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| -rw-r--r-- | admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php | 432 |
1 files changed, 0 insertions, 432 deletions
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php deleted file mode 100644 index dd2c094..0000000 --- a/admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php +++ /dev/null @@ -1,432 +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
- */
-
-
-/**
- * PHPExcel_Best_Fit
- *
- * @category PHPExcel
- * @package PHPExcel_Shared_Trend
- * @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
- */
-class PHPExcel_Best_Fit
-{
- /**
- * Indicator flag for a calculation error
- *
- * @var boolean
- **/
- protected $_error = False;
-
- /**
- * Algorithm type to use for best-fit
- *
- * @var string
- **/
- protected $_bestFitType = 'undetermined';
-
- /**
- * Number of entries in the sets of x- and y-value arrays
- *
- * @var int
- **/
- protected $_valueCount = 0;
-
- /**
- * X-value dataseries of values
- *
- * @var float[]
- **/
- protected $_xValues = array();
-
- /**
- * Y-value dataseries of values
- *
- * @var float[]
- **/
- protected $_yValues = array();
-
- /**
- * Flag indicating whether values should be adjusted to Y=0
- *
- * @var boolean
- **/
- protected $_adjustToZero = False;
-
- /**
- * Y-value series of best-fit values
- *
- * @var float[]
- **/
- protected $_yBestFitValues = array();
-
- protected $_goodnessOfFit = 1;
-
- protected $_stdevOfResiduals = 0;
-
- protected $_covariance = 0;
-
- protected $_correlation = 0;
-
- protected $_SSRegression = 0;
-
- protected $_SSResiduals = 0;
-
- protected $_DFResiduals = 0;
-
- protected $_F = 0;
-
- protected $_slope = 0;
-
- protected $_slopeSE = 0;
-
- protected $_intersect = 0;
-
- protected $_intersectSE = 0;
-
- protected $_Xoffset = 0;
-
- protected $_Yoffset = 0;
-
-
- public function getError() {
- return $this->_error;
- } // function getBestFitType()
-
-
- public function getBestFitType() {
- return $this->_bestFitType;
- } // function getBestFitType()
-
-
- /**
- * Return the Y-Value for a specified value of X
- *
- * @param float $xValue X-Value
- * @return float Y-Value
- */
- public function getValueOfYForX($xValue) {
- return False;
- } // 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 False;
- } // function getValueOfXForY()
-
-
- /**
- * Return the original set of X-Values
- *
- * @return float[] X-Values
- */
- public function getXValues() {
- return $this->_xValues;
- } // 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) {
- return False;
- } // function getEquation()
-
-
- /**
- * Return the Slope of the line
- *
- * @param int $dp Number of places of decimal precision to display
- * @return string
- */
- public function getSlope($dp=0) {
- if ($dp != 0) {
- return round($this->_slope,$dp);
- }
- return $this->_slope;
- } // function getSlope()
-
-
- /**
- * Return the standard error of the Slope
- *
- * @param int $dp Number of places of decimal precision to display
- * @return string
- */
- public function getSlopeSE($dp=0) {
- if ($dp != 0) {
- return round($this->_slopeSE,$dp);
- }
- return $this->_slopeSE;
- } // function getSlopeSE()
-
-
- /**
- * Return the Value of X where it intersects Y = 0
- *
- * @param int $dp Number of places of decimal precision to display
- * @return string
- */
- public function getIntersect($dp=0) {
- if ($dp != 0) {
- return round($this->_intersect,$dp);
- }
- return $this->_intersect;
- } // function getIntersect()
-
-
- /**
- * Return the standard error of the Intersect
- *
- * @param int $dp Number of places of decimal precision to display
- * @return string
- */
- public function getIntersectSE($dp=0) {
- if ($dp != 0) {
- return round($this->_intersectSE,$dp);
- }
- return $this->_intersectSE;
- } // function getIntersectSE()
-
-
- /**
- * Return the goodness of fit for this regression
- *
- * @param int $dp Number of places of decimal precision to return
- * @return float
- */
- public function getGoodnessOfFit($dp=0) {
- if ($dp != 0) {
- return round($this->_goodnessOfFit,$dp);
- }
- return $this->_goodnessOfFit;
- } // function getGoodnessOfFit()
-
-
- public function getGoodnessOfFitPercent($dp=0) {
- if ($dp != 0) {
- return round($this->_goodnessOfFit * 100,$dp);
- }
- return $this->_goodnessOfFit * 100;
- } // function getGoodnessOfFitPercent()
-
-
- /**
- * Return the standard deviation of the residuals for this regression
- *
- * @param int $dp Number of places of decimal precision to return
- * @return float
- */
- public function getStdevOfResiduals($dp=0) {
- if ($dp != 0) {
- return round($this->_stdevOfResiduals,$dp);
- }
- return $this->_stdevOfResiduals;
- } // function getStdevOfResiduals()
-
-
- public function getSSRegression($dp=0) {
- if ($dp != 0) {
- return round($this->_SSRegression,$dp);
- }
- return $this->_SSRegression;
- } // function getSSRegression()
-
-
- public function getSSResiduals($dp=0) {
- if ($dp != 0) {
- return round($this->_SSResiduals,$dp);
- }
- return $this->_SSResiduals;
- } // function getSSResiduals()
-
-
- public function getDFResiduals($dp=0) {
- if ($dp != 0) {
- return round($this->_DFResiduals,$dp);
- }
- return $this->_DFResiduals;
- } // function getDFResiduals()
-
-
- public function getF($dp=0) {
- if ($dp != 0) {
- return round($this->_F,$dp);
- }
- return $this->_F;
- } // function getF()
-
-
- public function getCovariance($dp=0) {
- if ($dp != 0) {
- return round($this->_covariance,$dp);
- }
- return $this->_covariance;
- } // function getCovariance()
-
-
- public function getCorrelation($dp=0) {
- if ($dp != 0) {
- return round($this->_correlation,$dp);
- }
- return $this->_correlation;
- } // function getCorrelation()
-
-
- public function getYBestFitValues() {
- return $this->_yBestFitValues;
- } // function getYBestFitValues()
-
-
- protected function _calculateGoodnessOfFit($sumX,$sumY,$sumX2,$sumY2,$sumXY,$meanX,$meanY, $const) {
- $SSres = $SScov = $SScor = $SStot = $SSsex = 0.0;
- foreach($this->_xValues as $xKey => $xValue) {
- $bestFitY = $this->_yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
-
- $SSres += ($this->_yValues[$xKey] - $bestFitY) * ($this->_yValues[$xKey] - $bestFitY);
- if ($const) {
- $SStot += ($this->_yValues[$xKey] - $meanY) * ($this->_yValues[$xKey] - $meanY);
- } else {
- $SStot += $this->_yValues[$xKey] * $this->_yValues[$xKey];
- }
- $SScov += ($this->_xValues[$xKey] - $meanX) * ($this->_yValues[$xKey] - $meanY);
- if ($const) {
- $SSsex += ($this->_xValues[$xKey] - $meanX) * ($this->_xValues[$xKey] - $meanX);
- } else {
- $SSsex += $this->_xValues[$xKey] * $this->_xValues[$xKey];
- }
- }
-
- $this->_SSResiduals = $SSres;
- $this->_DFResiduals = $this->_valueCount - 1 - $const;
-
- if ($this->_DFResiduals == 0.0) {
- $this->_stdevOfResiduals = 0.0;
- } else {
- $this->_stdevOfResiduals = sqrt($SSres / $this->_DFResiduals);
- }
- if (($SStot == 0.0) || ($SSres == $SStot)) {
- $this->_goodnessOfFit = 1;
- } else {
- $this->_goodnessOfFit = 1 - ($SSres / $SStot);
- }
-
- $this->_SSRegression = $this->_goodnessOfFit * $SStot;
- $this->_covariance = $SScov / $this->_valueCount;
- $this->_correlation = ($this->_valueCount * $sumXY - $sumX * $sumY) / sqrt(($this->_valueCount * $sumX2 - pow($sumX,2)) * ($this->_valueCount * $sumY2 - pow($sumY,2)));
- $this->_slopeSE = $this->_stdevOfResiduals / sqrt($SSsex);
- $this->_intersectSE = $this->_stdevOfResiduals * sqrt(1 / ($this->_valueCount - ($sumX * $sumX) / $sumX2));
- if ($this->_SSResiduals != 0.0) {
- if ($this->_DFResiduals == 0.0) {
- $this->_F = 0.0;
- } else {
- $this->_F = $this->_SSRegression / ($this->_SSResiduals / $this->_DFResiduals);
- }
- } else {
- if ($this->_DFResiduals == 0.0) {
- $this->_F = 0.0;
- } else {
- $this->_F = $this->_SSRegression / $this->_DFResiduals;
- }
- }
- } // function _calculateGoodnessOfFit()
-
-
- protected function _leastSquareFit($yValues, $xValues, $const) {
- // calculate sums
- $x_sum = array_sum($xValues);
- $y_sum = array_sum($yValues);
- $meanX = $x_sum / $this->_valueCount;
- $meanY = $y_sum / $this->_valueCount;
- $mBase = $mDivisor = $xx_sum = $xy_sum = $yy_sum = 0.0;
- for($i = 0; $i < $this->_valueCount; ++$i) {
- $xy_sum += $xValues[$i] * $yValues[$i];
- $xx_sum += $xValues[$i] * $xValues[$i];
- $yy_sum += $yValues[$i] * $yValues[$i];
-
- if ($const) {
- $mBase += ($xValues[$i] - $meanX) * ($yValues[$i] - $meanY);
- $mDivisor += ($xValues[$i] - $meanX) * ($xValues[$i] - $meanX);
- } else {
- $mBase += $xValues[$i] * $yValues[$i];
- $mDivisor += $xValues[$i] * $xValues[$i];
- }
- }
-
- // calculate slope
-// $this->_slope = (($this->_valueCount * $xy_sum) - ($x_sum * $y_sum)) / (($this->_valueCount * $xx_sum) - ($x_sum * $x_sum));
- $this->_slope = $mBase / $mDivisor;
-
- // calculate intersect
-// $this->_intersect = ($y_sum - ($this->_slope * $x_sum)) / $this->_valueCount;
- if ($const) {
- $this->_intersect = $meanY - ($this->_slope * $meanX);
- } else {
- $this->_intersect = 0;
- }
-
- $this->_calculateGoodnessOfFit($x_sum,$y_sum,$xx_sum,$yy_sum,$xy_sum,$meanX,$meanY,$const);
- } // function _leastSquareFit()
-
-
- /**
- * Define the regression
- *
- * @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) {
- // Calculate number of points
- $nY = count($yValues);
- $nX = count($xValues);
-
- // Define X Values if necessary
- if ($nX == 0) {
- $xValues = range(1,$nY);
- $nX = $nY;
- } elseif ($nY != $nX) {
- // Ensure both arrays of points are the same size
- $this->_error = True;
- return False;
- }
-
- $this->_valueCount = $nY;
- $this->_xValues = $xValues;
- $this->_yValues = $yValues;
- } // function __construct()
-
-} // class bestFit
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