src/common/linregr.c

#ifndef lint
static const char       RCSid[] = "$Id$";
#endif
/*
 * Basic linear regression calculation.
 */

/* ====================================================================
 * The Radiance Software License, Version 1.0
 *
 * Copyright (c) 1990 - 2002 The Regents of the University of California,
 * through Lawrence Berkeley National Laboratory.   All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
 * 1. Redistributions of source code must retain the above copyright
 *         notice, this list of conditions and the following disclaimer.
 *
 * 2. Redistributions in binary form must reproduce the above copyright
 *       notice, this list of conditions and the following disclaimer in
 *       the documentation and/or other materials provided with the
 *       distribution.
 *
 * 3. The end-user documentation included with the redistribution,
 *           if any, must include the following acknowledgment:
 *             "This product includes Radiance software
 *                 (http://radsite.lbl.gov/)
 *                 developed by the Lawrence Berkeley National Laboratory
 *               (http://www.lbl.gov/)."
 *       Alternately, this acknowledgment may appear in the software itself,
 *       if and wherever such third-party acknowledgments normally appear.
 *
 * 4. The names "Radiance," "Lawrence Berkeley National Laboratory"
 *       and "The Regents of the University of California" must
 *       not be used to endorse or promote products derived from this
 *       software without prior written permission. For written
 *       permission, please contact [email protected].
 *
 * 5. Products derived from this software may not be called "Radiance",
 *       nor may "Radiance" appear in their name, without prior written
 *       permission of Lawrence Berkeley National Laboratory.
 *
 * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
 * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
 * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED.   IN NO EVENT SHALL Lawrence Berkeley National Laboratory OR
 * ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
 * USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
 * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
 * SUCH DAMAGE.
 * ====================================================================
 *
 * This software consists of voluntary contributions made by many
 * individuals on behalf of Lawrence Berkeley National Laboratory.   For more
 * information on Lawrence Berkeley National Laboratory, please see
 * <http://www.lbl.gov/>.
 */

#include <math.h>

#include "linregr.h"


void
lrclear(l)                      /* initialize sum */
register LRSUM  *l;
{
        l->xs = l->ys = l->xxs = l->yys = l->xys = 0.0;
        l->n = 0;
}


int
flrpoint(x, y, l)               /* add point (x,y) to sum */
double  x, y;
register LRSUM  *l;
{
        l->xs += x;
        l->ys += y;
        l->xxs += x*x;
        l->yys += y*y;
        l->xys += x*y;
        return(++l->n);
}


int
lrfit(r, l)                     /* compute linear regression */
register LRLIN  *r;
register LRSUM  *l;
{
        double  nxvar, nyvar;

        if (l->n < 2)
                return(-1);
        nxvar = l->xxs - l->xs*l->xs/l->n;
        nyvar = l->yys - l->ys*l->ys/l->n;
        if (nxvar == 0.0 || nyvar == 0.0)
                return(-1);
        r->slope = (l->xys - l->xs*l->ys/l->n) / nxvar;
        r->intercept = (l->ys - r->slope*l->xs) / l->n;
        r->correlation = r->slope*sqrt(nxvar/nyvar);
        return(0);
}
Revision:	2.3
Committed:	Sat Feb 22 02:07:22 2003 UTC (22 years, 8 months ago) by greg
Content type:	text/plain
Branch:	MAIN
Changes since 2.2:	+61 -4 lines
Log Message:	Changes and check-in for 3.5 release Includes new source files and modifications not recorded for many years See ray/doc/notes/ReleaseNotes for notes between 3.1 and 3.5 release
#	User	Rev	Content
1	greg	1.1	#ifndef lint
2	greg	2.3	static const char RCSid[] = "$Id$";
3	greg	1.1	#endif
4			/*
5			* Basic linear regression calculation.
6			*/
7
8	greg	2.3	/* ====================================================================
9			* The Radiance Software License, Version 1.0
10			*
11			* Copyright (c) 1990 - 2002 The Regents of the University of California,
12			* through Lawrence Berkeley National Laboratory. All rights reserved.
13			*
14			* Redistribution and use in source and binary forms, with or without
15			* modification, are permitted provided that the following conditions
16			* are met:
17			*
18			* 1. Redistributions of source code must retain the above copyright
19			* notice, this list of conditions and the following disclaimer.
20			*
21			* 2. Redistributions in binary form must reproduce the above copyright
22			* notice, this list of conditions and the following disclaimer in
23			* the documentation and/or other materials provided with the
24			* distribution.
25			*
26			* 3. The end-user documentation included with the redistribution,
27			* if any, must include the following acknowledgment:
28			* "This product includes Radiance software
29			* (http://radsite.lbl.gov/)
30			* developed by the Lawrence Berkeley National Laboratory
31			* (http://www.lbl.gov/)."
32			* Alternately, this acknowledgment may appear in the software itself,
33			* if and wherever such third-party acknowledgments normally appear.
34			*
35			* 4. The names "Radiance," "Lawrence Berkeley National Laboratory"
36			* and "The Regents of the University of California" must
37			* not be used to endorse or promote products derived from this
38			* software without prior written permission. For written
39			* permission, please contact [email protected].
40			*
41			* 5. Products derived from this software may not be called "Radiance",
42			* nor may "Radiance" appear in their name, without prior written
43			* permission of Lawrence Berkeley National Laboratory.
44			*
45			* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
46			* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
47			* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
48			* DISCLAIMED. IN NO EVENT SHALL Lawrence Berkeley National Laboratory OR
49			* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
50			* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
51			* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
52			* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
53			* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
54			* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
55			* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
56			* SUCH DAMAGE.
57			* ====================================================================
58			*
59			* This software consists of voluntary contributions made by many
60			* individuals on behalf of Lawrence Berkeley National Laboratory. For more
61			* information on Lawrence Berkeley National Laboratory, please see
62			* <http://www.lbl.gov/>.
63			*/
64
65	greg	2.2	#include <math.h>
66
67	greg	1.1	#include "linregr.h"
68
69
70	greg	2.3	void
71	greg	1.1	lrclear(l) /* initialize sum */
72			register LRSUM *l;
73			{
74			l->xs = l->ys = l->xxs = l->yys = l->xys = 0.0;
75			l->n = 0;
76			}
77
78
79	greg	2.3	int
80	greg	1.1	flrpoint(x, y, l) /* add point (x,y) to sum */
81			double x, y;
82			register LRSUM *l;
83			{
84			l->xs += x;
85			l->ys += y;
86			l->xxs += x*x;
87			l->yys += y*y;
88			l->xys += x*y;
89			return(++l->n);
90			}
91
92
93	greg	2.3	int
94	greg	1.1	lrfit(r, l) /* compute linear regression */
95			register LRLIN *r;
96			register LRSUM *l;
97			{
98			double nxvar, nyvar;
99
100			if (l->n < 2)
101			return(-1);
102			nxvar = l->xxs - l->xs*l->xs/l->n;
103			nyvar = l->yys - l->ys*l->ys/l->n;
104			if (nxvar == 0.0 \|\| nyvar == 0.0)
105			return(-1);
106			r->slope = (l->xys - l->xs*l->ys/l->n) / nxvar;
107			r->intercept = (l->ys - r->slope*l->xs) / l->n;
108			r->correlation = r->slope*sqrt(nxvar/nyvar);
109			return(0);
110			}