| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120 | <?phpnamespace PhpOffice\PhpSpreadsheet\Shared\Trend;class Trend{    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 = [        self::TREND_LINEAR,        self::TREND_LOGARITHMIC,        self::TREND_EXPONENTIAL,        self::TREND_POWER,    ];    /**     * Names of the best-fit Trend polynomial orders.     *     * @var string[]     */    private static $trendTypePolynomialOrders = [        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 bestFit[]     */    private static $trendCache = [];    public static function calculate($trendType = self::TREND_BEST_FIT, $yValues = [], $xValues = [], $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 = '\PhpOffice\PhpSpreadsheet\Shared\Trend\\' . $trendType . 'BestFit';                    self::$trendCache[$key] = new $className($yValues, $xValues, $const);                }                return self::$trendCache[$key];            case self::TREND_POLYNOMIAL_2:            case self::TREND_POLYNOMIAL_3:            case self::TREND_POLYNOMIAL_4:            case self::TREND_POLYNOMIAL_5:            case self::TREND_POLYNOMIAL_6:                if (!isset(self::$trendCache[$key])) {                    $order = substr($trendType, -1);                    self::$trendCache[$key] = new PolynomialBestFit($order, $yValues, $xValues, $const);                }                return self::$trendCache[$key];            case self::TREND_BEST_FIT:            case self::TREND_BEST_FIT_NO_POLY:                //    If the request is to determine the best fit regression, then we test each Trend line in turn                //    Start by generating an instance of each available Trend method                foreach (self::$trendTypes as $trendMethod) {                    $className = '\PhpOffice\PhpSpreadsheet\Shared\Trend\\' . $trendType . 'BestFit';                    $bestFit[$trendMethod] = new $className($yValues, $xValues, $const);                    $bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();                }                if ($trendType != self::TREND_BEST_FIT_NO_POLY) {                    foreach (self::$trendTypePolynomialOrders as $trendMethod) {                        $order = substr($trendMethod, -1);                        $bestFit[$trendMethod] = new PolynomialBestFit($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];            default:                return false;        }    }}
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