167 lines
		
	
	
		
			4.7 KiB
		
	
	
	
		
			PHP
		
	
	
	
	
	
		
		
			
		
	
	
			167 lines
		
	
	
		
			4.7 KiB
		
	
	
	
		
			PHP
		
	
	
	
	
	
|   | <?php | ||
|  | /** | ||
|  |  * PHPExcel | ||
|  |  * | ||
|  |  * Copyright (c) 2006 - 2010 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_Best_Fit | ||
|  |  * @copyright  Copyright (c) 2006 - 2010 PHPExcel (http://www.codeplex.com/PHPExcel) | ||
|  |  * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL | ||
|  |  * @version    ##VERSION##, ##DATE##
 | ||
|  |  */ | ||
|  | 
 | ||
|  | 
 | ||
|  | 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_Best_Fit | ||
|  |  * @copyright  Copyright (c) 2006 - 2010 PHPExcel (http://www.codeplex.com/PHPExcel) | ||
|  |  */ | ||
|  | class PHPExcel_Polynomial_Best_Fit extends PHPExcel_Best_Fit | ||
|  | { | ||
|  | 	protected $_bestFitType		= 'polynomial'; | ||
|  | 
 | ||
|  | 	protected $_order			= 0; | ||
|  | 
 | ||
|  | 
 | ||
|  | 	public function getOrder() { | ||
|  | 		return $this->_order; | ||
|  | 	}	//	function getOrder()
 | ||
|  | 
 | ||
|  | 
 | ||
|  | 	public function getValueOfYForX($xValue) { | ||
|  | 		$retVal = $this->getIntersect(); | ||
|  | 		$slope = $this->getSlope(); | ||
|  | 		foreach($slope as $key => $value) { | ||
|  | 			if ($value != 0.0) { | ||
|  | 				$retVal += $value * pow($xValue, $key + 1); | ||
|  | 			} | ||
|  | 		} | ||
|  | 		return $retVal; | ||
|  | 	}	//	function getValueOfYForX()
 | ||
|  | 
 | ||
|  | 
 | ||
|  | 	public function getValueOfXForY($yValue) { | ||
|  | 		return ($yValue - $this->getIntersect()) / $this->getSlope(); | ||
|  | 	}	//	function getValueOfXForY()
 | ||
|  | 
 | ||
|  | 
 | ||
|  | 	public function getEquation($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 $equation; | ||
|  | 	}	//	function getEquation()
 | ||
|  | 
 | ||
|  | 
 | ||
|  | 	public function getSlope($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()
 | ||
|  | 
 | ||
|  | 
 | ||
|  | 	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()
 | ||
|  | 
 | ||
|  | 
 | ||
|  | 	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
 |