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<?php
namespace 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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