visualizer / vendor / phpoffice / phpexcel / Classes / PHPExcel / Shared / trend / linearBestFitClass.php

linearBestFitClass.php in Visualizer – Tables & Charts Manager with Built-in AI Generator 2.2.0, at vendor/phpoffice/phpexcel/Classes/PHPExcel/Shared/trend/linearBestFitClass.php

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1	<?php
2	/**
3	* PHPExcel
4	*
5	* Copyright (c) 2006 - 2014 PHPExcel
6	*
7	* This library is free software; you can redistribute it and/or
8	* modify it under the terms of the GNU Lesser General Public
9	* License as published by the Free Software Foundation; either
10	* version 2.1 of the License, or (at your option) any later version.
11	*
12	* This library is distributed in the hope that it will be useful,
13	* but WITHOUT ANY WARRANTY; without even the implied warranty of
14	* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
15	* Lesser General Public License for more details.
16	*
17	* You should have received a copy of the GNU Lesser General Public
18	* License along with this library; if not, write to the Free Software
19	* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
20	*
21	* @category PHPExcel
22	* @package PHPExcel_Shared_Trend
23	* @copyright Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
24	* @license http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt LGPL
25	* @version ##VERSION##, ##DATE##
26	*/
27
28
29	require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
30
31
32	/**
33	* PHPExcel_Linear_Best_Fit
34	*
35	* @category PHPExcel
36	* @package PHPExcel_Shared_Trend
37	* @copyright Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
38	*/
39	class PHPExcel_Linear_Best_Fit extends PHPExcel_Best_Fit
40	{
41	/**
42	* Algorithm type to use for best-fit
43	* (Name of this trend class)
44	*
45	* @var string
46	**/
47	protected $_bestFitType = 'linear';
48
49
50	/**
51	* Return the Y-Value for a specified value of X
52	*
53	* @param float $xValue X-Value
54	* @return float Y-Value
55	**/
56	public function getValueOfYForX($xValue) {
57	return $this->getIntersect() + $this->getSlope() * $xValue;
58	} // function getValueOfYForX()
59
60
61	/**
62	* Return the X-Value for a specified value of Y
63	*
64	* @param float $yValue Y-Value
65	* @return float X-Value
66	**/
67	public function getValueOfXForY($yValue) {
68	return ($yValue - $this->getIntersect()) / $this->getSlope();
69	} // function getValueOfXForY()
70
71
72	/**
73	* Return the Equation of the best-fit line
74	*
75	* @param int $dp Number of places of decimal precision to display
76	* @return string
77	**/
78	public function getEquation($dp=0) {
79	$slope = $this->getSlope($dp);
80	$intersect = $this->getIntersect($dp);
81
82	return 'Y = '.$intersect.' + '.$slope.' * X';
83	} // function getEquation()
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 boolean $const
92	*/
93	private function _linear_regression($yValues, $xValues, $const) {
94	$this->_leastSquareFit($yValues, $xValues,$const);
95	} // function _linear_regression()
96
97
98	/**
99	* Define the regression and calculate the goodness of fit for a set of X and Y data values
100	*
101	* @param float[] $yValues The set of Y-values for this regression
102	* @param float[] $xValues The set of X-values for this regression
103	* @param boolean $const
104	*/
105	function __construct($yValues, $xValues=array(), $const=True) {
106	if (parent::__construct($yValues, $xValues) !== False) {
107	$this->_linear_regression($yValues, $xValues, $const);
108	}
109	} // function __construct()
110
111	} // class linearBestFit