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/*
* nnls.c (c) 2003-2009 Turku PET Centre
* This file contains the routine NNLS (nonnegative least squares)
* and the subroutines required by it, except h12, which is in
* file 'lss_h12.c'.
*
* This routine is based on the text and fortran code in
* C.L. Lawson and R.J. Hanson, Solving Least Squares Problems,
* Prentice-Hall, Englewood Cliffs, New Jersey, 1974.
* Version:
* 2002-08-19 Vesa Oikonen
* 2003-05-08 Kaisa Sederholm & VO
* Included function nnlsWght().
* 2003-05-12 KS
* Variable a_dim1 excluded
*
* Usage of the coefficient matrix altered so that it is
* given in a[][] instead of a[].
* 2003-11-06 VO
* If n<2, then itmax is set to n*n instead of previous n*3.
* 2004-09-17 VO
* Doxygen style comments.
* 2006-24-04 Pauli Sundberg
* Added some debuging output, and made some comments more precise.
* 2007-05-17 VO
* 2009-04-16 VO
* Corrected a bug in nnls() which may have caused an infinite loop.
* 009-04-27 VO
* Added function nnlsWghtSquared() for faster pixel-by-pixel calculations.
* Checking for exceeding iteration count is corrected in nnls().
*/
#include <stdio.h>
#include <stdint.h>
#include <assert.h>
#include <stdlib.h>
#include <math.h>
#define MAX(a,b) ((a) >= (b) ? (a) : (b))
#define ABS(x) ((x) >= 0 ? (x) : -(x))
int64_t h12( int64_t mode, int64_t lpivot, int64_t l1, int64_t m, double *u, int64_t u_dim1, double *up, double *cm, int64_t ice, int64_t icv, int64_t ncv) {
double d1, b, clinv, cl, sm;
int64_t k, j;
/* Check parameters */
if (mode!=1 && mode!=2)
return(1);
if (m<1 || u==NULL || u_dim1<1 || cm==NULL)
assert(0);
// return(1);
if (lpivot<0 || lpivot>=l1 || l1>m)
// assert(0);
return(1);
/* Function Body */
cl = ABS( u[lpivot*u_dim1] );
// cl= (d1 = u[lpivot*u_dim1], fabs(d1));
if (mode==2)
{ /* Apply transformation I+U*(U**T)/B to cm[] */
if(cl<=0.)
// assert(0);
return(0);
}
else
{ /* Construct the transformation */
/* This is the way provided in the original pseudocode
sm = 0;
for (j = l1; j < m; j++)
{
d1 = u[j * u_dim1];
sm += d1*d1;
}
d1 = u[lpivot * u_dim1];
sm += d1*d1;
sm = sqrt(sm);
if (u[lpivot*u_dim1] > 0)
sm=-sm;
up[0] = u[lpivot*u_dim1] - sm;
u[lpivot*u_dim1]=sm;
printf("Got sum: %f\n",sm);
*/
/* and this trying to compensate overflow */
for (j=l1; j<m; j++)
{ // Computing MAX
cl = MAX( ABS( u[j*u_dim1] ), cl );
}
// zero vector?
if (cl<=0.)
return(0);
clinv=1.0/cl;
// Computing 2nd power
d1=u[lpivot*u_dim1]*clinv;
sm=d1*d1;
for (j=l1; j<m; j++)
{
d1=u[j*u_dim1]*clinv;
sm+=d1*d1;
}
cl *= sqrt(sm);
if (u[lpivot*u_dim1] > 0.)
cl=-cl;
up[0] = u[lpivot*u_dim1] - cl;
u[lpivot*u_dim1]=cl;
}
// no vectors where to apply? only change pivot vector!
b=up[0] * u[lpivot*u_dim1];
/* b must be nonpositive here; if b>=0., then return */
if (b == 0)
return(0);
// ok, for all vectors we want to apply
for (j =0; j < ncv; j++) {
sm = cm[ lpivot * ice + j * icv ] * (up[0]);
for (k=l1; k<m; k++)
sm += cm[ k * ice + j*icv ] * u[ k*u_dim1 ];
if (sm != 0.0) {
sm *= (1/b);
// cm[lpivot, j] = ..
cm[ lpivot * ice + j*icv] += sm * (up[0]);
for (k= l1; k<m; k++)
{
cm[ k*ice + j*icv] += u[k * u_dim1]*sm;
}
}
}
return(0);
}
void g1(double a, double b, double *cterm, double *sterm, double *sig)
{
double d1, xr, yr;
if( fabs(a) > fabs(b) ) {
xr = b / a;
d1 = xr;
yr = sqrt(d1*d1 + 1.);
d1 = 1./yr;
*cterm=(a>=0.0 ? fabs(d1) : -fabs(d1));
*sterm=(*cterm)*xr;
*sig=fabs(a)*yr;
} else if( b != 0.) {
xr = a / b;
d1 = xr;
yr = sqrt(d1 * d1 + 1.);
d1 = 1. / yr;
*sterm=(b>=0.0 ? fabs(d1) : -fabs(d1));
*cterm=(*sterm)*xr; *sig=fabs(b)*yr;
} else {
*sig=0.; *cterm=0.; *sterm=1.;
}
}
int64_t nnls_algorithm(double *a, int64_t m,int64_t n, double *b, double *x, double *rnorm) {
int64_t pfeas;
int ret=0;
int64_t iz;
int64_t jz;
int64_t k, j=0, l, itmax, izmax=0, ii, jj=0, ip;
double d1, d2, sm, up, ss;
double temp, wmax, t, alpha, asave, dummy, unorm, ztest, cc;
/* Check the parameters and data */
if(m <= 0 || n <= 0 || a == NULL || b == NULL || x == NULL)
return(2);
/* Allocate memory for working space, if required */
double *w = calloc(n, sizeof(double));
double *zz = calloc(m, sizeof(double));
int64_t *index = calloc(n, sizeof(int64_t));
if(w == NULL || zz == NULL || index == NULL)
return(2);
/* Initialize the arrays INDEX[] and X[] */
for(k=0; k<n; k++) {
x[k]=0.;
index[k]=k;
}
int64_t iz2 = n - 1;
int64_t iz1 = 0;
int64_t iter=0;
int64_t nsetp=0;
int64_t npp1=0;
/* Main loop; quit if all coeffs are already in the solution or */
/* if M cols of A have been triangularized */
if(n < 3)
itmax=n*3;
else
itmax=n*n;
while(iz1 <= iz2 && nsetp < m) {
/* Compute components of the dual (negative gradient) vector W[] */
for(iz=iz1; iz<=iz2; iz++) {
j=index[iz];
sm=0.;
for(l=npp1; l<m; l++)
sm+=a[j*m + l]*b[l];
w[j]=sm;
}
while(1) {
/* Find largest positive W[j] */
for(wmax=0., iz=iz1; iz<=iz2; iz++) {
j=index[iz]; if(w[j]>wmax) {wmax=w[j]; izmax=iz;}}
/* Terminate if wmax<=0.; */
/* it indicates satisfaction of the Kuhn-Tucker conditions */
if(wmax<=0.0)
break;
iz=izmax;
j=index[iz];
/* The sign of W[j] is ok for j to be moved to set P. */
/* Begin the transformation and check new diagonal element to avoid */
/* near linear dependence. */
asave=a[j*m + npp1];
h12(1, npp1, npp1+1, m, &a[j*m +0], 1, &up, &dummy, 1, 1, 0);
unorm=0.;
if(nsetp!=0){
for(l=0; l<nsetp; l++) {
d1=a[j*m + l];
unorm+=d1*d1;
}
}
unorm=sqrt(unorm);
d2=unorm+(d1=a[j*m + npp1], fabs(d1)) * 0.01;
if((d2-unorm)>0.) {
/* Col j is sufficiently independent. Copy B into ZZ, update ZZ */
/* and solve for ztest ( = proposed new value for X[j] ) */
for(l=0; l<m; l++) zz[l]=b[l];
h12(2, npp1, npp1+1, m, &a[j*m + 0], 1, &up, zz, 1, 1, 1);
ztest=zz[npp1]/a[j*m +npp1];
/* See if ztest is positive */
if(ztest>0.) break;
}
/* Reject j as a candidate to be moved from set Z to set P. Restore */
/* A[npp1,j], set W[j]=0., and loop back to test dual coeffs again */
a[j*m+ npp1]=asave; w[j]=0.;
} /* while(1) */
if(wmax<=0.0)
break;
/* Index j=INDEX[iz] has been selected to be moved from set Z to set P. */
/* Update B and indices, apply householder transformations to cols in */
/* new set Z, zero subdiagonal elts in col j, set W[j]=0. */
for(l=0; l<m; ++l)
b[l]=zz[l];
index[iz]=index[iz1];
index[iz1]=j;
iz1++;
npp1++;
nsetp=npp1;
if(iz1<=iz2) {
for(jz=iz1; jz<=iz2; jz++) {
jj=index[jz];
h12(2, nsetp-1, npp1, m, &a[j*m +0], 1, &up, &a[jj*m +0], 1, m, 1);
}
}
if(nsetp!=m) {
for(l=npp1; l<m; l++)
a[j*m +l]=0.;
}
w[j]=0.;
/* Solve the triangular system; store the solution temporarily in Z[] */
for(l=0; l<nsetp; l++) {
ip=nsetp-(l+1);
if(l!=0) for(ii=0; ii<=ip; ii++) zz[ii]-=a[jj*m + ii]*zz[ip+1];
jj=index[ip]; zz[ip]/=a[jj*m +ip];
}
/* Secondary loop begins here */
while(++iter < itmax) {
/* See if all new constrained coeffs are feasible; if not, compute alpha */
for(alpha = 2.0, ip = 0; ip < nsetp; ip++) {
l=index[ip];
if(zz[ip]<=0.) {
t = -x[l]/(zz[ip]-x[l]);
if(alpha > t) {
alpha = t;
jj = ip - 1;
}
}
}
/* If all new constrained coeffs are feasible then still alpha==2. */
/* If so, then exit from the secondary loop to main loop */
if(alpha==2.0)
break;
/* Use alpha (0.<alpha<1.) to interpolate between old X and new ZZ */
for(ip=0; ip<nsetp; ip++) {
l = index[ip];
x[l] += alpha*(zz[ip]-x[l]);
}
/* Modify A and B and the INDEX arrays to move coefficient i */
/* from set P to set Z. */
k=index[jj+1]; pfeas=1;
do {
x[k]=0.;
if(jj!=(nsetp-1)) {
jj++;
for(j=jj+1; j<nsetp; j++) {
ii=index[j]; index[j-1]=ii;
g1(a[ii*m + (j-1)], a[ii*m + j], &cc, &ss, &a[ii*m + j-1]);
for(a[ii*m + j]=0., l=0; l<n; l++) if(l!=ii) {
/* Apply procedure G2 (CC,SS,A(J-1,L),A(J,L)) */
temp=a[l*m + j-1];
a[l*m + j-1]=cc*temp+ss*a[l*m + j];
a[l*m + j]=-ss*temp+cc*a[l*m + j];
}
/* Apply procedure G2 (CC,SS,B(J-1),B(J)) */
temp=b[j-1]; b[j-1]=cc*temp+ss*b[j]; b[j]=-ss*temp+cc*b[j];
}
}
npp1=nsetp-1; nsetp--; iz1--; index[iz1]=k;
/* See if the remaining coeffs in set P are feasible; they should */
/* be because of the way alpha was determined. If any are */
/* infeasible it is due to round-off error. Any that are */
/* nonpositive will be set to zero and moved from set P to set Z */
for(jj=0, pfeas=1; jj<nsetp; jj++) {
k=index[jj]; if(x[k]<=0.) {pfeas=0; break;}
}
} while(pfeas==0);
/* Copy B[] into zz[], then solve again and loop back */
for(k=0; k<m; k++)
zz[k]=b[k];
for(l=0; l<nsetp; l++) {
ip=nsetp-(l+1);
if(l!=0) for(ii=0; ii<=ip; ii++) zz[ii]-=a[jj*m + ii]*zz[ip+1];
jj=index[ip]; zz[ip]/=a[jj*m + ip];
}
} /* end of secondary loop */
if(iter>=itmax) {
ret = 1;
break;
}
for(ip=0; ip<nsetp; ip++) {
k=index[ip];
x[k]=zz[ip];
}
} /* end of main loop */
/* Compute the norm of the final residual vector */
sm=0.;
if (rnorm != NULL) {
if (npp1<m)
for (k=npp1; k<m; k++)
sm+=(b[k] * b[k]);
else
for (j=0; j<n; j++)
w[j]=0.;
*rnorm=sqrt(sm);
}
/* Free working space, if it was allocated here */
free(w);
free(zz);
free(index);
return(ret);
}
/* nnls_ */
double *nnls(double *a_matrix, double *b_matrix, int64_t height, int64_t width) {
double *solution = calloc(height, sizeof(double));
if(solution == NULL) {
fprintf(stderr, "could not allocate enough memory for nnls\n");
exit(EXIT_FAILURE);
}
int ret = nnls_algorithm(a_matrix, width, height, b_matrix, solution, NULL);
if(ret == 1) {
printf("NNLS has reached the maximum iterations\n");
} else if(ret == 2) {
fprintf(stderr, "NNLS could not allocate enough memory\n");
exit(EXIT_FAILURE);
}
return solution;
}
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