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
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
|
<?php
/**
* PHPExcel
*
* Copyright (c) 2006 - 2014 PHPExcel
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*
* @category PHPExcel
* @package PHPExcel_Shared_Trend
* @copyright Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
* @license http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt LGPL
* @version 1.8.0, 2014-03-02
*/
require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
/**
* PHPExcel_Exponential_Best_Fit
*
* @category PHPExcel
* @package PHPExcel_Shared_Trend
* @copyright Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
*/
class PHPExcel_Exponential_Best_Fit extends PHPExcel_Best_Fit
{
/**
* Algorithm type to use for best-fit
* (Name of this trend class)
*
* @var string
**/
protected $_bestFitType = 'exponential';
/**
* Return the Y-Value for a specified value of X
*
* @param float $xValue X-Value
* @return float Y-Value
**/
public function getValueOfYForX($xValue) {
return $this->getIntersect() * pow($this->getSlope(),($xValue - $this->_Xoffset));
} // function getValueOfYForX()
/**
* Return the X-Value for a specified value of Y
*
* @param float $yValue Y-Value
* @return float X-Value
**/
public function getValueOfXForY($yValue) {
return log(($yValue + $this->_Yoffset) / $this->getIntersect()) / log($this->getSlope());
} // function getValueOfXForY()
/**
* 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.'^X';
} // function getEquation()
/**
* Return the Slope of the line
*
* @param int $dp Number of places of decimal precision to display
* @return string
**/
public function getSlope($dp=0) {
if ($dp != 0) {
return round(exp($this->_slope),$dp);
}
return exp($this->_slope);
} // function getSlope()
/**
* Return the Value of X where it intersects Y = 0
*
* @param int $dp Number of places of decimal precision to display
* @return string
**/
public function getIntersect($dp=0) {
if ($dp != 0) {
return round(exp($this->_intersect),$dp);
}
return exp($this->_intersect);
} // function getIntersect()
/**
* 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 boolean $const
*/
private function _exponential_regression($yValues, $xValues, $const) {
foreach($yValues 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);
} // function _exponential_regression()
/**
* 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 boolean $const
*/
function __construct($yValues, $xValues=array(), $const=True) {
if (parent::__construct($yValues, $xValues) !== False) {
$this->_exponential_regression($yValues, $xValues, $const);
}
} // function __construct()
} // class exponentialBestFit
|