Using SVD from numerical recipes?

Hi all,

I am trying to use the function svdcmp from the numerical recipes book. See code below. I am actually trying to perform a least square fit on a very large number of datapoints using singular value decomposition. Now, I am used to work with standard double matrices of the form double A[M][N], where int M and int N are of the orders 100-10000.

Now the function scdcmp () does not allow me to use these type of matrices as entries, and I cannot make it to work. Is there any way that I could perhaps use some code to pass the matrix I have (A[][]) into this thing **a the function works with?

I use Bloddshed DeV C++.

Many thanks,

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void svdcmp(double **a, int m, int n, double w[], double **v)
/*******************************************************************************
Given a matrix a[1..m][1..n], this routine computes its singular value
decomposition, A = U.W.VT.  The matrix U replaces a on output.  The diagonal
matrix of singular values W is output as a vector w[1..n].  The matrix V (not
the transpose VT) is output as v[1..n][1..n].
*******************************************************************************/
{
	int flag,i,its,j,jj,k,l,nm;
	double anorm,c,f,g,h,s,scale,x,y,z,*rv1;

	rv1=dvector(1,n);
	g=scale=anorm=0.0; /* Householder reduction to bidiagonal form */
	for (i=1;i<=n;i++) {
		l=i+1;
		rv1[i]=scale*g;
		g=s=scale=0.0;
		if (i <= m) {
			for (k=i;k<=m;k++) scale += fabs(a[k][i]);
			if (scale) {
				for (k=i;k<=m;k++) {
					a[k][i] /= scale;
					s += a[k][i]*a[k][i];
				}
				f=a[i][i];
				g = -SIGN(sqrt(s),f);
				h=f*g-s;
				a[i][i]=f-g;
				for (j=l;j<=n;j++) {
					for (s=0.0,k=i;k<=m;k++) s += a[k][i]*a[k][j];
					f=s/h;
					for (k=i;k<=m;k++) a[k][j] += f*a[k][i];
				}
				for (k=i;k<=m;k++) a[k][i] *= scale;
			}
		}
		w[i]=scale *g;
		g=s=scale=0.0;
		if (i <= m && i != n) {
			for (k=l;k<=n;k++) scale += fabs(a[i][k]);
			if (scale) {
				for (k=l;k<=n;k++) {
					a[i][k] /= scale;
					s += a[i][k]*a[i][k];
				}
				f=a[i][l];
				g = -SIGN(sqrt(s),f);
				h=f*g-s;
				a[i][l]=f-g;
				for (k=l;k<=n;k++) rv1[k]=a[i][k]/h;
				for (j=l;j<=m;j++) {
					for (s=0.0,k=l;k<=n;k++) s += a[j][k]*a[i][k];
					for (k=l;k<=n;k++) a[j][k] += s*rv1[k];
				}
				for (k=l;k<=n;k++) a[i][k] *= scale;
			}
		}
		anorm = DMAX(anorm,(fabs(w[i])+fabs(rv1[i])));
	}
	for (i=n;i>=1;i--) { /* Accumulation of right-hand transformations. */
		if (i < n) {
			if (g) {
				for (j=l;j<=n;j++) /* Double division to avoid possible underflow. */
					v[j][i]=(a[i][j]/a[i][l])/g;
				for (j=l;j<=n;j++) {
					for (s=0.0,k=l;k<=n;k++) s += a[i][k]*v[k][j];
					for (k=l;k<=n;k++) v[k][j] += s*v[k][i];
				}
			}
			for (j=l;j<=n;j++) v[i][j]=v[j][i]=0.0;
		}
		v[i][i]=1.0;
		g=rv1[i];
		l=i;
	}
	for (i=IMIN(m,n);i>=1;i--) { /* Accumulation of left-hand transformations. */
		l=i+1;
		g=w[i];
		for (j=l;j<=n;j++) a[i][j]=0.0;
		if (g) {
			g=1.0/g;
			for (j=l;j<=n;j++) {
				for (s=0.0,k=l;k<=m;k++) s += a[k][i]*a[k][j];
				f=(s/a[i][i])*g;
				for (k=i;k<=m;k++) a[k][j] += f*a[k][i];
			}
			for (j=i;j<=m;j++) a[j][i] *= g;
		} else for (j=i;j<=m;j++) a[j][i]=0.0;
		++a[i][i];
	}
	for (k=n;k>=1;k--) { /* Diagonalization of the bidiagonal form. */
		for (its=1;its<=30;its++) {
			flag=1;
			for (l=k;l>=1;l--) { /* Test for splitting. */
				nm=l-1; /* Note that rv1[1] is always zero. */
				if ((double)(fabs(rv1[l])+anorm) == anorm) {
					flag=0;
					break;
				}
				if ((double)(fabs(w[nm])+anorm) == anorm) break;
			}
			if (flag) {
				c=0.0; /* Cancellation of rv1[l], if l > 1. */
				s=1.0;
				for (i=l;i<=k;i++) {
					f=s*rv1[i];
					rv1[i]=c*rv1[i];
					if ((double)(fabs(f)+anorm) == anorm) break;
					g=w[i];
					h=pythag(f,g);
					w[i]=h;
					h=1.0/h;
					c=g*h;
					s = -f*h;
					for (j=1;j<=m;j++) {
						y=a[j][nm];
						z=a[j][i];
						a[j][nm]=y*c+z*s;
						a[j][i]=z*c-y*s;
					}
				}
			}
			z=w[k];
			if (l == k) { /* Convergence. */
				if (z < 0.0) { /* Singular value is made nonnegative. */
					w[k] = -z;
					for (j=1;j<=n;j++) v[j][k] = -v[j][k];
				}
				break;
			}
			if (its == 30) printf("no convergence in 30 svdcmp iterations");
			x=w[l]; /* Shift from bottom 2-by-2 minor. */
			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;
			c=s=1.0; /* Next QR transformation: */
			for (j=l;j<=nm;j++) {
				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 *= c;
				for (jj=1;jj<=n;jj++) {
					x=v[jj][j];
					z=v[jj][i];
					v[jj][j]=x*c+z*s;
					v[jj][i]=z*c-x*s;
				}
				z=pythag(f,h);
				w[j]=z; /* Rotation can be arbitrary if z = 0. */
				if (z) {
					z=1.0/z;
					c=f*z;
					s=h*z;
				}
				f=c*g+s*y;
				x=c*y-s*g;
				for (jj=1;jj<=m;jj++) {
					y=a[jj][j];
					z=a[jj][i];
					a[jj][j]=y*c+z*s;
					a[jj][i]=z*c-y*s;
				}
			}
			rv1[l]=0.0;
			rv1[k]=f;
			w[k]=x;
		}
	}
	free_dvector(rv1,1,n);
}
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