<?php
|
|
namespace PhpOffice\PhpSpreadsheet\Shared\Trend;
|
|
use Matrix\Matrix;
|
|
// Phpstan and Scrutinizer seem to have legitimate complaints.
|
// $this->slope is specified where an array is expected in several places.
|
// But it seems that it should always be float.
|
// This code is probably not exercised at all in unit tests.
|
class PolynomialBestFit extends BestFit
|
{
|
/**
|
* Algorithm type to use for best-fit
|
* (Name of this Trend class).
|
*/
|
protected string $bestFitType = 'polynomial';
|
|
/**
|
* Polynomial order.
|
*/
|
protected int $order = 0;
|
|
/**
|
* Return the order of this polynomial.
|
*/
|
public function getOrder(): int
|
{
|
return $this->order;
|
}
|
|
/**
|
* Return the Y-Value for a specified value of X.
|
*
|
* @param float $xValue X-Value
|
*
|
* @return float Y-Value
|
*/
|
public function getValueOfYForX(float $xValue): float
|
{
|
$retVal = $this->getIntersect();
|
$slope = $this->getSlope();
|
// Phpstan and Scrutinizer are both correct - getSlope returns float, not array.
|
// @phpstan-ignore-next-line
|
foreach ($slope as $key => $value) {
|
if ($value != 0.0) {
|
$retVal += $value * $xValue ** ($key + 1);
|
}
|
}
|
|
return $retVal;
|
}
|
|
/**
|
* Return the X-Value for a specified value of Y.
|
*
|
* @param float $yValue Y-Value
|
*
|
* @return float X-Value
|
*/
|
public function getValueOfXForY(float $yValue): float
|
{
|
return ($yValue - $this->getIntersect()) / $this->getSlope();
|
}
|
|
/**
|
* Return the Equation of the best-fit line.
|
*
|
* @param int $dp Number of places of decimal precision to display
|
*/
|
public function getEquation(int $dp = 0): string
|
{
|
$slope = $this->getSlope($dp);
|
$intersect = $this->getIntersect($dp);
|
|
$equation = 'Y = ' . $intersect;
|
// Phpstan and Scrutinizer are both correct - getSlope returns float, not array.
|
// @phpstan-ignore-next-line
|
foreach ($slope as $key => $value) {
|
if ($value != 0.0) {
|
$equation .= ' + ' . $value . ' * X';
|
if ($key > 0) {
|
$equation .= '^' . ($key + 1);
|
}
|
}
|
}
|
|
return $equation;
|
}
|
|
/**
|
* Return the Slope of the line.
|
*
|
* @param int $dp Number of places of decimal precision to display
|
*/
|
public function getSlope(int $dp = 0): float
|
{
|
if ($dp != 0) {
|
$coefficients = [];
|
//* @phpstan-ignore-next-line
|
foreach ($this->slope as $coefficient) {
|
$coefficients[] = round($coefficient, $dp);
|
}
|
|
// @phpstan-ignore-next-line
|
return $coefficients;
|
}
|
|
return $this->slope;
|
}
|
|
public function getCoefficients(int $dp = 0): array
|
{
|
// Phpstan and Scrutinizer are both correct - getSlope returns float, not array.
|
// @phpstan-ignore-next-line
|
return array_merge([$this->getIntersect($dp)], $this->getSlope($dp));
|
}
|
|
/**
|
* Execute the regression and calculate the goodness of fit for a set of X and Y data values.
|
*
|
* @param int $order Order of Polynomial for this regression
|
* @param float[] $yValues The set of Y-values for this regression
|
* @param float[] $xValues The set of X-values for this regression
|
*/
|
private function polynomialRegression(int $order, array $yValues, array $xValues): void
|
{
|
// calculate sums
|
$x_sum = array_sum($xValues);
|
$y_sum = array_sum($yValues);
|
$xx_sum = $xy_sum = $yy_sum = 0;
|
for ($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.
|
*
|
*/
|
$A = [];
|
$B = [];
|
for ($i = 0; $i < $this->valueCount; ++$i) {
|
for ($j = 0; $j <= $order; ++$j) {
|
$A[$i][$j] = $xValues[$i] ** $j;
|
}
|
}
|
for ($i = 0; $i < $this->valueCount; ++$i) {
|
$B[$i] = [$yValues[$i]];
|
}
|
$matrixA = new Matrix($A);
|
$matrixB = new Matrix($B);
|
$C = $matrixA->solve($matrixB);
|
|
$coefficients = [];
|
for ($i = 0; $i < $C->rows; ++$i) {
|
$r = $C->getValue($i + 1, 1); // row and column are origin-1
|
if (abs($r) <= 10 ** (-9)) {
|
$r = 0;
|
}
|
$coefficients[] = $r;
|
}
|
|
$this->intersect = array_shift($coefficients);
|
// Phpstan is correct
|
//* @phpstan-ignore-next-line
|
$this->slope = $coefficients;
|
|
$this->calculateGoodnessOfFit($x_sum, $y_sum, $xx_sum, $yy_sum, $xy_sum, 0, 0, 0);
|
foreach ($this->xValues as $xKey => $xValue) {
|
$this->yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
|
}
|
}
|
|
/**
|
* Define the regression and calculate the goodness of fit for a set of X and Y data values.
|
*
|
* @param int $order Order of Polynomial for this regression
|
* @param float[] $yValues The set of Y-values for this regression
|
* @param float[] $xValues The set of X-values for this regression
|
*/
|
public function __construct(int $order, array $yValues, array $xValues = [])
|
{
|
parent::__construct($yValues, $xValues);
|
|
if (!$this->error) {
|
if ($order < $this->valueCount) {
|
$this->bestFitType .= '_' . $order;
|
$this->order = $order;
|
$this->polynomialRegression($order, $yValues, $xValues);
|
if (($this->getGoodnessOfFit() < 0.0) || ($this->getGoodnessOfFit() > 1.0)) {
|
$this->error = true;
|
}
|
} else {
|
$this->error = true;
|
}
|
}
|
}
|
}
|
