $this->getSlope());
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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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|     {
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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.' * log(X)';
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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    $const
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|      */
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|     private function logarithmicRegression($yValues, $xValues, $const)
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|     {
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|         foreach ($xValues as &$value) {
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|             if ($value < 0.0) {
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|                 $value = 0 - log(abs($value));
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|             } elseif ($value > 0.0) {
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|                 $value = log($value);
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|             }
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|         }
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|         unset($value);
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| 
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|         $this->leastSquareFit($yValues, $xValues, $const);
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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        $const
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|      */
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|     public function __construct($yValues, $xValues = array(), $const = true)
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|     {
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|         if (parent::__construct($yValues, $xValues) !== false) {
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|             $this->logarithmicRegression($yValues, $xValues, $const);
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|         }
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|     }
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| }
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