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authorAnton Luka Šijanec <anton@sijanec.eu>2024-05-27 13:12:17 +0200
committerAnton Luka Šijanec <anton@sijanec.eu>2024-05-27 13:12:17 +0200
commitf1ab2f022fdc780aca0944d90e9a0e844a0820d7 (patch)
tree79942a40514f5ab40c5901349c9fcd30c6c8dc0e /admin/survey/excel/PHPExcel/Shared/trend
parent2024-02-19 upstream (diff)
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Diffstat (limited to 'admin/survey/excel/PHPExcel/Shared/trend')
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/bestFitClass.php432
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/exponentialBestFitClass.php148
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/linearBestFitClass.php111
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/logarithmicBestFitClass.php120
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/polynomialBestFitClass.php224
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/powerBestFitClass.php142
-rw-r--r--admin/survey/excel/PHPExcel/Shared/trend/trendClass.php156
7 files changed, 0 insertions, 1333 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
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/exponentialBestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/exponentialBestFitClass.php
deleted file mode 100644
index 6cc8201..0000000
--- a/admin/survey/excel/PHPExcel/Shared/trend/exponentialBestFitClass.php
+++ /dev/null
@@ -1,148 +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_Exponential_Best_Fit
- *
- * @category PHPExcel
- * @package PHPExcel_Shared_Trend
- * @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
- */
-class PHPExcel_Exponential_Best_Fit extends PHPExcel_Best_Fit
-{
- /**
- * Algorithm type to use for best-fit
- * (Name of this trend class)
- *
- * @var string
- **/
- protected $_bestFitType = 'exponential';
-
-
- /**
- * Return the Y-Value for a specified value of X
- *
- * @param float $xValue X-Value
- * @return float Y-Value
- **/
- public function getValueOfYForX($xValue) {
- return $this->getIntersect() * pow($this->getSlope(),($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 log(($yValue + $this->_Yoffset) / $this->getIntersect()) / log($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.'^X';
- } // 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 ($dp != 0) {
- return round(exp($this->_slope),$dp);
- }
- return exp($this->_slope);
- } // function getSlope()
-
-
- /**
- * 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 ($dp != 0) {
- return round(exp($this->_intersect),$dp);
- }
- return exp($this->_intersect);
- } // function getIntersect()
-
-
- /**
- * 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 $const
- */
- private function _exponential_regression($yValues, $xValues, $const) {
- foreach($yValues 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 _exponential_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) {
- $this->_exponential_regression($yValues, $xValues, $const);
- }
- } // function __construct()
-
-} // class exponentialBestFit \ No newline at end of file
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/linearBestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/linearBestFitClass.php
deleted file mode 100644
index 0fe62b1..0000000
--- a/admin/survey/excel/PHPExcel/Shared/trend/linearBestFitClass.php
+++ /dev/null
@@ -1,111 +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_Linear_Best_Fit
- *
- * @category PHPExcel
- * @package PHPExcel_Shared_Trend
- * @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
- */
-class PHPExcel_Linear_Best_Fit extends PHPExcel_Best_Fit
-{
- /**
- * Algorithm type to use for best-fit
- * (Name of this trend class)
- *
- * @var string
- **/
- protected $_bestFitType = 'linear';
-
-
- /**
- * 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() * $xValue;
- } // 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 ($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.' * 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 $const
- */
- private function _linear_regression($yValues, $xValues, $const) {
- $this->_leastSquareFit($yValues, $xValues,$const);
- } // function _linear_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) {
- $this->_linear_regression($yValues, $xValues, $const);
- }
- } // function __construct()
-
-} // class linearBestFit \ No newline at end of file
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 \ No newline at end of file
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/polynomialBestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/polynomialBestFitClass.php
deleted file mode 100644
index eef0060..0000000
--- a/admin/survey/excel/PHPExcel/Shared/trend/polynomialBestFitClass.php
+++ /dev/null
@@ -1,224 +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';
-require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/JAMA/Matrix.php';
-
-
-/**
- * PHPExcel_Polynomial_Best_Fit
- *
- * @category PHPExcel
- * @package PHPExcel_Shared_Trend
- * @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
- */
-class PHPExcel_Polynomial_Best_Fit extends PHPExcel_Best_Fit
-{
- /**
- * Algorithm type to use for best-fit
- * (Name of this trend class)
- *
- * @var string
- **/
- protected $_bestFitType = 'polynomial';
-
- /**
- * Polynomial order
- *
- * @protected
- * @var int
- **/
- protected $_order = 0;
-
-
- /**
- * Return the order of this polynomial
- *
- * @return int
- **/
- public function getOrder() {
- return $this->_order;
- } // function getOrder()
-
-
- /**
- * Return the Y-Value for a specified value of X
- *
- * @param float $xValue X-Value
- * @return float Y-Value
- **/
- public function getValueOfYForX($xValue) {
- $retVal = $this->getIntersect();
- $slope = $this->getSlope();
- foreach($slope as $key => $value) {
- if ($value != 0.0) {
- $retVal += $value * pow($xValue, $key + 1);
- }
- }
- return $retVal;
- } // 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 ($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);
-
- $equation = 'Y = '.$intersect;
- foreach($slope as $key => $value) {
- if ($value != 0.0) {
- $equation .= ' + '.$value.' * X';
- if ($key > 0) {
- $equation .= '^'.($key + 1);
- }
- }
- }
- return $equation;
- } // 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) {
- $coefficients = array();
- foreach($this->_slope as $coefficient) {
- $coefficients[] = round($coefficient,$dp);
- }
- return $coefficients;
- }
- return $this->_slope;
- } // function getSlope()
-
-
- public function getCoefficients($dp=0) {
- return array_merge(array($this->getIntersect($dp)),$this->getSlope($dp));
- } // function getCoefficients()
-
-
- /**
- * Execute the regression and calculate the goodness of fit for a set of X and Y data values
- *
- * @param int $order Order of Polynomial for this 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 $const
- */
- private function _polynomial_regression($order, $yValues, $xValues, $const) {
- // calculate sums
- $x_sum = array_sum($xValues);
- $y_sum = array_sum($yValues);
- $xx_sum = $xy_sum = 0;
- for($i = 0; $i < $this->_valueCount; ++$i) {
- $xy_sum += $xValues[$i] * $yValues[$i];
- $xx_sum += $xValues[$i] * $xValues[$i];
- $yy_sum += $yValues[$i] * $yValues[$i];
- }
- /*
- * This routine uses logic from the PHP port of polyfit version 0.1
- * written by Michael Bommarito and Paul Meagher
- *
- * The function fits a polynomial function of order $order through
- * a series of x-y data points using least squares.
- *
- */
- for ($i = 0; $i < $this->_valueCount; ++$i) {
- for ($j = 0; $j <= $order; ++$j) {
- $A[$i][$j] = pow($xValues[$i], $j);
- }
- }
- for ($i=0; $i < $this->_valueCount; ++$i) {
- $B[$i] = array($yValues[$i]);
- }
- $matrixA = new Matrix($A);
- $matrixB = new Matrix($B);
- $C = $matrixA->solve($matrixB);
-
- $coefficients = array();
- for($i = 0; $i < $C->m; ++$i) {
- $r = $C->get($i, 0);
- if (abs($r) <= pow(10, -9)) {
- $r = 0;
- }
- $coefficients[] = $r;
- }
-
- $this->_intersect = array_shift($coefficients);
- $this->_slope = $coefficients;
-
- $this->_calculateGoodnessOfFit($x_sum,$y_sum,$xx_sum,$yy_sum,$xy_sum);
- foreach($this->_xValues as $xKey => $xValue) {
- $this->_yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
- }
- } // function _polynomial_regression()
-
-
- /**
- * Define the regression and calculate the goodness of fit for a set of X and Y data values
- *
- * @param int $order Order of Polynomial for this 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 $const
- */
- function __construct($order, $yValues, $xValues=array(), $const=True) {
- if (parent::__construct($yValues, $xValues) !== False) {
- if ($order < $this->_valueCount) {
- $this->_bestFitType .= '_'.$order;
- $this->_order = $order;
- $this->_polynomial_regression($order, $yValues, $xValues, $const);
- if (($this->getGoodnessOfFit() < 0.0) || ($this->getGoodnessOfFit() > 1.0)) {
- $this->_error = True;
- }
- } else {
- $this->_error = True;
- }
- }
- } // function __construct()
-
-} // class polynomialBestFit \ No newline at end of file
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/powerBestFitClass.php b/admin/survey/excel/PHPExcel/Shared/trend/powerBestFitClass.php
deleted file mode 100644
index 22c23d7..0000000
--- a/admin/survey/excel/PHPExcel/Shared/trend/powerBestFitClass.php
+++ /dev/null
@@ -1,142 +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_Power_Best_Fit
- *
- * @category PHPExcel
- * @package PHPExcel_Shared_Trend
- * @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
- */
-class PHPExcel_Power_Best_Fit extends PHPExcel_Best_Fit
-{
- /**
- * Algorithm type to use for best-fit
- * (Name of this trend class)
- *
- * @var string
- **/
- protected $_bestFitType = 'power';
-
-
- /**
- * Return the Y-Value for a specified value of X
- *
- * @param float $xValue X-Value
- * @return float Y-Value
- **/
- public function getValueOfYForX($xValue) {
- return $this->getIntersect() * pow(($xValue - $this->_Xoffset),$this->getSlope());
- } // 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 pow((($yValue + $this->_Yoffset) / $this->getIntersect()),(1 / $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 = '.$intersect.' * X^'.$slope;
- } // function getEquation()
-
-
- /**
- * 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 ($dp != 0) {
- return round(exp($this->_intersect),$dp);
- }
- return exp($this->_intersect);
- } // function getIntersect()
-
-
- /**
- * 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 $const
- */
- private function _power_regression($yValues, $xValues, $const) {
- foreach($xValues as &$value) {
- if ($value < 0.0) {
- $value = 0 - log(abs($value));
- } elseif ($value > 0.0) {
- $value = log($value);
- }
- }
- unset($value);
- foreach($yValues 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 _power_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) {
- $this->_power_regression($yValues, $xValues, $const);
- }
- } // function __construct()
-
-} // class powerBestFit \ No newline at end of file
diff --git a/admin/survey/excel/PHPExcel/Shared/trend/trendClass.php b/admin/survey/excel/PHPExcel/Shared/trend/trendClass.php
deleted file mode 100644
index 59d1b1f..0000000
--- a/admin/survey/excel/PHPExcel/Shared/trend/trendClass.php
+++ /dev/null
@@ -1,156 +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/linearBestFitClass.php';
-require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/logarithmicBestFitClass.php';
-require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/exponentialBestFitClass.php';
-require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/powerBestFitClass.php';
-require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/polynomialBestFitClass.php';
-
-
-/**
- * PHPExcel_trendClass
- *
- * @category PHPExcel
- * @package PHPExcel_Shared_Trend
- * @copyright Copyright (c) 2006 - 2012 PHPExcel (http://www.codeplex.com/PHPExcel)
- */
-class trendClass
-{
- const TREND_LINEAR = 'Linear';
- const TREND_LOGARITHMIC = 'Logarithmic';
- const TREND_EXPONENTIAL = 'Exponential';
- const TREND_POWER = 'Power';
- const TREND_POLYNOMIAL_2 = 'Polynomial_2';
- const TREND_POLYNOMIAL_3 = 'Polynomial_3';
- const TREND_POLYNOMIAL_4 = 'Polynomial_4';
- const TREND_POLYNOMIAL_5 = 'Polynomial_5';
- const TREND_POLYNOMIAL_6 = 'Polynomial_6';
- const TREND_BEST_FIT = 'Bestfit';
- const TREND_BEST_FIT_NO_POLY = 'Bestfit_no_Polynomials';
-
- /**
- * Names of the best-fit trend analysis methods
- *
- * @var string[]
- **/
- private static $_trendTypes = array( self::TREND_LINEAR,
- self::TREND_LOGARITHMIC,
- self::TREND_EXPONENTIAL,
- self::TREND_POWER
- );
- /**
- * Names of the best-fit trend polynomial orders
- *
- * @var string[]
- **/
- private static $_trendTypePolyOrders = array( self::TREND_POLYNOMIAL_2,
- self::TREND_POLYNOMIAL_3,
- self::TREND_POLYNOMIAL_4,
- self::TREND_POLYNOMIAL_5,
- self::TREND_POLYNOMIAL_6
- );
-
- /**
- * Cached results for each method when trying to identify which provides the best fit
- *
- * @var PHPExcel_Best_Fit[]
- **/
- private static $_trendCache = array();
-
-
- public static function calculate($trendType=self::TREND_BEST_FIT, $yValues, $xValues=array(), $const=True) {
- // Calculate number of points in each dataset
- $nY = count($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
- trigger_error("trend(): Number of elements in coordinate arrays do not match.", E_USER_ERROR);
- }
-
- $key = md5($trendType.$const.serialize($yValues).serialize($xValues));
- // Determine which trend method has been requested
- switch ($trendType) {
- // Instantiate and return the class for the requested trend method
- case self::TREND_LINEAR :
- case self::TREND_LOGARITHMIC :
- case self::TREND_EXPONENTIAL :
- case self::TREND_POWER :
- if (!isset(self::$_trendCache[$key])) {
- $className = 'PHPExcel_'.$trendType.'_Best_Fit';
- self::$_trendCache[$key] = new $className($yValues,$xValues,$const);
- }
- return self::$_trendCache[$key];
- break;
- case self::TREND_POLYNOMIAL_2 :
- case self::TREND_POLYNOMIAL_3 :
- case self::TREND_POLYNOMIAL_4 :
- case self::TREND_POLYNOMIAL_5 :
- case self::TREND_POLYNOMIAL_6 :
- if (!isset(self::$_trendCache[$key])) {
- $order = substr($trendType,-1);
- self::$_trendCache[$key] = new PHPExcel_Polynomial_Best_Fit($order,$yValues,$xValues,$const);
- }
- return self::$_trendCache[$key];
- break;
- case self::TREND_BEST_FIT :
- case self::TREND_BEST_FIT_NO_POLY :
- // If the request is to determine the best fit regression, then we test each trend line in turn
- // Start by generating an instance of each available trend method
- foreach(self::$_trendTypes as $trendMethod) {
- $className = 'PHPExcel_'.$trendMethod.'BestFit';
- $bestFit[$trendMethod] = new $className($yValues,$xValues,$const);
- $bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();
- }
- if ($trendType != self::TREND_BEST_FIT_NO_POLY) {
- foreach(self::$_trendTypePolyOrders as $trendMethod) {
- $order = substr($trendMethod,-1);
- $bestFit[$trendMethod] = new PHPExcel_Polynomial_Best_Fit($order,$yValues,$xValues,$const);
- if ($bestFit[$trendMethod]->getError()) {
- unset($bestFit[$trendMethod]);
- } else {
- $bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();
- }
- }
- }
- // Determine which of our trend lines is the best fit, and then we return the instance of that trend class
- arsort($bestFitValue);
- $bestFitType = key($bestFitValue);
- return $bestFit[$bestFitType];
- break;
- default :
- return false;
- }
- } // function calculate()
-
-} // class trendClass \ No newline at end of file