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Diffstat (limited to 'admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php')
| -rw-r--r-- | admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php | 432 |
1 files changed, 432 insertions, 0 deletions
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php new file mode 100644 index 0000000..dd2c094 --- /dev/null +++ b/admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php @@ -0,0 +1,432 @@ +<?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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