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Diffstat (limited to 'admin/survey/excel/PHPExcel/Shared/trend/logarithmicBestFitClass.php')
| -rw-r--r-- | admin/survey/excel/PHPExcel/Shared/trend/logarithmicBestFitClass.php | 120 |
1 files changed, 0 insertions, 120 deletions
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/logarithmicBestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/logarithmicBestFitClass.php deleted file mode 100644 index acccc53..0000000 --- a/admin/survey/excel/PHPExcel/Shared/trend/logarithmicBestFitClass.php +++ /dev/null @@ -1,120 +0,0 @@ -<?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
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