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svd.h
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svd.h
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/*
* svdcomp - SVD decomposition routine.
* Takes an mxn matrix a and decomposes it into udv, where u,v are
* left and right orthogonal transformation matrices, and d is a
* diagonal matrix of singular values.
*
* This routine is adapted from svdecomp.c in XLISP-STAT 2.1 which is
* adapted by Luke Tierney and David Betz.
*
* the now dead xlisp-stat package seems to have been distributed
* under some sort of BSD license.
*
* Input to dsvd is as follows:
* a = mxn matrix to be decomposed, gets overwritten with u
* m = row dimension of a
* n = column dimension of a
* w = returns the vector of singular values of a
* v = returns the right orthogonal transformation matrix
*/
#define MAX(a,b) ((a)>(b)?(a):(b))
#pragma once
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
static inline double SIGN(double a, double b)
{
return copysign(a, b);
}
static inline double PYTHAG(double a, double b)
{
const double at = fabs(a), bt = fabs(b);
if (at > bt)
{
const double ct = bt / at;
return at * sqrt(1.0 + ct * ct);
}
if (bt > 0.0)
{
const double ct = at / bt;
return bt * sqrt(1.0 + ct * ct);
}
return 0.0;
}
// decompose (m >= n)
// n n n
// | | | | n | |
// m | a | = m | u | diag(w) | v^t | n
// | | | | | |
//
// where the data layout of a (in) and u (out) is strided by str for every row
static inline int dsvd(
double *a, // input matrix a[j*str + i] is j-th row and i-th column. will be overwritten by u
int m, // number of rows of a and u
int n, // number of cols of a and u
int str, // row stride of a and u
double *w, // output singular values w[n]
double *v) // output v matrix v[n*n]
{
if (m < n)
{
fprintf(stderr, "[svd] #rows must be >= #cols \n");
return 0;
}
double c, f, h, s, x, y, z;
double anorm = 0.0, g = 0.0, scale = 0.0;
double *rv1 = malloc(n * sizeof(double));
int l = 0;
/* Householder reduction to bidiagonal form */
for (int i = 0; i < n; i++)
{
/* left-hand reduction */
l = i + 1;
rv1[i] = scale * g;
g = s = scale = 0.0;
if (i < m)
{
for (int k = i; k < m; k++)
scale += fabs(a[k*str+i]);
if (scale != 0.0)
{
for (int k = i; k < m; k++)
{
a[k*str+i] = a[k*str+i]/scale;
s += a[k*str+i] * a[k*str+i];
}
f = a[i*str+i];
g = -SIGN(sqrt(s), f);
h = f * g - s;
a[i*str+i] = f - g;
if (i != n - 1)
{
for (int j = l; j < n; j++)
{
s = 0.0;
for (int k = i; k < m; k++)
s += a[k*str+i] * a[k*str+j];
f = s / h;
for (int k = i; k < m; k++)
a[k*str+j] += f * a[k*str+i];
}
}
for (int k = i; k < m; k++)
a[k*str+i] = a[k*str+i]*scale;
}
}
w[i] = scale * g;
/* right-hand reduction */
g = s = scale = 0.0;
if (i < m && i != n - 1)
{
for (int k = l; k < n; k++)
scale += fabs(a[i*str+k]);
if (scale != 0.0)
{
for (int k = l; k < n; k++)
{
a[i*str+k] = a[i*str+k]/scale;
s += a[i*str+k] * a[i*str+k];
}
f = a[i*str+l];
g = -SIGN(sqrt(s), f);
h = f * g - s;
a[i*str+l] = f - g;
for (int k = l; k < n; k++)
rv1[k] = a[i*str+k] / h;
if (i != m - 1)
{
for (int j = l; j < m; j++)
{
s = 0.0;
for (int k = l; k < n; k++)
s += a[j*str+k] * a[i*str+k];
for (int k = l; k < n; k++)
a[j*str+k] += s * rv1[k];
}
}
for (int k = l; k < n; k++)
a[i*str+k] = a[i*str+k]*scale;
}
}
anorm = MAX(anorm, (fabs(w[i]) + fabs(rv1[i])));
}
/* accumulate the right-hand transformation */
for (int i = n - 1; i >= 0; i--)
{
if (i < n - 1)
{
if (g != 0.0)
{
for (int j = l; j < n; j++)
v[j*n+i] = a[i*str+j] / a[i*str+l] / g;
/* double division to avoid underflow */
for (int j = l; j < n; j++)
{
s = 0.0;
for (int k = l; k < n; k++)
s += a[i*str+k] * v[k*n+j];
for (int k = l; k < n; k++)
v[k*n+j] += s * v[k*n+i];
}
}
for (int j = l; j < n; j++)
v[i*n+j] = v[j*n+i] = 0.0;
}
v[i*n+i] = 1.0;
g = rv1[i];
l = i;
}
/* accumulate the left-hand transformation */
for (int i = n - 1; i >= 0; i--)
{
l = i + 1;
g = w[i];
if (i < n - 1)
for (int j = l; j < n; j++)
a[i*str+j] = 0.0;
if (g != 0.0)
{
g = 1.0 / g;
if (i != n - 1)
{
for (int j = l; j < n; j++)
{
s = 0.0;
for (int k = l; k < m; k++)
s += a[k*str+i] * a[k*str+j];
f = (s / a[i*str+i]) * g;
for (int k = i; k < m; k++)
a[k*str+j] += f * a[k*str+i];
}
}
for (int j = i; j < m; j++)
a[j*str+i] = a[j*str+i]*g;
}
else
{
for (int j = i; j < m; j++)
a[j*str+i] = 0.0;
}
++a[i*str+i];
}
/* diagonalize the bidiagonal form */
for (int k = n - 1; k >= 0; k--)
{ /* loop over singular values */
const int max_its = 30;
for (int its = 0; its <= max_its; its++)
{ /* loop over allowed iterations */
_Bool flag = 1;
int nm = 0;
for (l = k; l >= 0; l--)
{ /* test for splitting */
nm = MAX(0, l - 1);
if (fabs(rv1[l]) + anorm == anorm)
{
flag = 0;
break;
}
if (l == 0 || fabs(w[nm]) + anorm == anorm)
break;
}
if (flag)
{
s = 1.0;
for (int i = l; i <= k; i++)
{
f = s * rv1[i];
if (fabs(f) + anorm != anorm)
{
g = w[i];
h = PYTHAG(f, g);
w[i] = h;
h = 1.0 / h;
c = g * h;
s = (- f * h);
for (int j = 0; j < m; j++)
{
y = a[j*str+nm];
z = a[j*str+i];
a[j*str+nm] = y * c + z * s;
a[j*str+i] = z * c - y * s;
}
}
}
}
z = w[k];
if (l == k)
{ /* convergence */
if (z < 0.0)
{ /* make singular value nonnegative */
w[k] = -z;
for (int j = 0; j < n; j++)
v[j*n+k] = -v[j*n+k];
}
break;
}
if (its >= max_its) {
fprintf(stderr, "[svd] no convergence after %d iterations\n", its);
free(rv1);
return 0;
}
/* shift from bottom 2 x 2 minor */
x = w[l];
nm = k - 1;
y = w[nm];
g = rv1[nm];
h = rv1[k];
f = ((y - z) * (y + z) + (g - h) * (g + h)) / (2.0 * h * y);
g = PYTHAG(f, 1.0);
f = ((x - z) * (x + z) + h * ((y / (f + SIGN(g, f))) - h)) / x;
/* next QR transformation */
c = s = 1.0;
for (int j = l; j <= nm; j++)
{
const int i = j + 1;
g = rv1[i];
y = w[i];
h = s * g;
g = c * g;
z = PYTHAG(f, h);
rv1[j] = z;
c = f / z;
s = h / z;
f = x * c + g * s;
g = g * c - x * s;
h = y * s;
y = y * c;
for (int jj = 0; jj < n; jj++)
{
x = v[jj*n+j];
z = v[jj*n+i];
v[jj*n+j] = x * c + z * s;
v[jj*n+i] = z * c - x * s;
}
z = PYTHAG(f, h);
w[j] = z;
if (z != 0.0)
{
z = 1.0 / z;
c = f * z;
s = h * z;
}
f = (c * g) + (s * y);
x = (c * y) - (s * g);
for (int jj = 0; jj < m; jj++)
{
y = a[jj*str+j];
z = a[jj*str+i];
a[jj*str+j] = y * c + z * s;
a[jj*str+i] = z * c - y * s;
}
}
rv1[l] = 0.0;
rv1[k] = f;
w[k] = x;
}
}
free(rv1);
return 1;
}