From 0773aaf89678b967588a902df1f5e6f9ccea393d Mon Sep 17 00:00:00 2001 From: Calvin Date: Tue, 14 May 2013 21:51:40 -0400 Subject: release1.0 --- src/c/nnls.c | 416 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 416 insertions(+) create mode 100644 src/c/nnls.c (limited to 'src/c/nnls.c') diff --git a/src/c/nnls.c b/src/c/nnls.c new file mode 100644 index 0000000..ddd9f2f --- /dev/null +++ b/src/c/nnls.c @@ -0,0 +1,416 @@ +/* + * nnls.c (c) 2002-2009 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 +#include +#include +#include +#define MAX(a,b) ((a) >= (b) ? (a) : (b)) +#define ABS(x) ((x) >= 0 ? (x) : -(x)) + +int h12( int mode, int lpivot, int l1, int m, double *u, int u_dim1, double *up, double *cm, int ice, int icv, int ncv) { + double d1, b, clinv, cl, sm; + int 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 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 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.; + } +} + + +int nnls_algorithm(double *a, int m,int n, double *b, double *x, double *rnorm) { + int pfeas; + int ret=0; + int iz; + int jz; + int 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 = (double*)calloc(n, sizeof(double)); + double *zz = (double*)calloc(m, sizeof(double)); + int *index = (int*)calloc(n, sizeof(int)); + if(w == NULL || zz == NULL || index == NULL) + return(2); + + /* Initialize the arrays INDEX[] and X[] */ + for(k=0; kwmax) {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; l0.) { + /* Col j is sufficiently independent. Copy B into ZZ, update ZZ */ + /* and solve for ztest ( = proposed new value for X[j] ) */ + for(l=0; l0.) 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 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.=itmax) { + ret = 1; + break; + } + + for(ip=0; ip