<?php

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';


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';

	private static $_trendTypes = array( self::TREND_LINEAR,
										 self::TREND_LOGARITHMIC,
										 self::TREND_EXPONENTIAL,
										 self::TREND_POWER
									   );
	private static $_trendTypePolyOrders = array( self::TREND_POLYNOMIAL_2,
												  self::TREND_POLYNOMIAL_3,
												  self::TREND_POLYNOMIAL_4,
												  self::TREND_POLYNOMIAL_5,
												  self::TREND_POLYNOMIAL_6
											    );

	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