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/*****************************************************************
* @LICENSE@
*****************************************************************/
/* sre_math.c
*
* Portability for and extensions to C math library.
* RCS $Id: sre_math.c,v 1.16 2005/01/21 16:36:58 eddy Exp $
*/
#include "squidconf.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "squid.h"
/* Function: Linefit()
*
* Purpose: Given points x[0..N-1] and y[0..N-1], fit to
* a straight line y = a + bx.
* a, b, and the linear correlation coefficient r
* are filled in for return.
*
* Args: x - x values of data
* y - y values of data
* N - number of data points
* ret_a - RETURN: intercept
* ret_b - RETURN: slope
* ret_r - RETURN: correlation coefficient
*
* Return: 1 on success, 0 on failure.
*/
int
Linefit(float *x, float *y, int N, float *ret_a, float *ret_b, float *ret_r)
{
float xavg, yavg;
float sxx, syy, sxy;
int i;
/* Calculate averages, xavg and yavg
*/
xavg = yavg = 0.0;
for (i = 0; i < N; i++)
{
xavg += x[i];
yavg += y[i];
}
xavg /= (float) N;
yavg /= (float) N;
sxx = syy = sxy = 0.0;
for (i = 0; i < N; i++)
{
sxx += (x[i] - xavg) * (x[i] - xavg);
syy += (y[i] - yavg) * (y[i] - xavg);
sxy += (x[i] - xavg) * (y[i] - yavg);
}
*ret_b = sxy / sxx;
*ret_a = yavg - xavg*(*ret_b);
*ret_r = sxy / (sqrt(sxx) * sqrt(syy));
return 1;
}
/* Function: WeightedLinefit()
*
* Purpose: Given points x[0..N-1] and y[0..N-1] with
* variances (measurement errors) var[0..N-1],
* fit to a straight line y = mx + b.
*
* Method: Algorithm from Numerical Recipes in C, [Press88].
*
* Return: (void)
* ret_m contains slope; ret_b contains intercept
*/
void
WeightedLinefit(float *x, float *y, float *var, int N, float *ret_m, float *ret_b)
{
int i;
double s;
double sx, sy;
double sxx, sxy;
double delta;
double m, b;
s = sx = sy = sxx = sxy = 0.;
for (i = 0; i < N; i++)
{
s += 1./var[i];
sx += x[i] / var[i];
sy += y[i] / var[i];
sxx += x[i] * x[i] / var[i];
sxy += x[i] * y[i] / var[i];
}
delta = s * sxx - (sx * sx);
b = (sxx * sy - sx * sxy) / delta;
m = (s * sxy - sx * sy) / delta;
*ret_m = m;
*ret_b = b;
}
/* 2D matrix operations
*/
float **
FMX2Alloc(int rows, int cols)
{
float **mx;
int r;
mx = (float **) MallocOrDie(sizeof(float *) * rows);
mx[0] = (float *) MallocOrDie(sizeof(float) * rows * cols);
for (r = 1; r < rows; r++)
mx[r] = mx[0] + r*cols;
return mx;
}
void
FMX2Free(float **mx)
{
free(mx[0]);
free(mx);
}
double **
DMX2Alloc(int rows, int cols)
{
double **mx;
int r;
mx = (double **) MallocOrDie(sizeof(double *) * rows);
mx[0] = (double *) MallocOrDie(sizeof(double) * rows * cols);
for (r = 1; r < rows; r++)
mx[r] = mx[0] + r*cols;
return mx;
}
void
DMX2Free(double **mx)
{
free(mx[0]);
free(mx);
}
/* Function: FMX2Multiply()
*
* Purpose: Matrix multiplication.
* Multiply an m x p matrix A by a p x n matrix B,
* giving an m x n matrix C.
* Matrix C must be a preallocated matrix of the right
* size.
*/
void
FMX2Multiply(float **A, float **B, float **C, int m, int p, int n)
{
int i, j, k;
for (i = 0; i < m; i++)
for (j = 0; j < n; j++)
{
C[i][j] = 0.;
for (k = 0; k < p; k++)
C[i][j] += A[i][k] * B[k][j];
}
}
/* Function: FMX2Copy()
* Incept: LSJ 14 Oct 2003
* incorp of HMMER eweights code;
* SRE, Thu May 20 11:27:05 2004 [St. Louis]
*
* Purpose: Copy mx_src to mx_dest.
* mx_src is m x n (rows x columns).
* mx_dest is too, and must already be allocated.
*
* Args: mx_dest - new copy
* mx_src - matrix to be copied
*
* Returns: (void)
*/
void
FMX2Copy(float **mx_dest, float **mx_src, int m, int n)
{
int row;
for (row = 0; row < m; row++)
FCopy(mx_dest[row], mx_src[row], n);
return;
}
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