121 lines
4.6 KiB
PHP
121 lines
4.6 KiB
PHP
<?php
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namespace PhpOffice\PhpSpreadsheet\Shared\Trend;
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class Trend
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{
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const TREND_LINEAR = 'Linear';
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const TREND_LOGARITHMIC = 'Logarithmic';
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const TREND_EXPONENTIAL = 'Exponential';
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const TREND_POWER = 'Power';
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const TREND_POLYNOMIAL_2 = 'Polynomial_2';
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const TREND_POLYNOMIAL_3 = 'Polynomial_3';
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const TREND_POLYNOMIAL_4 = 'Polynomial_4';
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const TREND_POLYNOMIAL_5 = 'Polynomial_5';
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const TREND_POLYNOMIAL_6 = 'Polynomial_6';
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const TREND_BEST_FIT = 'Bestfit';
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const TREND_BEST_FIT_NO_POLY = 'Bestfit_no_Polynomials';
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/**
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* Names of the best-fit Trend analysis methods.
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*
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* @var string[]
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*/
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private static $trendTypes = [
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self::TREND_LINEAR,
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self::TREND_LOGARITHMIC,
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self::TREND_EXPONENTIAL,
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self::TREND_POWER,
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];
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/**
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* Names of the best-fit Trend polynomial orders.
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*
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* @var string[]
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*/
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private static $trendTypePolynomialOrders = [
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self::TREND_POLYNOMIAL_2,
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self::TREND_POLYNOMIAL_3,
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self::TREND_POLYNOMIAL_4,
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self::TREND_POLYNOMIAL_5,
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self::TREND_POLYNOMIAL_6,
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];
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/**
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* Cached results for each method when trying to identify which provides the best fit.
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*
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* @var bestFit[]
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*/
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private static $trendCache = [];
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public static function calculate($trendType = self::TREND_BEST_FIT, $yValues = [], $xValues = [], $const = true)
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{
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// Calculate number of points in each dataset
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$nY = count($yValues);
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$nX = count($xValues);
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// Define X Values if necessary
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if ($nX == 0) {
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$xValues = range(1, $nY);
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$nX = $nY;
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} elseif ($nY != $nX) {
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// Ensure both arrays of points are the same size
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trigger_error('Trend(): Number of elements in coordinate arrays do not match.', E_USER_ERROR);
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}
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$key = md5($trendType . $const . serialize($yValues) . serialize($xValues));
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// Determine which Trend method has been requested
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switch ($trendType) {
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// Instantiate and return the class for the requested Trend method
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case self::TREND_LINEAR:
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case self::TREND_LOGARITHMIC:
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case self::TREND_EXPONENTIAL:
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case self::TREND_POWER:
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if (!isset(self::$trendCache[$key])) {
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$className = '\PhpOffice\PhpSpreadsheet\Shared\Trend\\' . $trendType . 'BestFit';
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self::$trendCache[$key] = new $className($yValues, $xValues, $const);
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}
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return self::$trendCache[$key];
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case self::TREND_POLYNOMIAL_2:
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case self::TREND_POLYNOMIAL_3:
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case self::TREND_POLYNOMIAL_4:
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case self::TREND_POLYNOMIAL_5:
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case self::TREND_POLYNOMIAL_6:
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if (!isset(self::$trendCache[$key])) {
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$order = substr($trendType, -1);
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self::$trendCache[$key] = new PolynomialBestFit($order, $yValues, $xValues, $const);
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}
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return self::$trendCache[$key];
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case self::TREND_BEST_FIT:
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case self::TREND_BEST_FIT_NO_POLY:
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// If the request is to determine the best fit regression, then we test each Trend line in turn
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// Start by generating an instance of each available Trend method
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foreach (self::$trendTypes as $trendMethod) {
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$className = '\PhpOffice\PhpSpreadsheet\Shared\Trend\\' . $trendType . 'BestFit';
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$bestFit[$trendMethod] = new $className($yValues, $xValues, $const);
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$bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();
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}
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if ($trendType != self::TREND_BEST_FIT_NO_POLY) {
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foreach (self::$trendTypePolynomialOrders as $trendMethod) {
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$order = substr($trendMethod, -1);
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$bestFit[$trendMethod] = new PolynomialBestFit($order, $yValues, $xValues, $const);
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if ($bestFit[$trendMethod]->getError()) {
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unset($bestFit[$trendMethod]);
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} else {
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$bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();
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}
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}
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}
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// Determine which of our Trend lines is the best fit, and then we return the instance of that Trend class
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arsort($bestFitValue);
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$bestFitType = key($bestFitValue);
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return $bestFit[$bestFitType];
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default:
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return false;
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}
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}
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}
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