void matrixDMConstraintWeights(pulsar *psr){
int i,j,k;
int nobs=0;
int nfit=psr->dmoffsDMnum+psr->dmoffsCMnum;
int nDM=psr->dmoffsDMnum;
double x;
if (psr->param[param_dmmodel].fitFlag[0]==1)
{
logdbg("Getting DM constraints for %s",psr->name);
// find out how many obs we have.
for(i=0; i < psr->nobs; i++){
if (psr->obsn[i].deleted==0)
{
char okay=1;
/* Check for START and FINISH flags */
if (psr->param[param_start].paramSet[0]==1 && psr->param[param_start].fitFlag[0]==1 &&
(psr->param[param_start].val[0] > psr->obsn[i].sat))
okay=0;
if (psr->param[param_finish].paramSet[0]==1 && psr->param[param_finish].fitFlag[0]==1 &&
psr->param[param_finish].val[0] < psr->obsn[i].sat)
okay=0;
if (okay==1)
{
nobs++;
}
}
}
// originally was sizeof(double*)*nobs.
double ** designMatrix=(double**)malloc_uinv(nobs);
double *e=(double*)malloc(sizeof(double)*nobs);
nobs=0;
// printf("c0: %d %s\n",psr->nobs,psr->name);
for(i=0; i < psr->nobs; i++){
// Check for "ok" and start/finish coppied from dofit.
// Needs to be the same so that the weighting is the same as the fit,
// but in practice probably doesn't matter.
// printf("c1 checking: %d %d %s\n",psr->obsn[i].deleted,psr->nobs,psr->name);
if (psr->obsn[i].deleted==0)
{
char okay=1;
/* Check for START and FINISH flags */
if (psr->param[param_start].paramSet[0]==1 && psr->param[param_start].fitFlag[0]==1 &&
(psr->param[param_start].val[0] > psr->obsn[i].sat))
okay=0;
if (psr->param[param_finish].paramSet[0]==1 && psr->param[param_finish].fitFlag[0]==1 &&
psr->param[param_finish].val[0] < psr->obsn[i].sat)
okay=0;
// printf("c2 checking: %d\n",okay);
if (okay==1)
{
x = (double)(psr->obsn[i].bbat-psr->param[param_pepoch].val[0]);
double sig=psr->obsn[i].toaErr*1e-6;
double dmf = 1.0/(DM_CONST*powl(psr->obsn[i].freqSSB/1.0e6,2));
for (k=0; k < nfit;k++){
if(k<nDM)
designMatrix[nobs][k]=dmf*getParamDeriv(psr,i,x,param_dmmodel,k)/sig;
else
designMatrix[nobs][k]=getParamDeriv(psr,i,x,param_dmmodel,k)/sig;
}
nobs++;
}
}
}
printf("Calling TKleastSquares %d %d\n",nobs,nfit); fflush(stdout);
TKleastSquares(NULL,NULL,designMatrix,designMatrix,nobs,nfit,1e-20,0,NULL,e,NULL);
printf("Returning from calling TKleastSquares\n"); fflush(stdout);
double sum_wDM=0;
double sum_wCM=0;
for (i=0;i<nfit;i++)
{
double sum=0.0;
if(i < nDM){
psr->dmoffsDM_weight[i]=1.0/e[i]/e[i];
printf("constraints.C here: %d %g\n",i,e[i]);
sum_wDM+=psr->dmoffsDM_weight[i];
} else {
psr->dmoffsCM_weight[i-nDM]=1.0/e[i]/e[i];
sum_wCM+=psr->dmoffsCM_weight[i-nDM];
}
}
//normalise the weights
for (i=0;i<psr->dmoffsDMnum;i++)
psr->dmoffsDM_weight[i]/=sum_wDM;
for (i=0;i<psr->dmoffsCMnum;i++)
psr->dmoffsCM_weight[i]/=sum_wCM;
// free everything .
free_uinv(designMatrix);
free(e);
}
}
/**
* Do the least squares using QR decomposition
*/
double accel_lsq_qr(double** A, double* data, double* oparam, int ndata, int nparam, double** Ocvm){
int nhrs=1;
int nwork = -1;
int info=0;
int i,j;
double iwork;
// workspace query - works out optimal size for work array
F77_dgels("T", &nparam, &ndata, &nhrs, A[0], &nparam, data, &ndata, &iwork, &nwork, &info);
nwork=(int)iwork;
logdbg("nwork = %d (%lf)",nwork,iwork);
double* work = static_cast<double*>(malloc(sizeof(double)*nwork));
logdbg("accel_lsq_qr ndata=%d nparam=%d",ndata,nparam);
// as usual we prentend that the matrix is transposed to deal with C->fortran conversion
// degls does a least-squares using QR decomposition. Fast and robust.
F77_dgels("T", &nparam, &ndata, &nhrs, A[0], &nparam, data, &ndata, work, &nwork, &info);
free(work);
// if info is not zero then the fit failed.
if(info!=0){
logerr("Error in lapack DEGLS. INFO=%d See full logs for explanation.",info);
logmsg("");
logmsg("From: http://www.netlib.org/lapack/explore-html/d8/dde/dgels_8f.html");
logmsg("INFO is INTEGER");
logmsg(" = 0: successful exit");
logmsg(" < 0: if INFO = -i, the i-th argument had an illegal value");
logmsg(" > 0: if INFO = i, the i-th diagonal element of the");
logmsg(" triangular factor of A is zero, so that A does not have");
logmsg(" full rank; the least squares solution could not be");
logmsg(" computed.");
logmsg("");
if(info > 0){
logerr("It appears that you are fitting for a 'bad' parameter - E.g A jump on a non-existant flag.");
logmsg(" TEMPO2 will NOT attempt to deal with this!");
logmsg("Cannot continue. Abort fit.");
return -1;
} else {
logmsg("Cannot continue. Abort fit.");
return -1;
}
}
assert(info==0);
if(oparam!=NULL){
// copy out the output parameters, which are written into the "data" array.
memcpy(oparam,data,sizeof(double)*nparam);
}
double chisq=0;
for( i = nparam; i < ndata; i++ ) chisq += data[i] * data[i];
if (Ocvm != NULL){
int n=nparam;
// packed triangular matrix.
double* _t=(double*)malloc(sizeof(double)*(n*(n+1))/2);
// This code taken from the LAPACK documentation
// to pack a triangular matrix.
// we want the upper triangular matrix part of A.
//
// pack upper triangle like (r,c)
// (1,1) (1,2) (2,2)
// i+(2n-j)(j-1)/2
int jc=0;
for (j=0;j<n;j++){ // cols
for (i=0; i <=j; i++) { // rows
_t[jc] = A[i][j]; // A came from fortran, so is in [col][row] ordering
// BUT - we have transposed A, so we have to un-transpose it
++jc;
}
}
logdbg("Inverting...");
F77_dtptri("U","N",&n,_t,&i);
if(i!=0){
logerr("Error in lapack DTPTRI. INFO=%d",i);
logmsg("From: http://www.netlib.org/lapack/explore-html/d8/d05/dtptri_8f.html");
logmsg("INFO is INTEGER");
logmsg(" = 0: successful exit");
logmsg(" < 0: if INFO = -i, the i-th argument had an illegal value");
logmsg(" > 0: if INFO = i, A(i,i) is exactly zero. The triangular");
logmsg(" matrix is singular and its inverse can not be computed.");
logmsg("Cannot continue - abort fit");
return -1;
}
double **Rinv = malloc_uinv(n);
for (j=0;j<n;j++){ // cols
for (i=0;i<n;i++){ //rows
Ocvm[i][j]=0;
}
}
// Unpack the triangular matrix using reverse of above
// We will put it in fortran, so continue to use [col][row] order
jc=0;
for (j=0;j<n;j++){ // cols
for (i=0; i <=j; i++) { // rows
Rinv[j][i] = _t[jc];
Ocvm[j][i] = _t[jc];
++jc;
}
}
free(_t);
double a=chisq/(double)(ndata-nparam);
// (X^T X)^-1 = Rinv.Rinv^T gives parameter covariance matrix
// Note that Ocvm is input and output
// and that covar matrix will be transposed, but it is
// symetric so it doesn't matter!
F77_dtrmm( "R", "U", "T", "N", &n, &n, &a, *Rinv, &n, *Ocvm, &n);
// DTRMM ( SIDE, UPLO, TRANSA, DIAG, M, N, ALPHA, A , LDA, B, LDB )
if(debugFlag){
for(i=0;i<n;i++){
for(j=0;j<n;j++){
logdbg("COVAR %d %d %lg",i,j,Ocvm[i][j]);
}
}
}
free_uinv(Rinv);
}
return chisq;
}
