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

ExponentialBestFit.php in Visualizer – Tables & Charts Manager with Built-in AI Generator 3.7.4, at vendor/phpoffice/phpspreadsheet/src/PhpSpreadsheet/Shared/Trend/ExponentialBestFit.php

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1	<?php
2
3	namespace PhpOffice\PhpSpreadsheet\Shared\Trend;
4
5	class ExponentialBestFit 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 = 'exponential';
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 $this->getIntersect() * pow($this->getSlope(), ($xValue - $this->xOffset));
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 log(($yValue + $this->yOffset) / $this->getIntersect()) / log($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 . ' * ' . $slope . '^X';
52	}
53
54	/**
55	* Return the Slope of the line.
56	*
57	* @param int $dp Number of places of decimal precision to display
58	*
59	* @return float
60	*/
61	public function getSlope($dp = 0)
62	{
63	if ($dp != 0) {
64	return round(exp($this->slope), $dp);
65	}
66
67	return exp($this->slope);
68	}
69
70	/**
71	* Return the Value of X where it intersects Y = 0.
72	*
73	* @param int $dp Number of places of decimal precision to display
74	*
75	* @return float
76	*/
77	public function getIntersect($dp = 0)
78	{
79	if ($dp != 0) {
80	return round(exp($this->intersect), $dp);
81	}
82
83	return exp($this->intersect);
84	}
85
86	/**
87	* Execute the regression and calculate the goodness of fit for a set of X and Y data values.
88	*
89	* @param float[] $yValues The set of Y-values for this regression
90	* @param float[] $xValues The set of X-values for this regression
91	* @param bool $const
92	*/
93	private function exponentialRegression($yValues, $xValues, $const)
94	{
95	foreach ($yValues as &$value) {
96	if ($value < 0.0) {
97	$value = 0 - log(abs($value));
98	} elseif ($value > 0.0) {
99	$value = log($value);
100	}
101	}
102	unset($value);
103
104	$this->leastSquareFit($yValues, $xValues, $const);
105	}
106
107	/**
108	* Define the regression and calculate the goodness of fit for a set of X and Y data values.
109	*
110	* @param float[] $yValues The set of Y-values for this regression
111	* @param float[] $xValues The set of X-values for this regression
112	* @param bool $const
113	*/
114	public function __construct($yValues, $xValues = [], $const = true)
115	{
116	parent::__construct($yValues, $xValues);
117
118	if (!$this->error) {
119	$this->exponentialRegression($yValues, $xValues, $const);
120	}
121	}
122	}
123