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 (21 years, 2 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
#	Content
1	#ifndef lint
2	static const char RCSid[] = "$Id$";
3	#endif
4	/*
5	* Basic linear regression calculation.
6	*/
7
8	/* ====================================================================
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	#include <math.h>
66
67	#include "linregr.h"
68
69
70	void
71	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	int
80	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	int
94	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	}