120 lines
3.5 KiB
PHP
120 lines
3.5 KiB
PHP
<?php
|
|
/**
|
|
* PHPExcel
|
|
*
|
|
* Copyright (c) 2006 - 2012 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 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
|
|
* @license http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt LGPL
|
|
* @version 1.7.8, 2012-10-12
|
|
*/
|
|
|
|
|
|
require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
|
|
|
|
|
|
/**
|
|
* PHPExcel_Logarithmic_Best_Fit
|
|
*
|
|
* @category PHPExcel
|
|
* @package PHPExcel_Shared_Trend
|
|
* @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
|
|
*/
|
|
class PHPExcel_Logarithmic_Best_Fit extends PHPExcel_Best_Fit
|
|
{
|
|
/**
|
|
* Algorithm type to use for best-fit
|
|
* (Name of this trend class)
|
|
*
|
|
* @var string
|
|
**/
|
|
protected $_bestFitType = 'logarithmic';
|
|
|
|
|
|
/**
|
|
* 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() + $this->getSlope() * log($xValue - $this->_Xoffset);
|
|
} // 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 exp(($yValue - $this->getIntersect()) / $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 = '.$intersect.' + '.$slope.' * log(X)';
|
|
} // function getEquation()
|
|
|
|
|
|
/**
|
|
* 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 $const
|
|
*/
|
|
private function _logarithmic_regression($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);
|
|
|
|
$this->_leastSquareFit($yValues, $xValues, $const);
|
|
} // function _logarithmic_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) {
|
|
$this->_logarithmic_regression($yValues, $xValues, $const);
|
|
}
|
|
} // function __construct()
|
|
|
|
} // class logarithmicBestFit
|