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 1.8.0, 2014-03-02
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