New file |
0,0 → 1,120 |
<?php |
/** |
* PHPExcel |
* |
* Copyright (c) 2006 - 2013 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 - 2013 PHPExcel (http://www.codeplex.com/PHPExcel) |
* @license http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt LGPL |
* @version ##VERSION##, ##DATE## |
*/ |
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require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php'); |
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/** |
* PHPExcel_Logarithmic_Best_Fit |
* |
* @category PHPExcel |
* @package PHPExcel_Shared_Trend |
* @copyright Copyright (c) 2006 - 2013 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'; |
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/** |
* 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() |
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/** |
* 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() |
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/** |
* Return the Equation of the best-fit line |
* |
* @param int $dp Number of places of decimal precision to display |
* @return string |
**/ |
public function getEquation($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 $const |
*/ |
private function _logarithmic_regression($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 $const |
*/ |
function __construct($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 |