blob: 4f2c805102484f9856b19682f7cdae3064c5a91c (
plain) (
blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
|
<?php
namespace PhpOffice\PhpSpreadsheet\Shared\Trend;
class LogarithmicBestFit extends BestFit
{
/**
* Algorithm type to use for best-fit
* (Name of this Trend class).
*
* @var string
*/
protected $bestFitType = 'logarithmic';
/**
* Return the Y-Value for a specified value of X.
*
* @param float $xValue X-Value
*
* @return float Y-Value
*/
public function getValueOfYForX($xValue)
{
return $this->getIntersect() + $this->getSlope() * log($xValue - $this->xOffset);
}
/**
* Return the X-Value for a specified value of Y.
*
* @param float $yValue Y-Value
*
* @return float X-Value
*/
public function getValueOfXForY($yValue)
{
return exp(($yValue - $this->getIntersect()) / $this->getSlope());
}
/**
* Return the Equation of the best-fit line.
*
* @param int $dp Number of places of decimal precision to display
*
* @return string
*/
public function getEquation($dp = 0)
{
$slope = $this->getSlope($dp);
$intersect = $this->getIntersect($dp);
return 'Y = ' . $intersect . ' + ' . $slope . ' * log(X)';
}
/**
* Execute the regression and calculate the goodness of fit for a set of X and Y data values.
*
* @param float[] $yValues The set of Y-values for this regression
* @param float[] $xValues The set of X-values for this regression
* @param bool $const
*/
private function logarithmicRegression($yValues, $xValues, $const): void
{
foreach ($xValues as &$value) {
if ($value < 0.0) {
$value = 0 - log(abs($value));
} elseif ($value > 0.0) {
$value = log($value);
}
}
unset($value);
$this->leastSquareFit($yValues, $xValues, $const);
}
/**
* Define the regression and calculate the goodness of fit for a set of X and Y data values.
*
* @param float[] $yValues The set of Y-values for this regression
* @param float[] $xValues The set of X-values for this regression
* @param bool $const
*/
public function __construct($yValues, $xValues = [], $const = true)
{
parent::__construct($yValues, $xValues);
if (!$this->error) {
$this->logarithmicRegression($yValues, $xValues, $const);
}
}
}
|
