int rnorm(taucs_ccs_matrix* A, double* x, double* y, double* aux)
{
int i;
int one = 1;
double relerr;
for(i=0; i<A->n; i++) aux[i] = y[i]-x[i];
relerr = my_dnrm2(&(A->n),aux,&one)/my_dnrm2(&(A->n),x,&one);
taucs_printf("2-norm relative forward error %.2e \n",relerr);
if (relerr > 1e-8) {
taucs_printf("test failed, error seems too high (but\n");
taucs_printf("maybe the matrix is too ill-conditioned)\n");
return 1;
}
return 0;
}
/* N>1 */
double
fit_N_point_em_f(hpixelf *parr, int npix, int Nf, double *freqs, double *bmaj, double *bmin, double *bpa, double ref_freq, int maxiter, int max_em_iter, double *ll, double *mm, double *sI, double *sP, int N, int Nh, hpoint *hull){
int ci,cj,ck;
double *p,*p1,*p2, // params m x 1
*x; // observed data n x 1, the image pixel fluxes
double *xdummy, *xsub; //extra arrays
int m,n;
double *b; /* affine combination */
double opts[CLM_OPTS_SZ], info[CLM_INFO_SZ];
double l_min,l_max,m_min,m_max,sumI;
double fraction;
double penalty; /* penalty for solutions with components out of pixel range */
fit_double_point_dataf lmdata;
/* for initial average pixel fit */
hpixel *parrav;
double mean_bmaj,mean_bmin,mean_bpa,mean_err;
/***** first do a fit for average pixesl, using average PSF ******/
if ((parrav=(hpixel*)calloc((size_t)(npix),sizeof(hpixel)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
for (ci=0; ci<npix; ++ci) {
parrav[ci].x=parr[ci].x;
parrav[ci].y=parr[ci].y;
parrav[ci].l=parr[ci].l;
parrav[ci].m=parr[ci].m;
parrav[ci].ra=parr[ci].ra;
parrav[ci].dec=parr[ci].dec;
parrav[ci].sI=0.0;
for (cj=0; cj<Nf; ++cj) {
parrav[ci].sI+=parr[ci].sI[cj];
}
parrav[ci].sI/=(double)Nf;
}
mean_bmaj=mean_bmin=mean_bpa=0.0;
for (cj=0; cj<Nf; ++cj) {
mean_bmaj+=bmaj[cj];
mean_bmin+=bmin[cj];
mean_bpa+=bpa[cj];
}
mean_bmaj/=(double)Nf;
mean_bmin/=(double)Nf;
mean_bpa/=(double)Nf;
/* we get mean_err=2*3*N+npix*log(error) */
mean_err=fit_N_point_em(parrav, npix, mean_bmaj, mean_bmin, mean_bpa, maxiter, max_em_iter, ll, mm, sI, N, Nh, hull);
free(parrav);
opts[0]=CLM_INIT_MU; opts[1]=1E-15; opts[2]=1E-15; opts[3]=1E-15;
opts[4]=-CLM_DIFF_DELTA;
m=4; /* 1x1 flux, 3x1 spec index for each component */
n=Nf*npix; /* no of pixels */
if ((p=(double*)calloc((size_t)(m),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
if ((p1=(double*)calloc((size_t)(m),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
if ((p2=(double*)calloc((size_t)(m),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
if ((x=(double*)calloc((size_t)(n),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
if ((xsub=(double*)calloc((size_t)(n),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
if ((xdummy=(double*)calloc((size_t)(n),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
if ((b=(double*)calloc((size_t)(N),sizeof(double)))==0) {
fprintf(stderr,"%s: %d: no free memory\n",__FILE__,__LINE__);
exit(1);
}
l_min=m_min=INFINITY_L;
l_max=m_max=-INFINITY_L;
sumI=0.0;
/* only use valid pixels for initial conditions */
for (ci=0; ci<npix; ci++) {
if (parr[ci].ra!=-1 && parr[ci].m!=-1) {
if (l_min>parr[ci].l) {
l_min=parr[ci].l;
}
if (l_max<parr[ci].l) {
l_max=parr[ci].l;
}
if (m_min>parr[ci].m) {
m_min=parr[ci].m;
}
if (m_max<parr[ci].m) {
m_max=parr[ci].m;
}
}
}
ck=0;
for (cj=0; cj<Nf; ++cj) {
for (ci=0; ci<npix; ci++) {
x[ck++]=parr[ci].sI[cj];
sumI+=parr[ci].sI[cj];
}
}
sumI/=(double)n;
fraction=1.0;///(double)N;
/**********************************/
for (ci=0; ci<N; ci++) {
sP[ci]=0.0;
sP[ci+N]=0.0;
sP[ci+2*N]=0.0;
b[ci]=fraction;
}
lmdata.Nf=Nf;
lmdata.parr=parr;
lmdata.freqs=freqs;
lmdata.bmaj=bmaj;
lmdata.bmin=bmin;
lmdata.bpa=bpa;
lmdata.ref_freq=ref_freq;
double aic1,aic2,aic3;
for (ci=0; ci<max_em_iter; ci++) {
for (cj=0; cj<N; cj++) {
/* calculate contribution from hidden data, subtract from x */
memcpy(xdummy,x,(size_t)(n)*sizeof(double));
for (ck=0; ck<N; ck++) {
if (ck!=cj) {
lmdata.ll=&ll[ck]; /* pointer to positions */
lmdata.mm=&mm[ck];
p[0]=sI[ck];
p[1]=sP[ck];
p[2]=sP[ck+N];
p[3]=sP[ck+2*N];
mylm_fit_single_pf(p, xsub, m, n, (void*)&lmdata);
/* xdummy=xdummy-b*xsub */
my_daxpy(n, xsub, -b[ck], xdummy);
}
}
lmdata.ll=&ll[cj]; /* pointer to positions */
lmdata.mm=&mm[cj];
p[0]=p1[0]=p2[0]=sI[cj];
p[1]=p1[1]=p2[1]=sP[cj];
p[2]=p2[2]=sP[cj+N]; p1[2]=0.0;
p[3]=sP[cj+2*N]; p1[3]=p2[3]=0.0;
//ret=dlevmar_dif(mylm_fit_single_pf, p, xdummy, m, n, maxiter, opts, info, NULL, NULL, (void*)&lmdata); // no Jacobian
clevmar_der_single_nocuda(mylm_fit_single_pf, NULL, p, xdummy, m, n, maxiter, opts, info, 2, (void*)&lmdata); // no Jacobian
/* penalize only 1/10 of parameters */
aic3=0.3+log(info[1]);
clevmar_der_single_nocuda(mylm_fit_single_pf_2d, NULL, p2, xdummy, m-1, n, maxiter, opts, info, 2, (void*)&lmdata); // no Jacobian
aic2=0.2+log(info[1]);
clevmar_der_single_nocuda(mylm_fit_single_pf_1d, NULL, p1, xdummy, m-2, n, maxiter, opts, info, 2, (void*)&lmdata); // no Jacobian
aic1=0.1+log(info[1]);
/* choose one with minimum error */
if (aic3<aic2) {
if (aic3<aic1) {
/* 3d */
sI[cj]=p[0];
sP[cj]=p[1];
sP[cj+N]=p[2];
sP[cj+2*N]=p[3];
} else {
/* 1d */
sI[cj]=p1[0];
sP[cj]=p1[1];
sP[cj+N]=p1[2];
sP[cj+2*N]=p1[3];
}
} else {
if (aic2<aic1) {
/* 2d */
sI[cj]=p2[0];
sP[cj]=p2[1];
sP[cj+N]=p2[2];
sP[cj+2*N]=p2[3];
} else {
/* 1d */
sI[cj]=p1[0];
sP[cj]=p1[1];
sP[cj+N]=p1[2];
sP[cj+2*N]=p1[3];
}
}
}
}
/**********************************/
#ifdef DEBUG
print_levmar_info(info[0],info[1],(int)info[5], (int)info[6], (int)info[7], (int)info[8], (int)info[9]);
printf("Levenberg-Marquardt returned %d in %g iter, reason %g\nSolution: ", ret, info[5], info[6]);
#endif
/* check for solutions such that l_min <= ll <= l_max and m_min <= mm <= m_max */
penalty=0.0;
for (ci=0; ci<N; ci++) {
/* position out of range */
if (ll[ci]<l_min || ll[ci]>l_max || mm[ci]<m_min || mm[ci]>m_max) {
penalty+=INFINITY_L;
}
/* spec index too high to be true */
if (fabs(sP[ci])>20.0) {
penalty+=INFINITY_L;
}
}
/* calculate error */
memcpy(xdummy,x,(size_t)(n)*sizeof(double));
for (cj=0; cj<N; cj++) {
for (ck=0; ck<N; ck++) {
lmdata.ll=&ll[ck]; /* pointer to positions */
lmdata.mm=&mm[ck];
p[0]=sI[ck];
p[1]=sP[ck];
p[2]=sP[ck+N];
p[3]=sP[ck+2*N];
mylm_fit_single_pf(p, xsub, m, n, (void*)&lmdata);
/* xdummy=xdummy-b*xsub */
my_daxpy(n, xsub, -1.0, xdummy);
}
}
/*sumI=0.0;
for (ci=0; ci<n; ++ci ){
sumI+=xdummy[ci]*xdummy[ci];
} */
sumI=my_dnrm2(n,xdummy);
sumI=sumI*sumI;
free(p);
free(p1);
free(p2);
free(x);
free(xdummy);
free(xsub);
free(b);
/* AIC, 4*N parms */
//return 2*4*N+npix*Nf*log(sumI)+penalty;
return 2*4*N+Nf*(mean_err-2*3*N)+log(sumI)*npix*Nf+penalty;
}
