visualizer / vendor / phpoffice / phpspreadsheet / src / PhpSpreadsheet / Shared / Trend / PowerBestFit.php

PowerBestFit.php in Visualizer – Tables & Charts Manager with Built-in AI Generator 3.7.11, at vendor/phpoffice/phpspreadsheet/src/PhpSpreadsheet/Shared/Trend/PowerBestFit.php

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1	<?php
2
3	namespace PhpOffice\PhpSpreadsheet\Shared\Trend;
4
5	class PowerBestFit extends BestFit
6	{
7	/**
8	* Algorithm type to use for best-fit
9	* (Name of this Trend class).
10	*
11	* @var string
12	*/
13	protected $bestFitType = 'power';
14
15	/**
16	* Return the Y-Value for a specified value of X.
17	*
18	* @param float $xValue X-Value
19	*
20	* @return float Y-Value
21	*/
22	public function getValueOfYForX($xValue)
23	{
24	return $this->getIntersect() * pow(($xValue - $this->xOffset), $this->getSlope());
25	}
26
27	/**
28	* Return the X-Value for a specified value of Y.
29	*
30	* @param float $yValue Y-Value
31	*
32	* @return float X-Value
33	*/
34	public function getValueOfXForY($yValue)
35	{
36	return pow((($yValue + $this->yOffset) / $this->getIntersect()), (1 / $this->getSlope()));
37	}
38
39	/**
40	* Return the Equation of the best-fit line.
41	*
42	* @param int $dp Number of places of decimal precision to display
43	*
44	* @return string
45	*/
46	public function getEquation($dp = 0)
47	{
48	$slope = $this->getSlope($dp);
49	$intersect = $this->getIntersect($dp);
50
51	return 'Y = ' . $intersect . ' * X^' . $slope;
52	}
53
54	/**
55	* Return the Value of X where it intersects Y = 0.
56	*
57	* @param int $dp Number of places of decimal precision to display
58	*
59	* @return float
60	*/
61	public function getIntersect($dp = 0)
62	{
63	if ($dp != 0) {
64	return round(exp($this->intersect), $dp);
65	}
66
67	return exp($this->intersect);
68	}
69
70	/**
71	* Execute the regression and calculate the goodness of fit for a set of X and Y data values.
72	*
73	* @param float[] $yValues The set of Y-values for this regression
74	* @param float[] $xValues The set of X-values for this regression
75	* @param bool $const
76	*/
77	private function powerRegression($yValues, $xValues, $const)
78	{
79	foreach ($xValues as &$value) {
80	if ($value < 0.0) {
81	$value = 0 - log(abs($value));
82	} elseif ($value > 0.0) {
83	$value = log($value);
84	}
85	}
86	unset($value);
87	foreach ($yValues as &$value) {
88	if ($value < 0.0) {
89	$value = 0 - log(abs($value));
90	} elseif ($value > 0.0) {
91	$value = log($value);
92	}
93	}
94	unset($value);
95
96	$this->leastSquareFit($yValues, $xValues, $const);
97	}
98
99	/**
100	* Define the regression and calculate the goodness of fit for a set of X and Y data values.
101	*
102	* @param float[] $yValues The set of Y-values for this regression
103	* @param float[] $xValues The set of X-values for this regression
104	* @param bool $const
105	*/
106	public function __construct($yValues, $xValues = [], $const = true)
107	{
108	parent::__construct($yValues, $xValues);
109
110	if (!$this->error) {
111	$this->powerRegression($yValues, $xValues, $const);
112	}
113	}
114	}
115