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<?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## |
*/ |
|
|
/** |
* PHPExcel_Best_Fit |
* |
* @category PHPExcel |
* @package PHPExcel_Shared_Trend |
* @copyright Copyright (c) 2006 - 2013 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(); |
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protected $_goodnessOfFit = 1; |
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protected $_stdevOfResiduals = 0; |
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protected $_covariance = 0; |
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protected $_correlation = 0; |
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protected $_SSRegression = 0; |
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protected $_SSResiduals = 0; |
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protected $_DFResiduals = 0; |
|
protected $_F = 0; |
|
protected $_slope = 0; |
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protected $_slopeSE = 0; |
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protected $_intersect = 0; |
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protected $_intersectSE = 0; |
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protected $_Xoffset = 0; |
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protected $_Yoffset = 0; |
|
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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 $this->_SSResiduals; |
} // function getSSResiduals() |
|
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public function getDFResiduals($dp=0) { |
if ($dp != 0) { |
return round($this->_DFResiduals,$dp); |
} |
return $this->_DFResiduals; |
} // function getDFResiduals() |
|
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public function getF($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 $this->_yBestFitValues; |
} // function getYBestFitValues() |
|
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protected function _calculateGoodnessOfFit($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 |