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<?php
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/**
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* PHPExcel
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*
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* Copyright (c) 2006 - 2013 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 - 2013 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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require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
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/**
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* PHPExcel_Logarithmic_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 - 2013 PHPExcel (http://www.codeplex.com/PHPExcel)
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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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* 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() + $this->getSlope() * log($xValue - $this->_Xoffset);
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} // function getValueOfYForX()
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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 exp(($yValue - $this->getIntersect()) / $this->getSlope());
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} // function getValueOfXForY()
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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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return 'Y = '.$intersect.' + '.$slope.' * log(X)';
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} // function getEquation()
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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 $const
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*/
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private function _logarithmic_regression($yValues, $xValues, $const) {
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foreach($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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$this->_leastSquareFit($yValues, $xValues, $const);
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} // function _logarithmic_regression()
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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->_logarithmic_regression($yValues, $xValues, $const);
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}
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} // function __construct()
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} // class logarithmicBestFit
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