int main() {
double lb[2] = { -HUGE_VAL, 0 }; /* lower bounds */
nlopt_opt opt;
opt = nlopt_create(NLOPT_LD_MMA, 2); /* algorithm and dimensionality */
nlopt_set_lower_bounds(opt, lb);
nlopt_set_min_objective(opt, myfunc, NULL);
my_constraint_data data[2] = { { 2, 0 }, { -1, 1 } };
nlopt_add_inequality_constraint(opt, myconstraint, &data[0], 1e-8);
nlopt_add_inequality_constraint(opt, myconstraint, &data[1], 1e-8);
nlopt_set_xtol_rel(opt, 1e-4);
double x[2] = { 1.234, 5.678 }; /* some initial guess */
double minf; /* the minimum objective value, upon return */
if (nlopt_optimize(opt, x, &minf) < 0) {
printf("nlopt failed!\n");
}
else {
printf("found minimum at f(%g,%g) = %0.10g\n", x[0], x[1], minf);
}
nlopt_destroy(opt);
}
nlopt_result nlopt_optimize_limited(nlopt_opt opt, double *x, double *minf,
int maxeval, double maxtime)
{
int save_maxeval;
double save_maxtime;
nlopt_result ret;
if (!opt) return NLOPT_INVALID_ARGS;
save_maxeval = nlopt_get_maxeval(opt);
save_maxtime = nlopt_get_maxtime(opt);
/* override opt limits if maxeval and/or maxtime are more stringent */
if (save_maxeval <= 0 || (maxeval > 0 && maxeval < save_maxeval))
nlopt_set_maxeval(opt, maxeval);
if (save_maxtime <= 0 || (maxtime > 0 && maxtime < save_maxtime))
nlopt_set_maxtime(opt, maxtime);
ret = nlopt_optimize(opt, x, minf);
nlopt_set_maxeval(opt, save_maxeval);
nlopt_set_maxtime(opt, save_maxtime);
return ret;
}
static void phyanimal_fit_lambda(PhyAnimal model) {
nlopt_opt opt;
double lb, ub, lambda, loglh;
opt = nlopt_create(NLOPT_LN_NELDERMEAD, 1); /* one dimension */
lb = 0.0;
ub = 1.0;
nlopt_set_lower_bounds(opt,&lb);
nlopt_set_upper_bounds(opt,&ub);
/* No inequality constraints */
nlopt_set_max_objective(opt, loglh_worker, model);
nlopt_set_xtol_rel(opt, 1e-4);
lambda = 0.1;
if (nlopt_optimize(opt, &lambda, &loglh)<0) {
printf("NLOPT failed\n");
} else {
printf("Maximum lh %f at lambda %f\n",loglh,lambda);
printf("Sigma = %f\n",model->sigma);
printf("Sigma_b = %f\nSigma_e = %f\n",model->sigma*lambda,model->sigma*(1-lambda));
}
model->loglh = loglh;
model->lambda = lambda;
nlopt_destroy(opt);
return;
}
Eigen::VectorXd TargetTrackingController::getControl(const EKF *ekf, const MultiAgentMotionModel *motionModel, const std::vector<const SensorModel*> &sensorModel, double *f) const {
Evaluator evaluator(ekf, motionModel, sensorModel, params);
Eigen::VectorXd p = Eigen::VectorXd::Zero(motionModel->getControlDim());
Eigen::VectorXd lowerBound = Eigen::VectorXd::Constant(motionModel->getControlDim(), params("multi_rotor_control/controlMin").toDouble());
Eigen::VectorXd upperBound = Eigen::VectorXd::Constant(motionModel->getControlDim(), params("multi_rotor_control/controlMax").toDouble());
nlopt_opt opt = nlopt_create(NLOPT_LN_COBYLA, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LN_BOBYQA, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LN_NEWUOA_BOUND, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LN_PRAXIS, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LN_NELDERMEAD, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LN_SBPLX, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_GN_ORIG_DIRECT, p.size()); // failed
// nlopt_opt opt = nlopt_create(NLOPT_GN_ORIG_DIRECT_L, p.size()); // very good: p 0.0118546 -6.27225e-05 6.27225e-05 -2.09075e-05 2.09075e-05 -8.51788e-06 -2.09075e-05 10
// nlopt_opt opt = nlopt_create(NLOPT_GN_ISRES, p.size()); // rather bad
// nlopt_opt opt = nlopt_create(NLOPT_GN_CRS2_LM, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LD_MMA, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LD_CCSAQ, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LD_SLSQP, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LD_LBFGS, p.size());
// nlopt_opt opt = nlopt_create(NLOPT_LD_TNEWTON_PRECOND, p.size()); // bad
// nlopt_opt opt = nlopt_create(NLOPT_LD_TNEWTON_PRECOND_RESTART, p.size()); // bad
// nlopt_opt opt = nlopt_create(NLOPT_LD_VAR2, p.size());
nlopt_set_min_objective(opt, f_evaluate, &evaluator);
nlopt_set_lower_bounds(opt, lowerBound.data());
nlopt_set_upper_bounds(opt, upperBound.data());
nlopt_set_ftol_abs(opt, 1E-6);
nlopt_set_xtol_rel(opt, 1E-3);
nlopt_set_maxeval(opt, 1E8);
nlopt_set_maxtime(opt, 7200);
double pa[p.size()];
memcpy(pa, p.data(), p.size()*sizeof(double));
double cost = 0;
// std::string tmp; std::cerr << "Press enter to start optimization\n"; std::getline(std::cin, tmp);
nlopt_result ret = nlopt_optimize(opt, pa, &cost);
Eigen::VectorXd p_res = Eigen::Map<Eigen::VectorXd>(pa, p.size());
if (f)
*f = cost;
std::cerr << "\nInitial guess:\n";
std::cerr << " p " << p.transpose() << "\n";
std::cerr << " value " << evaluator.evaluate(p) << "\n";
std::cerr << "Optimization result (return code " << ret << "):\n";
std::cerr << " p " << p_res.transpose() << "\n";
std::cerr << " value " << evaluator.evaluate(p_res) << "\n";
nlopt_destroy(opt);
return p_res;
}
double Optimize_Torsion_Parameters(int Idx_Soft_Tor)
{
double lb[N_TOR_PARA] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -100.0 }; /* lower bounds */
double ub[N_TOR_PARA] = { 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 100.0 }; /* lower bounds */
double Phase[32][5]={{0, 0, 0, 0, 0}, {0, 0, 0, 0, PI}, {0, 0, 0, PI, 0}, {0, 0, 0, PI, PI}, {0, 0, PI, 0, 0}, {0, 0, PI, 0, PI}, {0, 0, PI, PI, 0}, {0, 0, PI, PI, PI}, {0, PI, 0, 0, 0}, {0, PI, 0, 0, PI},
{0, PI, 0, PI, 0}, {0, PI, 0, PI, PI}, {0, PI, PI, 0, 0}, {0, PI, PI, 0, PI}, {0, PI, PI, PI, 0}, {0, PI, PI, PI, PI}, {PI, 0, 0, 0, 0}, {PI, 0, 0, 0, PI}, {PI, 0, 0, PI, 0}, {PI, 0, 0, PI, PI},
{PI, 0, PI, 0, 0}, {PI, 0, PI, 0, PI}, {PI, 0, PI, PI, 0}, {PI, 0, PI, PI, PI}, {PI, PI, 0, 0, 0}, {PI, PI, 0, 0, PI}, {PI, PI, 0, PI, 0}, {PI, PI, 0, PI, PI}, {PI, PI, PI, 0, 0}, {PI, PI, PI, 0, PI},
{PI, PI, PI, PI, 0}, {PI, PI, PI, PI, PI}};
nlopt_opt opt;
double Chi_SQ;
int i, j, Idx_Phi;
Chi_SQ_Min = 1.0E100;
opt = nlopt_create(NLOPT_LD_LBFGS, N_TOR_PARA);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-8);
iseed = time(NULL);
ActiveRun = 0;
Chi_SQ_Min_Local[0] = 1.0E200;
FailCount = Iteration = 0;
Idx_Phi = IdxDihSelect[Idx_Soft_Tor];
Para_Tor[10] = 0.0;
for(i=0; i<N_TOR_PARA; i++) {
IsPara_Fixed[i] = 1;
}
IsPara_Fixed[N_TOR_PARA-1] = 0; // only optimize the last parameter
if (nlopt_optimize(opt, Para_Tor, &Chi_SQ) < 0) {
printf("nlopt failed!\n");
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
memcpy(Para_Tor, Para_Best, sizeof(double)*N_TOR_PARA);
CalObjectiveFunction_Tor(Para_Tor);
nlopt_destroy(opt);
return Chi_SQ_Min;
}
int call_nlopt(nlopt_algorithm alg, double ftol, double *step_size, double *params, unsigned np, double (*func) (unsigned,const double*,double*,void*),double *lower, double *upper) {
nlopt_opt opt;
double minf; /* the minimum objective value, upon return */
int retval;
int i;
opt = nlopt_create(alg,np);
nlopt_set_lower_bounds(opt,lower);
nlopt_set_upper_bounds(opt,upper);
nlopt_set_min_objective(opt,func,NULL);
nlopt_set_ftol_abs(opt,ftol);
nlopt_set_initial_step(opt,step_size);
retval = nlopt_optimize(opt, params, &minf) ;
nlopt_destroy(opt);
return retval;
}
double Shredder::optimize(double x0)
{
// bounds may have changed
nlopt_set_lower_bounds(opt, &lower_limit);
nlopt_set_upper_bounds(opt, &upper_limit);
x0 = std::max<double>(std::min<double>(x0, upper_limit), lower_limit);
//x0 = (lower_limit + upper_limit) / 2;
double maxf;
nlopt_result result = nlopt_optimize(opt, &x0, &maxf);
if (result < 0 && result != NLOPT_ROUNDOFF_LIMITED) {
Logger::warn("Optimization failed with code %d", (int) result);
}
return std::max<double>(std::min<double>(x0, upper_limit), lower_limit);
}
double Do_Geometry_Optimization(CMol *pMol)
{
int i, nAtom, nDim, iPos, Return_Opt;
double x[MAX_NUM_ATOM*3], x_Ini[MAX_NUM_ATOM], y_Ini[MAX_NUM_ATOM], z_Ini[MAX_NUM_ATOM], E_min=1.0E100;
// pMol->Restrain_All_Torsions(1);
nAtom = pMol->nAtom;
nDim = 3*nAtom;
// for a large molecule with many soft dihedrals, we prefer the optimizer in nlopt since it is around 8 times faster
memcpy(x_Ini, pMol->x, sizeof(double)*nAtom); // backup the structure
memcpy(y_Ini, pMol->y, sizeof(double)*nAtom);
memcpy(z_Ini, pMol->z, sizeof(double)*nAtom);
opt_Geo = nlopt_create(NLOPT_LD_LBFGS, nDim); // fast for non-polarizable model. Not applicable for drude model
nlopt_set_min_objective(opt_Geo, func_Geo_Optimization, pMol);
nlopt_set_ftol_rel(opt_Geo, 5E-12);
for(i=0; i<nAtom; i++) { // to set up the initial parameters
iPos = 3*i;
x[iPos ] = pMol->x[i];
x[iPos+1] = pMol->y[i];
x[iPos+2] = pMol->z[i];
}
Iter_Geo_Opt = 0;
Return_Opt = nlopt_optimize(opt_Geo, x, &E_min);
nlopt_destroy(opt_Geo);
if( (Return_Opt == NLOPT_FTOL_REACHED) || (Return_Opt == NLOPT_SUCCESS) ) { // success in optimization
pMol->Restrain_All_Torsions(0);
return (pMol->Cal_E(0));
}
else { // try FullGeometryOptimization_LBFGS()
memcpy(pMol->x, x_Ini, sizeof(double)*nAtom); // restore the structure
memcpy(pMol->y, y_Ini, sizeof(double)*nAtom);
memcpy(pMol->z, z_Ini, sizeof(double)*nAtom);
pMol->FullGeometryOptimization_LBFGS_step(0);
pMol->Restrain_All_Torsions(0);
E_min = pMol->Cal_E(0);
return E_min;
}
}
/*
* NLOPT optimization routine for table tennis traj gen
*
*/
void nlopt_optim_poly_run(double *x, double *params) {
static double tol[EQ_CONSTR_DIM];
static double lb[OPTIM_DIM]; /* lower bounds */
static double ub[OPTIM_DIM]; /* upper bounds */
set_bounds(lb,ub);
const_vec(EQ_CONSTR_DIM,1e-2,tol); /* set tolerances equal to second argument */
nlopt_opt opt;
opt = nlopt_create(NLOPT_LN_COBYLA, OPTIM_DIM); /* LN = does not require gradients */
//nlopt_set_xtol_rel(opt, 1e-2);
//opt = nlopt_create(NLOPT_AUGLAG, OPTIM_DIM); /* algorithm and dimensionality */
//nlopt_set_local_optimizer(opt, opt);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, costfunc, params);
nlopt_add_inequality_mconstraint(opt, INEQ_CONSTR_DIM, joint_limits_ineq_constr, params, tol);
nlopt_add_equality_mconstraint(opt, EQ_CONSTR_DIM, kinematics_eq_constr, params, tol);
nlopt_set_xtol_rel(opt, 1e-2);
//int maxeval = 20000;
//nlopt_set_maxeval(opt, maxeval);
//double maxtime = 0.001;
//nlopt_set_maxtime(opt, maxtime);
//init_soln_to_rest_posture(x,params); //parameters are the initial joint positions q0
double initTime = get_time();
double minf; /* the minimum objective value, upon return */
if (nlopt_optimize(opt, x, &minf) < 0) {
printf("NLOPT failed!\n");
}
else {
//nlopt_example_run();
printf("NLOPT took %f ms\n", (get_time() - initTime)/1e3);
printf("Found minimum at f = %0.10g\n", minf);
test_optim(x,params);
}
nlopt_destroy(opt);
}
double NLfit::run_method(vector<realt>* best_a)
{
if (opt_ != NULL && na_ != (int) nlopt_get_dimension(opt_)) {
nlopt_destroy(opt_);
opt_ = NULL;
}
if (opt_ == NULL) {
opt_ = nlopt_create(algorithm_, na_);
nlopt_set_min_objective(opt_, calculate_for_nlopt, this);
}
// this is also handled in Fit::common_termination_criteria()
nlopt_set_maxtime(opt_, F_->get_settings()->max_fitting_time);
nlopt_set_maxeval(opt_, max_eval() - 1); // save 1 eval for final calc.
nlopt_set_ftol_rel(opt_, F_->get_settings()->ftol_rel);
nlopt_set_xtol_rel(opt_, F_->get_settings()->xtol_rel);
double *lb = new double[na_];
double *ub = new double[na_];
for (int i = 0; i < na_; ++i) {
const RealRange& d = F_->mgr.get_variable(i)->domain;
lb[i] = d.lo;
ub[i] = d.hi;
}
nlopt_set_lower_bounds(opt_, lb);
nlopt_set_upper_bounds(opt_, ub);
delete [] lb;
delete [] ub;
double opt_f;
double *a = new double[na_];
for (int i = 0; i < na_; ++i)
a[i] = a_orig_[i];
nlopt_result r = nlopt_optimize(opt_, a, &opt_f);
F_->msg("NLopt says: " + S(nlresult_to_string(r)));
best_a->assign(a, a+na_);
delete [] a;
return opt_f;
}
void calculateSigma2() {
// use non linear optimization to calculate sigma2
nlopt_opt opt;
const int nParam = sigma2.size();
std::vector<double> lb(nParam, 1e-10);
opt = nlopt_create(NLOPT_LN_COBYLA, nParam);
nlopt_set_lower_bounds(opt, lb.data());
nlopt_set_min_objective(opt, goalFunction, this);
nlopt_set_xtol_rel(opt, 1e-4);
double minf; /* the minimum objective value, upon return */
int retCode = nlopt_optimize(opt, sigma2.data(), &minf);
if (retCode < 0) {
#ifdef DEBUG
printf("nlopt failed [ %d ]!\n", retCode);
#endif
} else {
#ifdef DEBUG
printf("found minimum at %g\n", minf);
#endif
}
nlopt_destroy(opt);
}
void
FitOrientation(
const int NrOfFiles,
const int nLayers,
const double ExcludePoleAngle,
double Lsd[nLayers],
const long long int SizeObsSpots,
const double XGrain[3],
const double YGrain[3],
double TiltsOrig[3],
const double OmegaStart,
const double OmegaStep,
const double px,
double ybc[nLayers],
double zbc[nLayers],
const double gs,
double OmegaRanges[MAX_N_OMEGA_RANGES][2],
const int NoOfOmegaRanges,
double BoxSizes[MAX_N_OMEGA_RANGES][4],
double P0[nLayers][3],
const int NrPixelsGrid,
int *ObsSpotsInfo,
double EulerIn[3],
double tol,
double *EulerOutA,
double *EulerOutB,
double *EulerOutC,
double *ResultFracOverlap,
double hkls[5000][4],
double Thetas[5000],
int n_hkls,
double *LsdFit,
double *TiltsFit,
double **BCsFit,
double tolLsd,
double tolLsdRel,
double tolTilts,
double tolBCsa,
double tolBCsb)
{
unsigned n;
long int i,j;
n = 6+(nLayers*3);
double x[n],xl[n],xu[n];
for (i=0;i<n;i++){
x[i] = 0;
xl[i] = 0;
xu[i] = 0;
}
for( i=0; i<3; i++)
{
x[i] = EulerIn[i];
xl[i] = x[i] - (tol*M_PI/180);
xu[i] = x[i] + (tol*M_PI/180);
}
int count = 0;
for (i=3;i<6;i++)
{
x[i] = TiltsOrig[count];
xl[i] = x[i] - tolTilts;
xu[i] = x[i] + tolTilts;
count++;
}
count = 0;
x[6] = Lsd[0];
xl[6] = x[6] - tolLsd;
xu[6] = x[6] + tolLsd;
count++;
for (i=7;i<nLayers+6;i++)
{
x[i] = Lsd[count] - Lsd[count-1];
xl[i] = x[i] - tolLsdRel;
xu[i] = x[i] + tolLsdRel;
count++;
}
count = 0;
for (i=6+nLayers;i<6+(nLayers*2);i++)
{
x[i] = ybc[count];
x[i+nLayers] = zbc[count];
xl[i] = x[i] - tolBCsa;
xl[i+nLayers] = x[i+nLayers] - tolBCsb;
xu[i] = x[i] + tolBCsa;
xu[i+nLayers] = x[i+nLayers] + tolBCsb;
count++;
}
struct my_func_data f_data;
f_data.NrOfFiles = NrOfFiles;
f_data.nLayers = nLayers;
f_data.n_hkls = n_hkls;
for (i=0;i<5000;i++){
f_data.hkls[i][0] = hkls[i][0];
f_data.hkls[i][1] = hkls[i][1];
f_data.hkls[i][2] = hkls[i][2];
f_data.hkls[i][3] = hkls[i][3];
f_data.Thetas[i] = Thetas[i];
}
f_data.ExcludePoleAngle = ExcludePoleAngle;
f_data.SizeObsSpots = SizeObsSpots;
f_data.P0 = allocMatrixF(nLayers,3);
for (i=0;i<3;i++){
f_data.XGrain[i] = XGrain[i];
f_data.YGrain[i] = YGrain[i];
for (j=0;j<nLayers;j++){
f_data.P0[j][i] = P0[j][i];
}
}
for (i=0;i<MAX_N_OMEGA_RANGES;i++){
for (j=0;j<2;j++){
f_data.OmegaRanges[i][j] = OmegaRanges[i][j];
}
for (j=0;j<4;j++){
f_data.BoxSizes[i][j] = BoxSizes[i][j];
}
}
f_data.ObsSpotsInfo = &ObsSpotsInfo[0];
f_data.OmegaStart = OmegaStart;
f_data.OmegaStep = OmegaStep;
f_data.px = px;
f_data.gs = gs;
f_data.NoOfOmegaRanges = NoOfOmegaRanges;
f_data.NrPixelsGrid = NrPixelsGrid;
struct my_func_data *f_datat;
f_datat = &f_data;
void* trp = (struct my_func_data *) f_datat;
double tole = 1e-3;
nlopt_opt opt;
opt = nlopt_create(NLOPT_LN_NELDERMEAD, n);
nlopt_set_lower_bounds(opt, xl);
nlopt_set_upper_bounds(opt, xu);
nlopt_set_min_objective(opt, problem_function, trp);
double minf=1;
nlopt_optimize(opt, x, &minf);
nlopt_destroy(opt);
*ResultFracOverlap = minf;
*EulerOutA = x[0];
*EulerOutB = x[1];
*EulerOutC = x[2];
TiltsFit[0] = x[3];
TiltsFit[1] = x[4];
TiltsFit[2] = x[5];
LsdFit[0] = x[6];
for (i=1;i<nLayers;i++){
LsdFit[i] = LsdFit[i-1] + x[6+i];
}
for (i=0;i<nLayers;i++){
BCsFit[i][0] = x[6+nLayers+i];
BCsFit[i][1] = x[6+nLayers+nLayers+i];
}
}
int main(int argc, char **argv)
{
/* -------Initialize and Get the parameters from command line ------*/
PetscInitialize(&argc, &argv, PETSC_NULL, PETSC_NULL);
PetscPrintf(PETSC_COMM_WORLD,"--------Initializing------ \n");
PetscErrorCode ierr;
PetscBool flg;
int myrank;
MPI_Comm_rank(MPI_COMM_WORLD,&myrank);
if(myrank==0)
mma_verbose=1;
/*-------------------------------------------------*/
int Mx,My,Mz,Mzslab, Npmlx,Npmly,Npmlz,DegFree, anisotropic;
PetscOptionsGetInt(PETSC_NULL,"-Nx",&Nx,&flg); MyCheckAndOutputInt(flg,Nx,"Nx","Nx");
PetscOptionsGetInt(PETSC_NULL,"-Ny",&Ny,&flg); MyCheckAndOutputInt(flg,Ny,"Ny","Nx");
PetscOptionsGetInt(PETSC_NULL,"-Nz",&Nz,&flg); MyCheckAndOutputInt(flg,Nz,"Nz","Nz");
PetscOptionsGetInt(PETSC_NULL,"-Mx",&Mx,&flg); MyCheckAndOutputInt(flg,Mx,"Mx","Mx");
PetscOptionsGetInt(PETSC_NULL,"-My",&My,&flg); MyCheckAndOutputInt(flg,My,"My","My");
PetscOptionsGetInt(PETSC_NULL,"-Mz",&Mz,&flg); MyCheckAndOutputInt(flg,Mz,"Mz","Mz");
PetscOptionsGetInt(PETSC_NULL,"-Mzslab",&Mzslab,&flg); MyCheckAndOutputInt(flg,Mzslab,"Mzslab","Mzslab");
PetscOptionsGetInt(PETSC_NULL,"-Npmlx",&Npmlx,&flg); MyCheckAndOutputInt(flg,Npmlx,"Npmlx","Npmlx");
PetscOptionsGetInt(PETSC_NULL,"-Npmly",&Npmly,&flg); MyCheckAndOutputInt(flg,Npmly,"Npmly","Npmly");
PetscOptionsGetInt(PETSC_NULL,"-Npmlz",&Npmlz,&flg); MyCheckAndOutputInt(flg,Npmlz,"Npmlz","Npmlz");
Nxyz = Nx*Ny*Nz;
// if anisotropic !=0, Degree of Freedom = 3*Mx*My*Mz; else DegFree = Mx*My*Mz;
PetscOptionsGetInt(PETSC_NULL,"-anisotropic",&anisotropic,&flg);
if(!flg) anisotropic = 0; // by default, it is isotropc.
DegFree = (anisotropic ? 3 : 1 )*Mx*My*((Mzslab==0)?Mz:1);
PetscPrintf(PETSC_COMM_WORLD," the Degree of Freedoms is %d \n ", DegFree);
int DegFreeAll=DegFree+1;
PetscPrintf(PETSC_COMM_WORLD," the Degree of Freedoms ALL is %d \n ", DegFreeAll);
int BCPeriod, Jdirection, Jdirectiontwo, LowerPML;
int bx[2], by[2], bz[2];
PetscOptionsGetInt(PETSC_NULL,"-BCPeriod",&BCPeriod,&flg); MyCheckAndOutputInt(flg,BCPeriod,"BCPeriod","BCPeriod given");
PetscOptionsGetInt(PETSC_NULL,"-Jdirection",&Jdirection,&flg); MyCheckAndOutputInt(flg,Jdirection,"Jdirection","Diapole current direction");
PetscOptionsGetInt(PETSC_NULL,"-Jdirectiontwo",&Jdirectiontwo,&flg); MyCheckAndOutputInt(flg,Jdirectiontwo,"Jdirectiontwo","Diapole current direction for source two");
PetscOptionsGetInt(PETSC_NULL,"-LowerPML",&LowerPML,&flg); MyCheckAndOutputInt(flg,LowerPML,"LowerPML","PML in the lower xyz boundary");
PetscOptionsGetInt(PETSC_NULL,"-bxl",bx,&flg); MyCheckAndOutputInt(flg,bx[0],"bxl","BC at x lower");
PetscOptionsGetInt(PETSC_NULL,"-bxu",bx+1,&flg); MyCheckAndOutputInt(flg,bx[1],"bxu","BC at x upper");
PetscOptionsGetInt(PETSC_NULL,"-byl",by,&flg); MyCheckAndOutputInt(flg,by[0],"byl","BC at y lower");
PetscOptionsGetInt(PETSC_NULL,"-byu",by+1,&flg); MyCheckAndOutputInt(flg,by[1],"byu","BC at y upper");
PetscOptionsGetInt(PETSC_NULL,"-bzl",bz,&flg); MyCheckAndOutputInt(flg,bz[0],"bzl","BC at z lower");
PetscOptionsGetInt(PETSC_NULL,"-bzu",bz+1,&flg); MyCheckAndOutputInt(flg,bz[1],"bzu","BC at z upper");
double epssub, RRT, sigmax, sigmay, sigmaz ;
PetscOptionsGetReal(PETSC_NULL,"-hx",&hx,&flg); MyCheckAndOutputDouble(flg,hx,"hx","hx");
hy = hx;
hz = hx;
hxyz = (Nz==1)*hx*hy + (Nz>1)*hx*hy*hz;
double omega, omegaone, omegatwo, wratio;
PetscOptionsGetReal(PETSC_NULL,"-omega",&omega,&flg); MyCheckAndOutputDouble(flg,omega,"omega","omega");
PetscOptionsGetReal(PETSC_NULL,"-wratio",&wratio,&flg); MyCheckAndOutputDouble(flg,wratio,"wratio","wratio");
omegaone=omega;
omegatwo=wratio*omega;
PetscPrintf(PETSC_COMM_WORLD,"---omegaone is %.16e and omegatwo is %.16e ---\n",omegaone, omegatwo);
PetscOptionsGetReal(PETSC_NULL,"-Qabs",&Qabs,&flg);
if (flg && Qabs>1e+15)
Qabs=1.0/0.0;
MyCheckAndOutputDouble(flg,Qabs,"Qabs","Qabs");
PetscOptionsGetReal(PETSC_NULL,"-epsair",&epsair,&flg); MyCheckAndOutputDouble(flg,epsair,"epsair","epsair");
PetscOptionsGetReal(PETSC_NULL,"-epssub",&epssub,&flg); MyCheckAndOutputDouble(flg,epssub,"epssub","epssub");
PetscOptionsGetReal(PETSC_NULL,"-RRT",&RRT,&flg); MyCheckAndOutputDouble(flg,RRT,"RRT","RRT given");
sigmax = pmlsigma(RRT,Npmlx*hx);
sigmay = pmlsigma(RRT,Npmly*hy);
sigmaz = pmlsigma(RRT,Npmlz*hz);
PetscPrintf(PETSC_COMM_WORLD,"----sigmax is %.12e \n",sigmax);
PetscPrintf(PETSC_COMM_WORLD,"----sigmay is %.12e \n",sigmay);
PetscPrintf(PETSC_COMM_WORLD,"----sigmaz is %.12e \n",sigmaz);
char initialdata[PETSC_MAX_PATH_LEN]; //filenameComm[PETSC_MAX_PATH_LEN];
PetscOptionsGetString(PETSC_NULL,"-initialdata",initialdata,PETSC_MAX_PATH_LEN,&flg); MyCheckAndOutputChar(flg,initialdata,"initialdata","Inputdata file");
PetscOptionsGetString(PETSC_NULL,"-filenameComm",filenameComm,PETSC_MAX_PATH_LEN,&flg); MyCheckAndOutputChar(flg,filenameComm,"filenameComm","Output filenameComm");
// add cx, cy, cz to indicate where the diapole current is;
int cx, cy, cz;
PetscOptionsGetInt(PETSC_NULL,"-cx",&cx,&flg);
if (!flg)
{cx=(LowerPML)*floor(Nx/2); PetscPrintf(PETSC_COMM_WORLD,"cx is %d by default \n",cx);}
else
{PetscPrintf(PETSC_COMM_WORLD,"the current poisiont cx is %d \n",cx);}
PetscOptionsGetInt(PETSC_NULL,"-cy",&cy,&flg);
if (!flg)
{cy=(LowerPML)*floor(Ny/2); PetscPrintf(PETSC_COMM_WORLD,"cy is %d by default \n",cy);}
else
{PetscPrintf(PETSC_COMM_WORLD,"the current poisiont cy is %d \n",cy);}
PetscOptionsGetInt(PETSC_NULL,"-cz",&cz,&flg);
if (!flg)
{cz=(LowerPML)*floor(Nz/2); PetscPrintf(PETSC_COMM_WORLD,"cz is %d by default \n",cz);}
else
{PetscPrintf(PETSC_COMM_WORLD,"the current poisiont cz is %d \n",cz);}
posj = (cx*Ny+ cy)*Nz + cz;
PetscPrintf(PETSC_COMM_WORLD,"the posj is %d \n. ", posj);
int fixpteps;
PetscOptionsGetInt(PETSC_NULL,"-fixpteps",&fixpteps,&flg); MyCheckAndOutputInt(flg,fixpteps,"fixpteps","fixpteps");
// Get minapproach;
PetscOptionsGetInt(PETSC_NULL,"-minapproach",&minapproach,&flg); MyCheckAndOutputInt(flg,minapproach,"minapproach","minapproach");
// Get withepsinldos;
PetscOptionsGetInt(PETSC_NULL,"-withepsinldos",&withepsinldos,&flg); MyCheckAndOutputInt(flg,withepsinldos,"withepsinldos","withepsinldos");
// Get outputbase;
PetscOptionsGetInt(PETSC_NULL,"-outputbase",&outputbase,&flg); MyCheckAndOutputInt(flg,outputbase,"outputbase","outputbase");
// Get cavityverbose;
PetscOptionsGetInt(PETSC_NULL,"-cavityverbose",&cavityverbose,&flg);
if(!flg) cavityverbose=0;
PetscPrintf(PETSC_COMM_WORLD,"the cavity verbose is set as %d \n", cavityverbose);
// Get refinedldos;
PetscOptionsGetInt(PETSC_NULL,"-refinedldos",&refinedldos,&flg);
if(!flg) refinedldos=0;
PetscPrintf(PETSC_COMM_WORLD,"the refinedldos is set as %d \n", refinedldos);
// Get cmpwrhs;
int cmpwrhs;
PetscOptionsGetInt(PETSC_NULL,"-cmpwrhs",&cmpwrhs,&flg);
if(!flg) cmpwrhs=0;
PetscPrintf(PETSC_COMM_WORLD,"the cmpwrhs is set as %d \n", cmpwrhs);
// Get lrzsqr;
PetscOptionsGetInt(PETSC_NULL,"-lrzsqr",&lrzsqr,&flg);
if(!flg) lrzsqr=0;
PetscPrintf(PETSC_COMM_WORLD,"the lrzsqr is set as %d \n", lrzsqr);
// Get newQdef;
PetscOptionsGetInt(PETSC_NULL,"-newQdef",&newQdef,&flg);
if(!flg) newQdef=0;
PetscPrintf(PETSC_COMM_WORLD,"the newQdef is set as %d \n", newQdef);
/*--------------------------------------------------------*/
/*--------------------------------------------------------*/
/*---------- Set the current source---------*/
//Mat D; //ImaginaryIMatrix;
ImagIMat(PETSC_COMM_WORLD, &D,6*Nxyz);
Vec J;
ierr = VecCreateMPI(PETSC_COMM_WORLD, PETSC_DECIDE, 6*Nxyz, &J);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) J, "Source");CHKERRQ(ierr);
VecSet(J,0.0); //initialization;
if (Jdirection == 1)
SourceSingleSetX(PETSC_COMM_WORLD, J, Nx, Ny, Nz, cx, cy, cz,1.0/hxyz);
else if (Jdirection ==2)
SourceSingleSetY(PETSC_COMM_WORLD, J, Nx, Ny, Nz, cx, cy, cz,1.0/hxyz);
else if (Jdirection == 3)
SourceSingleSetZ(PETSC_COMM_WORLD, J, Nx, Ny, Nz, cx, cy, cz,1.0/hxyz);
else
PetscPrintf(PETSC_COMM_WORLD," Please specify correct direction of current: x (1) , y (2) or z (3)\n ");
Vec Jtwo;
ierr = VecDuplicate(J, &Jtwo);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) Jtwo, "Sourcetwo");CHKERRQ(ierr);
VecSet(Jtwo,0.0); //initialization;
if (Jdirectiontwo == 1)
SourceSingleSetX(PETSC_COMM_WORLD, Jtwo, Nx, Ny, Nz, cx, cy, cz,1.0/hxyz);
else if (Jdirectiontwo ==2)
SourceSingleSetY(PETSC_COMM_WORLD, Jtwo, Nx, Ny, Nz, cx, cy, cz,1.0/hxyz);
else if (Jdirectiontwo == 3)
SourceSingleSetZ(PETSC_COMM_WORLD, Jtwo, Nx, Ny, Nz, cx, cy, cz,1.0/hxyz);
else
PetscPrintf(PETSC_COMM_WORLD," Please specify correct direction of current two: x (1) , y (2) or z (3)\n ");
//Vec b; // b= i*omega*J;
Vec bone, btwo;
ierr = VecDuplicate(J,&b);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) b, "rhsone");CHKERRQ(ierr);
ierr = VecDuplicate(J,&bone);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) bone, "rhsone");CHKERRQ(ierr);
ierr = VecDuplicate(Jtwo,&btwo);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) btwo, "rhstwo");CHKERRQ(ierr);
if (cmpwrhs==0)
{
ierr = MatMult(D,J,b);CHKERRQ(ierr);
ierr = MatMult(D,Jtwo,btwo);CHKERRQ(ierr);
VecCopy(b,bone);
VecScale(bone,omegaone);
VecScale(btwo,omegatwo);
VecScale(b,omega);
}
else
{
double complex cmpiomega;
cmpiomega = cpow(1+I/Qabs,newQdef+1);
double sqrtiomegaR = -omega*cimag(csqrt(cmpiomega));
double sqrtiomegaI = omega*creal(csqrt(cmpiomega));
PetscPrintf(PETSC_COMM_WORLD,"the real part of sqrt cmpomega is %g and imag sqrt is % g ", sqrtiomegaR, sqrtiomegaI);
Vec tmpi;
ierr = VecDuplicate(J,&tmpi);
VecSet(b,0.0);
VecSet(tmpi,0.0);
CmpVecScale(J,b,sqrtiomegaR,sqrtiomegaI,D,tmpi);
VecDestroy(&tmpi);
}
/*-------Get the weight vector ------------------*/
//Vec weight;
ierr = VecDuplicate(J,&weight); CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) weight, "weight");CHKERRQ(ierr);
if(LowerPML==0)
GetWeightVec(weight, Nx, Ny,Nz); // new code handles both 3D and 2D;
else
VecSet(weight,1.0);
Vec weightedJ;
ierr = VecDuplicate(J,&weightedJ); CHKERRQ(ierr);
ierr = VecPointwiseMult(weightedJ,J,weight);
ierr = PetscObjectSetName((PetscObject) weightedJ, "weightedJ");CHKERRQ(ierr);
Vec weightedJtwo;
ierr = VecDuplicate(Jtwo,&weightedJtwo); CHKERRQ(ierr);
ierr = VecPointwiseMult(weightedJtwo,Jtwo,weight);
ierr = PetscObjectSetName((PetscObject) weightedJtwo, "weightedJtwo");CHKERRQ(ierr);
//Vec vR;
ierr = VecDuplicate(J,&vR); CHKERRQ(ierr);
GetRealPartVec(vR, 6*Nxyz);
// VecFReal;
if (lrzsqr)
{ ierr = VecDuplicate(J,&epsFReal); CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) epsFReal, "epsFReal");CHKERRQ(ierr);
if (newQdef==0)
{
sqrtomegaI = omega*cimag(csqrt(1+I/Qabs));
PetscPrintf(PETSC_COMM_WORLD,"the real part of sqrt cmpomega is %g and imag sqrt is % g ", omega*creal(csqrt(1+I/Qabs)), sqrtomegaI);
betar = 2*sqrtomegaI;
betai = betar/Qabs;
}
else
{
double gamma;
gamma = omega/Qabs;
betar = 2*gamma*(1-1.0/pow(Qabs,2));
betai = 2*gamma*(2.0/Qabs);
}
ierr = VecDuplicate(J,&nb); CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) nb, "nb"); CHKERRQ(ierr);
ierr = VecDuplicate(J,&y); CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) y, "y"); CHKERRQ(ierr);
ierr = VecDuplicate(J,&xsqr); CHKERRQ(ierr); // xsqr = x*x;
ierr = PetscObjectSetName((PetscObject) xsqr, "xsqr"); CHKERRQ(ierr);
CongMat(PETSC_COMM_WORLD, &C, 6*Nxyz);
}
/*----------- Define PML muinv vectors */
Vec muinvpml;
MuinvPMLFull(PETSC_COMM_SELF, &muinvpml,Nx,Ny,Nz,Npmlx,Npmly,Npmlz,sigmax,sigmay,sigmaz,omega, LowerPML);
//double *muinv;
muinv = (double *) malloc(sizeof(double)*6*Nxyz);
int add=0;
AddMuAbsorption(muinv,muinvpml,Qabs,add);
ierr = VecDestroy(&muinvpml); CHKERRQ(ierr);
/*---------- Define PML eps vectors: epspml---------- */
Vec epspml; //epspmlQ, epscoef;
ierr = VecDuplicate(J,&epspml);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) epspml,"EpsPMLFull"); CHKERRQ(ierr);
EpsPMLFull(PETSC_COMM_WORLD, epspml,Nx,Ny,Nz,Npmlx,Npmly,Npmlz,sigmax,sigmay,sigmaz,omega, LowerPML);
ierr = VecDuplicate(J,&epspmlQ);CHKERRQ(ierr);
Vec epscoefone, epscoeftwo;
ierr = VecDuplicate(J,&epscoefone);CHKERRQ(ierr);
ierr = VecDuplicate(J,&epscoeftwo);CHKERRQ(ierr);
// compute epspmlQ,epscoef;
EpsCombine(D, weight, epspml, epspmlQ, epscoefone, Qabs, omegaone);
EpsCombine(D, weight, epspml, epspmlQ, epscoeftwo, Qabs, omegatwo);
/*--------- Setup the interp matrix ----------------------- */
/* for a samll eps block, interp it into yee-lattice. The interp matrix A and PML epspml only need to generated once;*/
//Mat A;
//new routine for myinterp;
myinterp(PETSC_COMM_WORLD, &A, Nx,Ny,Nz, LowerPML*floor((Nx-Mx)/2),LowerPML*floor((Ny-My)/2),LowerPML*floor((Nz-Mz)/2), Mx,My,Mz,Mzslab, anisotropic); // LoweerPML*Npmlx,..,.., specify where the interp starts;
//Vec epsSReal, epsgrad, vgrad; // create compatiable vectors with A.
ierr = MatGetVecs(A,&epsSReal, &epsgrad); CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) epsgrad, "epsgrad");CHKERRQ(ierr);
ierr = VecDuplicate(epsSReal, &vgrad); CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) epsSReal, "epsSReal");CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) vgrad, "vgrad");CHKERRQ(ierr);
/*---------Setup the epsmedium vector----------------*/
//Vec epsmedium;
ierr = VecDuplicate(J,&epsmedium); CHKERRQ(ierr);
GetMediumVec(epsmedium,Nz,Mz,epsair,epssub);
/*--------- Setup the finitie difference matrix-------------*/
//Mat M;
MoperatorGeneral(PETSC_COMM_WORLD, &M, Nx,Ny,Nz,hx,hy,hz, bx, by, bz,muinv,BCPeriod);
free(muinv);
/*--------Setup the KSP variables ---------------*/
KSP kspone;
PC pcone;
ierr = KSPCreate(PETSC_COMM_WORLD,&kspone);CHKERRQ(ierr);
//ierr = KSPSetType(ksp, KSPPREONLY);CHKERRQ(ierr);
ierr = KSPSetType(kspone, KSPGMRES);CHKERRQ(ierr);
ierr = KSPGetPC(kspone,&pcone);CHKERRQ(ierr);
ierr = PCSetType(pcone,PCLU);CHKERRQ(ierr);
ierr = PCFactorSetMatSolverPackage(pcone,MATSOLVERPASTIX);CHKERRQ(ierr);
ierr = PCSetFromOptions(pcone);
int maxkspit = 20;
ierr = KSPSetTolerances(kspone,1e-14,PETSC_DEFAULT,PETSC_DEFAULT,maxkspit);CHKERRQ(ierr);
ierr = KSPSetFromOptions(kspone);CHKERRQ(ierr);
KSP ksptwo;
PC pctwo;
ierr = KSPCreate(PETSC_COMM_WORLD,&ksptwo);CHKERRQ(ierr);
//ierr = KSPSetType(ksp, KSPPREONLY);CHKERRQ(ierr);
ierr = KSPSetType(ksptwo, KSPGMRES);CHKERRQ(ierr);
ierr = KSPGetPC(ksptwo,&pctwo);CHKERRQ(ierr);
ierr = PCSetType(pctwo,PCLU);CHKERRQ(ierr);
ierr = PCFactorSetMatSolverPackage(pctwo,MATSOLVERPASTIX);CHKERRQ(ierr);
ierr = PCSetFromOptions(pctwo);
ierr = KSPSetTolerances(ksptwo,1e-14,PETSC_DEFAULT,PETSC_DEFAULT,maxkspit);CHKERRQ(ierr);
ierr = KSPSetFromOptions(ksptwo);CHKERRQ(ierr);
/*--------- Create the space for solution vector -------------*/
//Vec x;
ierr = VecDuplicate(J,&x);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) x, "Solution");CHKERRQ(ierr);
/*----------- Create the space for final eps -------------*/
//Vec epsC, epsCi, epsP;
ierr = VecDuplicate(J,&epsC);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject) epsC, "EpsC");CHKERRQ(ierr);
ierr = VecDuplicate(J,&epsCi);CHKERRQ(ierr);
ierr = VecDuplicate(J,&epsP);CHKERRQ(ierr);
ierr = VecSet(epsP,0.0); CHKERRQ(ierr);
ierr = VecAssemblyBegin(epsP); CHKERRQ(ierr);
ierr = VecAssemblyEnd(epsP); CHKERRQ(ierr);
/*------------ Create space used in the solver ------------*/
//Vec vgradlocal,tmp, tmpa,tmpb;
ierr = VecCreateSeq(PETSC_COMM_SELF, DegFree, &vgradlocal); CHKERRQ(ierr);
ierr = VecDuplicate(J,&tmp); CHKERRQ(ierr);
ierr = VecDuplicate(J,&tmpa); CHKERRQ(ierr);
ierr = VecDuplicate(J,&tmpb); CHKERRQ(ierr);
// Vec pickposvec; this vector is zero except that first entry is one;
if (withepsinldos)
{ ierr = VecDuplicate(J,&pickposvec); CHKERRQ(ierr);
ierr = VecSet(pickposvec,0.0); CHKERRQ(ierr);
ierr = VecSetValue(pickposvec,posj+Jdirection*Nxyz,1.0,INSERT_VALUES);
VecAssemblyBegin(pickposvec);
VecAssemblyEnd(pickposvec);
}
/*------------ Create scatter used in the solver -----------*/
//VecScatter scatter;
//IS from, to;
ierr =ISCreateStride(PETSC_COMM_SELF,DegFree,0,1,&from); CHKERRQ(ierr);
ierr =ISCreateStride(PETSC_COMM_SELF,DegFree,0,1,&to); CHKERRQ(ierr);
/*-------------Read the input file -------------------------*/
double *epsoptAll;
epsoptAll = (double *) malloc(DegFreeAll*sizeof(double));
FILE *ptf;
ptf = fopen(initialdata,"r");
PetscPrintf(PETSC_COMM_WORLD,"reading from input files \n");
int i;
// set the dielectric at the center is fixed, and alwyas high
//epsopt[0]=myub; is defined below near lb and ub;
for (i=0;i<DegFree;i++)
{ //PetscPrintf(PETSC_COMM_WORLD,"current eps reading is %lf \n",epsopt[i]);
fscanf(ptf,"%lf",&epsoptAll[i]);
}
epsoptAll[DegFreeAll-1]=0; //initialize auxiliary variable;
fclose(ptf);
/*----declare these data types, althought they may not be used for job 2 -----------------*/
double mylb,myub, *lb=NULL, *ub=NULL;
int maxeval, maxtime, mynloptalg;
double maxf;
nlopt_opt opt;
nlopt_result result;
/*--------------------------------------------------------------*/
/*----Now based on Command Line, Do the corresponding job----*/
/*----------------------------------------------------------------*/
//int Job; set Job to be gloabl variables;
PetscOptionsGetInt(PETSC_NULL,"-Job",&Job,&flg); MyCheckAndOutputInt(flg,Job,"Job","The Job indicator you set");
int numofvar=(Job==1)*DegFreeAll + (Job==3);
/*-------- convert the epsopt array to epsSReal (if job!=optmization) --------*/
if (Job==2 || Job ==3)
{
// copy epsilon from file to epsSReal; (different from FindOpt.c, because epsilon is not degree-of-freedoms in computeQ.
// i) create a array to read file (done above in epsopt); ii) convert the array to epsSReal;
int ns, ne;
ierr = VecGetOwnershipRange(epsSReal,&ns,&ne);
for(i=ns;i<ne;i++)
{ ierr=VecSetValue(epsSReal,i,epsoptAll[i],INSERT_VALUES);
CHKERRQ(ierr); }
if(withepsinldos)
{ epsatinterest = epsoptAll[cx*Ny*Nz + cy*Nz + cz] + epsair;
PetscPrintf(PETSC_COMM_WORLD, " the relative permitivity at the point of current is %.16e \n ",epsatinterest);}
ierr = VecAssemblyBegin(epsSReal); CHKERRQ(ierr);
ierr = VecAssemblyEnd(epsSReal); CHKERRQ(ierr);
}
if (Job==1 || Job==3) // optimization bounds setup;
{
PetscOptionsGetInt(PETSC_NULL,"-maxeval",&maxeval,&flg); MyCheckAndOutputInt(flg,maxeval,"maxeval","max number of evaluation");
PetscOptionsGetInt(PETSC_NULL,"-maxtime",&maxtime,&flg); MyCheckAndOutputInt(flg,maxtime,"maxtime","max time of evaluation");
PetscOptionsGetInt(PETSC_NULL,"-mynloptalg",&mynloptalg,&flg); MyCheckAndOutputInt(flg,mynloptalg,"mynloptalg","The algorithm used ");
PetscOptionsGetReal(PETSC_NULL,"-mylb",&mylb,&flg); MyCheckAndOutputDouble(flg,mylb,"mylb","optimization lb");
PetscOptionsGetReal(PETSC_NULL,"-myub",&myub,&flg); MyCheckAndOutputDouble(flg,myub,"myub","optimization ub");
lb = (double *) malloc(numofvar*sizeof(double));
ub = (double *) malloc(numofvar*sizeof(double));
// the dielectric constant at center is fixed!
for(i=0;i<numofvar;i++)
{
lb[i] = mylb;
ub[i] = myub;
} //initial guess, lower bounds, upper bounds;
// set lower and upper bounds for auxiliary variable;
lb[numofvar-1]=0;
ub[numofvar-1]=1.0/0.0;
//fix the dielectric at the center to be high for topology optimization;
if (Job==1 && fixpteps==1)
{
epsoptAll[0]=myub;
lb[0]=myub;
ub[0]=myub;
}
opt = nlopt_create(mynloptalg, numofvar);
myfundatatypeshg data[2] = {{omegaone, bone, weightedJ, epscoefone,kspone},{omegatwo, btwo, weightedJtwo, epscoeftwo,ksptwo}};
nlopt_add_inequality_constraint(opt,ldosconstraint, &data[0], 1e-8);
nlopt_add_inequality_constraint(opt,ldosconstraint, &data[1], 1e-8);
nlopt_set_lower_bounds(opt,lb);
nlopt_set_upper_bounds(opt,ub);
nlopt_set_maxeval(opt,maxeval);
nlopt_set_maxtime(opt,maxtime);
/*add functionality to choose local optimizer; */
int mynloptlocalalg;
nlopt_opt local_opt;
PetscOptionsGetInt(PETSC_NULL,"-mynloptlocalalg",&mynloptlocalalg,&flg); MyCheckAndOutputInt(flg,mynloptlocalalg,"mynloptlocalalg","The local optimization algorithm used ");
if (mynloptlocalalg)
{
local_opt=nlopt_create(mynloptlocalalg,numofvar);
nlopt_set_ftol_rel(local_opt, 1e-14);
nlopt_set_maxeval(local_opt,100000);
nlopt_set_local_optimizer(opt,local_opt);
}
}
switch (Job)
{
case 1:
{
if (minapproach)
nlopt_set_min_objective(opt,maxminobjfun,NULL);// NULL: no data to be passed because of global variables;
else
nlopt_set_max_objective(opt,maxminobjfun,NULL);
result = nlopt_optimize(opt,epsoptAll,&maxf);
}
break;
case 2 : //AnalyzeStructure
{
int Linear, Eig, maxeigit;
PetscOptionsGetInt(PETSC_NULL,"-Linear",&Linear,&flg); MyCheckAndOutputInt(flg,Linear,"Linear","Linear solver indicator");
PetscOptionsGetInt(PETSC_NULL,"-Eig",&Eig,&flg); MyCheckAndOutputInt(flg,Eig,"Eig","Eig solver indicator");
PetscOptionsGetInt(PETSC_NULL,"-maxeigit",&maxeigit,&flg); MyCheckAndOutputInt(flg,maxeigit,"maxeigit","maximum number of Eig solver iterations is");
/*----------------------------------*/
//EigenSolver(Linear, Eig, maxeigit);
/*----------------------------------*/
OutputVec(PETSC_COMM_WORLD, weight,filenameComm, "weight.m");
}
break;
default:
PetscPrintf(PETSC_COMM_WORLD,"--------Interesting! You're doing nothing!--------\n ");
}
if(Job==1 || Job==3)
{
/* print the optimization parameters */
#if 0
double xrel, frel, fabs;
// double *xabs;
frel=nlopt_get_ftol_rel(opt);
fabs=nlopt_get_ftol_abs(opt);
xrel=nlopt_get_xtol_rel(opt);
PetscPrintf(PETSC_COMM_WORLD,"nlopt frel is %g \n",frel);
PetscPrintf(PETSC_COMM_WORLD,"nlopt fabs is %g \n",fabs);
PetscPrintf(PETSC_COMM_WORLD,"nlopt xrel is %g \n",xrel);
//nlopt_result nlopt_get_xtol_abs(const nlopt_opt opt, double *tol);
#endif
/*--------------*/
if (result < 0) {
PetscPrintf(PETSC_COMM_WORLD,"nlopt failed! \n", result);
}
else {
PetscPrintf(PETSC_COMM_WORLD,"found extremum %0.16e\n", minapproach?1.0/maxf:maxf);
}
PetscPrintf(PETSC_COMM_WORLD,"nlopt returned value is %d \n", result);
if(Job==1)
{ //OutputVec(PETSC_COMM_WORLD, epsopt,filenameComm, "epsopt.m");
//OutputVec(PETSC_COMM_WORLD, epsgrad,filenameComm, "epsgrad.m");
//OutputVec(PETSC_COMM_WORLD, vgrad,filenameComm, "vgrad.m");
//OutputVec(PETSC_COMM_WORLD, x,filenameComm, "x.m");
int rankA;
MPI_Comm_rank(PETSC_COMM_WORLD, &rankA);
if(rankA==0)
{
ptf = fopen(strcat(filenameComm,"epsopt.txt"),"w");
for (i=0;i<DegFree;i++)
fprintf(ptf,"%0.16e \n",epsoptAll[i]);
fclose(ptf);
PetscPrintf(PETSC_COMM_WORLD,"the t parameter is %.8e \n",epsoptAll[DegFreeAll-1]);
}
}
nlopt_destroy(opt);
}
ierr = PetscPrintf(PETSC_COMM_WORLD,"--------Done!--------\n ");CHKERRQ(ierr);
/*------------------------------------*/
/* ----------------------Destroy Vecs and Mats----------------------------*/
free(epsoptAll);
free(lb);
free(ub);
ierr = VecDestroy(&J); CHKERRQ(ierr);
ierr = VecDestroy(&b); CHKERRQ(ierr);
ierr = VecDestroy(&weight); CHKERRQ(ierr);
ierr = VecDestroy(&weightedJ); CHKERRQ(ierr);
ierr = VecDestroy(&vR); CHKERRQ(ierr);
ierr = VecDestroy(&epspml); CHKERRQ(ierr);
ierr = VecDestroy(&epspmlQ); CHKERRQ(ierr);
ierr = VecDestroy(&epsSReal); CHKERRQ(ierr);
ierr = VecDestroy(&epsgrad); CHKERRQ(ierr);
ierr = VecDestroy(&vgrad); CHKERRQ(ierr);
ierr = VecDestroy(&epsmedium); CHKERRQ(ierr);
ierr = VecDestroy(&epsC); CHKERRQ(ierr);
ierr = VecDestroy(&epsCi); CHKERRQ(ierr);
ierr = VecDestroy(&epsP); CHKERRQ(ierr);
ierr = VecDestroy(&x); CHKERRQ(ierr);
ierr = VecDestroy(&vgradlocal);CHKERRQ(ierr);
ierr = VecDestroy(&tmp); CHKERRQ(ierr);
ierr = VecDestroy(&tmpa); CHKERRQ(ierr);
ierr = VecDestroy(&tmpb); CHKERRQ(ierr);
ierr = MatDestroy(&A); CHKERRQ(ierr);
ierr = MatDestroy(&D); CHKERRQ(ierr);
ierr = MatDestroy(&M); CHKERRQ(ierr);
ierr = VecDestroy(&epscoefone); CHKERRQ(ierr);
ierr = VecDestroy(&epscoeftwo); CHKERRQ(ierr);
ierr = KSPDestroy(&kspone);CHKERRQ(ierr);
ierr = KSPDestroy(&ksptwo);CHKERRQ(ierr);
ISDestroy(&from);
ISDestroy(&to);
if (withepsinldos)
{ierr=VecDestroy(&pickposvec); CHKERRQ(ierr);}
if (lrzsqr)
{
ierr=VecDestroy(&epsFReal); CHKERRQ(ierr);
ierr=VecDestroy(&xsqr); CHKERRQ(ierr);
ierr=VecDestroy(&y); CHKERRQ(ierr);
ierr=VecDestroy(&nb); CHKERRQ(ierr);
ierr=MatDestroy(&C); CHKERRQ(ierr);
}
ierr = VecDestroy(&bone); CHKERRQ(ierr);
ierr = VecDestroy(&btwo); CHKERRQ(ierr);
ierr = VecDestroy(&Jtwo); CHKERRQ(ierr);
/*------------ finalize the program -------------*/
{
int rank;
MPI_Comm_rank(PETSC_COMM_WORLD, &rank);
//if (rank == 0) fgetc(stdin);
MPI_Barrier(PETSC_COMM_WORLD);
}
ierr = PetscFinalize(); CHKERRQ(ierr);
return 0;
}
nlopt_result
NLOPT_STDCALL nlopt_minimize_econstrained(
nlopt_algorithm algorithm,
int n, nlopt_func_old f, void *f_data,
int m, nlopt_func_old fc, void *fc_data_, ptrdiff_t fc_datum_size,
int p, nlopt_func_old h, void *h_data_, ptrdiff_t h_datum_size,
const double *lb, const double *ub, /* bounds */
double *x, /* in: initial guess, out: minimizer */
double *minf, /* out: minimum */
double minf_max, double ftol_rel, double ftol_abs,
double xtol_rel, const double *xtol_abs,
double htol_rel, double htol_abs,
int maxeval, double maxtime)
{
char *fc_data = (char *) fc_data_;
char *h_data = (char *) h_data_;
nlopt_opt opt;
nlopt_result ret;
int i;
if (n < 0 || m < 0 || p < 0) return NLOPT_INVALID_ARGS;
opt = nlopt_create(algorithm, (unsigned) n);
if (!opt) return NLOPT_INVALID_ARGS;
ret = nlopt_set_min_objective(opt, (nlopt_func) f, f_data);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
for (i = 0; i < m; ++i) {
ret = nlopt_add_inequality_constraint(opt, (nlopt_func) fc,
fc_data + i*fc_datum_size,
0.0);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
}
(void) htol_rel; /* unused */
for (i = 0; i < p; ++i) {
ret = nlopt_add_equality_constraint(opt, (nlopt_func) h,
h_data + i*h_datum_size,
htol_abs);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
}
ret = nlopt_set_lower_bounds(opt, lb);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_upper_bounds(opt, ub);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_stopval(opt, minf_max);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_ftol_rel(opt, ftol_rel);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_ftol_abs(opt, ftol_abs);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_xtol_rel(opt, xtol_rel);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_xtol_abs(opt, xtol_abs);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_maxeval(opt, maxeval);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_set_maxtime(opt, maxtime);
if (ret != NLOPT_SUCCESS) { nlopt_destroy(opt); return ret; }
ret = nlopt_optimize(opt, x, minf);
nlopt_destroy(opt);
return ret;
}
void
FitOrientation(
const int NrOfFiles,
const int nLayers,
const double ExcludePoleAngle,
double Lsd[nLayers],
const long long int SizeObsSpots,
double TiltsOrig[3],
const double OmegaStart,
const double OmegaStep,
const double px,
double ybc[nLayers],
double zbc[nLayers],
const double gs,
double SpotsInfo[200][9],
int nSpots,
double OmegaRanges[MAX_N_OMEGA_RANGES][2],
const int NoOfOmegaRanges,
double BoxSizes[MAX_N_OMEGA_RANGES][4],
double P0[nLayers][3],
const int NrPixelsGrid,
int *ObsSpotsInfo,
double tol,
double hkls[5000][4],
double Thetas[5000],
int n_hkls,
double **SpotsOut,
double *LsdFit,
double *TiltsFit,
double **BCsFit,
double tolLsd,
double tolLsdRel,
double tolTilts,
double tolBCsa,
double tolBCsb)
{
unsigned n;
long int i,j;
n = 3+(nLayers*3)+(nSpots*3);
double x[n],xl[n],xu[n];
for (i=0;i<n;i++){
x[i] = 0;
xl[i] = 0;
xu[i] = 0;
}
int count = 0;
for (i=0;i<3;i++)
{
x[i] = TiltsOrig[count];
xl[i] = x[i] - tolTilts;
xu[i] = x[i] + tolTilts;
count++;
}
count = 0;
x[3] = Lsd[0];
xl[3] = x[3] - tolLsd;
xu[3] = x[3] + tolLsd;
count++;
for (i=4;i<nLayers+3;i++)
{
x[i] = Lsd[count] - Lsd[count-1];
xl[i] = x[i] - tolLsdRel;
xu[i] = x[i] + tolLsdRel;
count++;
}
count = 0;
for (i=3+nLayers;i<3+(nLayers*2);i++)
{
x[i] = ybc[count];
x[i+nLayers] = zbc[count];
xl[i] = x[i] - tolBCsa;
xl[i+nLayers] = x[i+nLayers] - tolBCsb;
xu[i] = x[i] + tolBCsa;
xu[i+nLayers] = x[i+nLayers] + tolBCsb;
count++;
}
count = 0;
int ps;
for( i=0; i<nSpots; i++)
{
for (j=0;j<3;j++){
ps = i*3+j+3+(nLayers*3);
x[ps] = SpotsInfo[i][6+j];
xl[ps] = x[ps] - (tol*M_PI/180);
xu[ps] = x[ps] + (tol*M_PI/180);
}
}
//for (i=0;i<n;i++) printf("%f %f %f\n",x[i],xl[i],xu[i]);
struct my_func_data f_data;
f_data.NrOfFiles = NrOfFiles;
f_data.nLayers = nLayers;
f_data.n_hkls = n_hkls;
for (i=0;i<5000;i++){
f_data.hkls[i][0] = hkls[i][0];
f_data.hkls[i][1] = hkls[i][1];
f_data.hkls[i][2] = hkls[i][2];
f_data.hkls[i][3] = hkls[i][3];
f_data.Thetas[i] = Thetas[i];
}
f_data.ExcludePoleAngle = ExcludePoleAngle;
f_data.SizeObsSpots = SizeObsSpots;
f_data.P0 = allocMatrixF(nLayers,3);
for (i=0;i<3;i++){
for (j=0;j<nSpots;j++){
f_data.XGrain[j][i] = SpotsInfo[j][2*i];
f_data.YGrain[j][i] = SpotsInfo[j][2*i+1];
}
for (j=0;j<nLayers;j++){
f_data.P0[j][i] = P0[j][i];
}
}
for (i=0;i<MAX_N_OMEGA_RANGES;i++){
for (j=0;j<2;j++){
f_data.OmegaRanges[i][j] = OmegaRanges[i][j];
}
for (j=0;j<4;j++){
f_data.BoxSizes[i][j] = BoxSizes[i][j];
}
}
f_data.ObsSpotsInfo = &ObsSpotsInfo[0];
f_data.OmegaStart = OmegaStart;
f_data.OmegaStep = OmegaStep;
f_data.px = px;
f_data.gs = gs;
f_data.nSpots = nSpots;
f_data.NoOfOmegaRanges = NoOfOmegaRanges;
f_data.NrPixelsGrid = NrPixelsGrid;
struct my_func_data *f_datat;
f_datat = &f_data;
void* trp = (struct my_func_data *) f_datat;
double tole = 1e-3;
nlopt_opt opt;
opt = nlopt_create(NLOPT_LN_NELDERMEAD, n);
nlopt_set_lower_bounds(opt, xl);
nlopt_set_upper_bounds(opt, xu);
nlopt_set_min_objective(opt, problem_function, trp);
double minf=1;
nlopt_optimize(opt, x, &minf);
nlopt_destroy(opt);
TiltsFit[0] = x[0];
TiltsFit[1] = x[1];
TiltsFit[2] = x[2];
LsdFit[0] = x[3];
for (i=1;i<nLayers;i++){
LsdFit[i] = LsdFit[i-1] + x[3+i];
}
for (i=0;i<nLayers;i++){
BCsFit[i][0] = x[3+nLayers+i];
BCsFit[i][1] = x[3+nLayers+nLayers+i];
}
for (i=0;i<nSpots;i++){
for (j=0;j<3;j++){
ps = i*3+j+3+(nLayers*3);
SpotsOut[i][j] = x[ps];
}
SpotsOut[i][3] = IndividualResults[i];
}
}
/********************************************************************
* nlopt main function
* *****************************************************************/
SEXP TKF92LikelihoodFunction3DMain_nlopt(SEXP seq1IntR, SEXP seq2IntR,
SEXP expectedLength, SEXP probMatR, SEXP eqFrequenciesR,
SEXP method){
int ncol, nrow;
ncol = INTEGER(GET_DIM(probMatR))[1];
nrow = INTEGER(GET_DIM(probMatR))[0];
int i, j;
// probMat
gsl_matrix *probMat = gsl_matrix_alloc(nrow, ncol);
for(i = 0; i < nrow; i++)
for(j = 0; j < ncol; j++)
gsl_matrix_set(probMat, i, j, REAL(probMatR)[i+j*ncol]);
// eqFrequenciesR
gsl_vector *eqFrequencies = gsl_vector_alloc(GET_LENGTH(eqFrequenciesR));
for(i = 0; i < GET_LENGTH(eqFrequenciesR); i++){
gsl_vector_set(eqFrequencies, i, REAL(eqFrequenciesR)[i]);
}
// seqInt preparation
int *seq1Int, *seq2Int;
seq1Int = (int *) R_alloc(GET_LENGTH(seq1IntR), sizeof(int));
seq2Int = (int *) R_alloc(GET_LENGTH(seq2IntR), sizeof(int));
for(i = 0; i < GET_LENGTH(seq1IntR); i++){
seq1Int[i] = INTEGER(seq1IntR)[i];
}
for(i = 0; i < GET_LENGTH(seq2IntR); i++){
seq2Int[i] = INTEGER(seq2IntR)[i];
}
// construct params
struct TKF92LikelihoodFunction3D_params params;
params.len = REAL(expectedLength)[0];
params.substModel = probMat;
params.eqFrequencies = eqFrequencies;
params.seq1Int = seq1Int;
params.seq2Int = seq2Int;
params.SA = GET_LENGTH(seq1IntR);
params.SB = GET_LENGTH(seq2IntR);
// nlopt main procedure
double lb[3] = {0.0494497, 1e-20, 1e-20}; // lower bounds
double ub[3] = {2000, 0.1, 1-1e-20}; // upper bounds
//double dx[3] = {20, 0.01, 0.1}; // The initial step size
nlopt_opt opt;
if(strcmp(CHAR(STRING_ELT(method, 0)), "NM") == 0){
opt = nlopt_create(NLOPT_LN_NELDERMEAD, 3); /* algorithm and dimensionality */
}else if(strcmp(CHAR(STRING_ELT(method, 0)), "Sbplx") == 0){
opt = nlopt_create(NLOPT_LN_SBPLX, 3);
}else if(strcmp(CHAR(STRING_ELT(method, 0)), "COBYLA") == 0){
opt = nlopt_create(NLOPT_LN_COBYLA, 3);
}else if(strcmp(CHAR(STRING_ELT(method, 0)), "BOBYQA") == 0){
opt = nlopt_create(NLOPT_LN_BOBYQA, 3);
}else if(strcmp(CHAR(STRING_ELT(method, 0)), "PRAXIS") == 0){
opt = nlopt_create(NLOPT_LN_PRAXIS, 3);
}else{
error("Wrong optimisation method!");
}
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, TKF92LikelihoodFunction3D_nlopt, ¶ms);
nlopt_set_ftol_rel(opt, F_TOL); // stopping criteria
//nlopt_set_initial_step(opt, dx); // initial step size
nlopt_set_maxeval(opt, MAX_ITER);
double x[3] = {100, exp(-3), 0.5}; /* some initial guess */
double minf; /* the minimum objective value, upon return */
if (nlopt_optimize(opt, x, &minf) < 0) {
Rprintf("nlopt failed!\n");
}else{
Rprintf("found minimum at f(%g,%g,%g) = %0.10g using %s algorithm\n",
x[0], x[1], x[2], minf, CHAR(STRING_ELT(method, 0)));
}
SEXP ans, ansNames;
PROTECT(ans = NEW_NUMERIC(4)); // a vector of distance, mu, r and the negative log likelihood
PROTECT(ansNames = NEW_CHARACTER(4));
REAL(ans)[0] = x[0];
REAL(ans)[1] = x[1];
REAL(ans)[2] = x[2];
REAL(ans)[3] = minf;
SET_STRING_ELT(ansNames, 0, mkChar("PAM"));
SET_STRING_ELT(ansNames, 1, mkChar("Mu"));
SET_STRING_ELT(ansNames, 2, mkChar("r"));
SET_STRING_ELT(ansNames, 3, mkChar("negLogLikelihood"));
SET_NAMES(ans, ansNames);
// free everything
nlopt_destroy(opt);
gsl_vector_free(eqFrequencies);
gsl_matrix_free(probMat);
UNPROTECT(2);
return ans;
}
double ColorLines::findMagnitude(const Mat *img, Mat *alpha_mat, double a[3])
{
int w=img->cols;
int h=img->rows;
int t=img->type();
int c;
if(img->type()==CV_8UC3){
c=3;
} else if(img->type()==CV_8UC1){
c=1;
}
uchar *p_data=img->data;
uchar *alpha_data=alpha_mat->data;
//cout << *alpha_mat << endl;
double img_div[h*w*c];
double *alpha=(double*)malloc(h*w*sizeof(double));
for(int i=0; i<h; i++){
for(int j=0; j<w; j++){
alpha[i*w+j]=(double)alpha_data[w*i+j]/255.0l;
for(int k=0; k<c; k++){
img_div[c*(w*i+j)+k]=(double(p_data[c*(w*i+j)+k])/255.0l)/a[k];
}
}
}
double *withoutA = (double*)malloc(h*w*c*sizeof(double));
double temp;
for(int i=0; i<h; i++){
for(int j=0; j<w; j++){
for(int k=0; k<c; k++){
temp=(double(p_data[c*(w*i+j)+k])/255.0l)-alpha[w*i+j]*a[k];
if(temp>0){
withoutA[c*(w*i+j)+k]=temp;
} else{
withoutA[c*(w*i+j)+k]=0;
}
}
}
}
double *gray=(double*)malloc(w*h*sizeof(double));
double initMag=0.5;
bool isNegative=true;
while(isNegative){
initMag+=0.1;
isNegative=false;
for(int i=0; i<h; i++){
for(int j=0; j<w; j++){
gray[w*i+j]=0;
for(int k=0; k<c; k++){
temp=withoutA[c*(w*i+j)+k]/(1-alpha[w*i+j]/initMag);
isNegative=temp<0;
gray[w*i+j]+=temp*temp;
}
gray[w*i+j]=sqrt(gray[w*i+j]);
}
}
}
double *transmission=(double*)malloc(w*h*sizeof(double));
for(int i=0; i<w*h; i++){
transmission[i]=1-alpha[i]/initMag;
}
double alpha_min=transmission[0];
double alpha_max=transmission[0];
for(int i=1; i<w*h; i++){
if(transmission[i]>alpha_max){
alpha_max=transmission[i];
} else if(transmission[i]<alpha_min){
alpha_min=transmission[i];
}
}
int numBins=50;
double binW=(alpha_max-alpha_min)/(double)numBins;
double mtrans[numBins+1];
double mshading[numBins+1];
mtrans[0]=alpha_min;
mshading[0]=0;
mtrans[numBins]=alpha_max;
for(int i=1; i<numBins; i++){
mtrans[i]=mtrans[i-1]+binW;
mshading[i]=0;
}
double val;
double *inBin=(double*)malloc(w*h*sizeof(double));
int ind;
for(int i=0; i<=numBins; i++){
ind=0;
val=mtrans[i]+binW/2.0;
for(int j=0; j<w*h; j++){
if(transmission[j]<val+binW/2.0 && transmission[j]>=val-binW/2.0){
inBin[ind]=gray[j];
ind++;
}
}
if(ind>100){
qsort(inBin, ind, sizeof(double), comp);
mshading[i]=inBin[(int)(0.995*ind+0.5)-1];
}
}
double ak[2];
ak[0]=1;
ak[1]=1;
struct_fitError entrada;
entrada.withoutA=withoutA;
entrada.alpha=alpha;
entrada.mshading=mshading;
entrada.h=w;
entrada.w=h;
entrada.c=c;
entrada.numBins=numBins;
entrada.initMag=initMag;
cout << " OPTIMIZATION " << endl;
nlopt_opt opt;
//algoritmos de minimização, nao sei qual e melhor..
opt = nlopt_create(NLOPT_GN_DIRECT_L, 2);
//opt = nlopt_create(NLOPT_GN_DIRECT, 2);
//opt = nlopt_create(NLOPT_GN_CRS2_LM, 2);
//opt = nlopt_create(NLOPT_GD_STOGO, 2);
//opt = nlopt_create( NLOPT_GD_STOGO_RAND, 2);
//opt = nlopt_create(NLOPT_GN_ISRES, 2);
//opt = nlopt_create(NLOPT_GN_ESCH, 2);
//valores maximos e minimos do espaço de busca, nao sei se 0 e 1 sao valores bons
double lb[2]={0,0};
double ub[2]={1,1};
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, fitError, &entrada);
//acho que isso esta relacionado com a precisao, se aumentar o resultado fica ruim, se diminuir muito nao converge nunca
nlopt_set_xtol_rel(opt, 1e-1);
//numero maximo de iterações, pode ser que precise aumentar
nlopt_set_maxeval(opt, 500);
double minf;
if (nlopt_optimize(opt, ak, &minf) < 0) {
printf("nlopt failed!\n");
}
double mag=initMag/ak[0];
free(alpha);
free(gray);
free(inBin);
free(transmission);
//printf("resultado final: %f %f %f\n", ak[0], ak[1], mag);
return mag;
}
void Fit2DPeaks(unsigned nPeaks, int NrPixelsThisRegion, double *z, int **UsefulPixels, double *MaximaValues,
int **MaximaPositions, double *IntegratedIntensity, double *IMAX, double *YCEN, double *ZCEN,
double *RCens, double *EtaCens,double Ycen, double Zcen, double Thresh, int *NrPx,double *OtherInfo)
{
unsigned n = 1 + (8*nPeaks);
double x[n],xl[n],xu[n];
x[0] = Thresh/2;
xl[0] = 0;
xu[0] = Thresh;
int i;
double *Rs, *Etas;
Rs = malloc(NrPixelsThisRegion*2*sizeof(*Rs));
Etas = malloc(NrPixelsThisRegion*2*sizeof(*Etas));
for (i=0;i<NrPixelsThisRegion;i++){
Rs[i] = CalcNorm2(UsefulPixels[i][0]-Ycen,UsefulPixels[i][1]-Zcen);
Etas[i] = CalcEtaAngle(UsefulPixels[i][0]-Ycen,UsefulPixels[i][1]-Zcen);
}
double Width = sqrt(NrPixelsThisRegion/nPeaks);
for (i=0;i<nPeaks;i++){
x[(8*i)+1] = MaximaValues[i]; // Imax
x[(8*i)+2] = CalcNorm2(MaximaPositions[i][0]-Ycen,MaximaPositions[i][1]-Zcen); //Radius
x[(8*i)+3] = CalcEtaAngle(MaximaPositions[i][0]-Ycen,MaximaPositions[i][1]-Zcen); // Eta
x[(8*i)+4] = 0.5; // Mu
x[(8*i)+5] = Width; //SigmaGR
x[(8*i)+6] = Width; //SigmaLR
x[(8*i)+7] = atand(Width/x[(8*i)+2]); //SigmaGEta //0.5;
x[(8*i)+8] = atand(Width/x[(8*i)+2]); //SigmaLEta //0.5;
double dEta = rad2deg*atan(1/x[(8*i)+2]);
xl[(8*i)+1] = MaximaValues[i]/2;
xl[(8*i)+2] = x[(8*i)+2] - 1;
xl[(8*i)+3] = x[(8*i)+3] - dEta;
xl[(8*i)+4] = 0;
xl[(8*i)+5] = 0.01;
xl[(8*i)+6] = 0.01;
xl[(8*i)+7] = 0.005;
xl[(8*i)+8] = 0.005;
xu[(8*i)+1] = MaximaValues[i]*2;
xu[(8*i)+2] = x[(8*i)+2] + 1;
xu[(8*i)+3] = x[(8*i)+3] + dEta;
xu[(8*i)+4] = 1;
xu[(8*i)+5] = 30;
xu[(8*i)+6] = 30;
xu[(8*i)+7] = 2;
xu[(8*i)+8] = 2;
}
struct func_data f_data;
f_data.NrPixels = NrPixelsThisRegion;
f_data.Rs = &Rs[0];
f_data.Etas = &Etas[0];
f_data.z = &z[0];
struct func_data *f_datat;
f_datat = &f_data;
void *trp = (struct func_data *) f_datat;
nlopt_opt opt;
opt = nlopt_create(NLOPT_LN_NELDERMEAD, n);
nlopt_set_lower_bounds(opt, xl);
nlopt_set_upper_bounds(opt, xu);
nlopt_set_maxtime(opt, 300);
nlopt_set_min_objective(opt, problem_function, trp);
double minf;
nlopt_optimize(opt, x, &minf);
nlopt_destroy(opt);
for (i=0;i<nPeaks;i++){
IMAX[i] = x[(8*i)+1];
RCens[i] = x[(8*i)+2];
EtaCens[i] = x[(8*i)+3];
if (x[(8*i)+5] > x[(8*i)+6]){
OtherInfo[2*i] = x[(8*i)+5];
}else{
OtherInfo[2*i] = x[(8*i)+6];
}
if (x[(8*i)+7] > x[(8*i)+8]){
OtherInfo[2*i+1] = x[(8*i)+7];
}else{
OtherInfo[2*i+1] = x[(8*i)+8];
}
}
YZ4mREta(nPeaks,RCens,EtaCens,YCEN,ZCEN);
CalcIntegratedIntensity(nPeaks,x,Rs,Etas,NrPixelsThisRegion,IntegratedIntensity,NrPx);
free(Rs);
free(Etas);
}
int main(int argc, char *argv[])
{
double XTOL = -1; /* to be set by "user" */
int NHITS = -1;
int c;
while ((c = getopt(argc, argv, "N:t:")) != -1)
switch (c) {
case 'N':
NHITS = atoi(optarg);
break;
case 't':
XTOL = atof(optarg);
break;
case '?':
if (optopt == 'N' || optopt == 't')
fprintf(stderr, "Option -%c requires argument.\n", optopt);
else
fprintf(stderr, "unknown option -%c\n", optopt);
return 1;
default:
;
}
if (XTOL < 0 || NHITS < 0) {
fprintf(stderr,
"please specify NHITS and XTOL with -N and -t\n");
return 1;
}
/* geometry like SNO+'s (as close to 9,000 PMTS as possible) */
int NTHETA = 67;
int NPHI = 134;
struct pmtmap pmtmap;
pmtmap.N = NPHI*NTHETA;
pmtmap.nphi = NPHI;
pmtmap.ntheta = NTHETA;
struct event e1;
struct pos_data data;
data.p = &pmtmap;
data.e = &e1;
init_random();
init_pmtmap(&data);
make_event(&e1, NHITS);
fill_pmt_info(&data);
nlopt_opt opt;
opt = nlopt_create(NLOPT_GN_ISRES, 3);
double lb[3] = {-6, -6, -6};
double ub[3] = {6, 6, 6};
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, mf_p, &data);
double tols[3] = {XTOL, XTOL, XTOL};
nlopt_set_xtol_abs(opt, tols);
nlopt_set_maxtime(opt, 10.0); /* unstick this */
nlopt_set_maxeval(opt, 4e5); /* if timing doesn't unstick it*/
nlopt_add_inequality_constraint(opt, radius_check, &data, 1e-10);
double x[3] = {0, 0, 0};
double fval = mf_p(3, x, NULL, &data);
nlopt_result ret;
ret = nlopt_optimize(opt, x, &fval);
if (ret > 0)
printf("%g %g %g\n", x[0] - e1.spawn_pos[0],
x[1] - e1.spawn_pos[1],
x[2] - e1.spawn_pos[2]);
else
fprintf(stderr, "optimizing failed with code %d\n", ret);
return 0;
}
void omxInvokeNLOPT(double *est, GradientOptimizerContext &goc)
{
goc.optName = "SLSQP";
goc.setupSimpleBounds();
goc.useGradient = true;
FitContext *fc = goc.fc;
int oldWanted = fc->wanted;
fc->wanted = 0;
omxState *globalState = fc->state;
nlopt_opt opt = nlopt_create(NLOPT_LD_SLSQP, fc->numParam);
goc.extraData = opt;
//local_opt = nlopt_create(NLOPT_LD_SLSQP, n); // Subsidiary algorithm
//nlopt_set_local_optimizer(opt, local_opt);
nlopt_set_lower_bounds(opt, goc.solLB.data());
nlopt_set_upper_bounds(opt, goc.solUB.data());
int eq, ieq;
globalState->countNonlinearConstraints(eq, ieq);
if (fc->CI) {
nlopt_set_xtol_rel(opt, 5e-3);
std::vector<double> tol(fc->numParam, std::numeric_limits<double>::epsilon());
nlopt_set_xtol_abs(opt, tol.data());
} else {
// The *2 is there to roughly equate accuracy with NPSOL.
nlopt_set_ftol_rel(opt, goc.ControlTolerance * 2);
nlopt_set_ftol_abs(opt, std::numeric_limits<double>::epsilon());
}
nlopt_set_min_objective(opt, SLSQP::nloptObjectiveFunction, &goc);
double feasibilityTolerance = Global->feasibilityTolerance;
SLSQP::context ctx(goc);
if (eq + ieq) {
ctx.origeq = eq;
if (ieq > 0){
goc.inequality.resize(ieq);
std::vector<double> tol(ieq, feasibilityTolerance);
nlopt_add_inequality_mconstraint(opt, ieq, SLSQP::nloptInequalityFunction, &goc, tol.data());
}
if (eq > 0){
goc.equality.resize(eq);
std::vector<double> tol(eq, feasibilityTolerance);
nlopt_add_equality_mconstraint(opt, eq, SLSQP::nloptEqualityFunction, &ctx, tol.data());
}
}
int priorIterations = fc->iterations;
int code = nlopt_optimize(opt, est, &fc->fit);
if (ctx.eqredundent) {
nlopt_remove_equality_constraints(opt);
eq -= ctx.eqredundent;
std::vector<double> tol(eq, feasibilityTolerance);
nlopt_add_equality_mconstraint(opt, eq, SLSQP::nloptEqualityFunction, &ctx, tol.data());
code = nlopt_optimize(opt, est, &fc->fit);
}
if (goc.verbose >= 2) mxLog("nlopt_optimize returned %d", code);
nlopt_destroy(opt);
fc->wanted = oldWanted;
if (code == NLOPT_INVALID_ARGS) {
Rf_error("NLOPT invoked with invalid arguments");
} else if (code == NLOPT_OUT_OF_MEMORY) {
Rf_error("NLOPT ran out of memory");
} else if (code == NLOPT_FORCED_STOP) {
if (fc->iterations - priorIterations <= 1) {
goc.informOut = INFORM_STARTING_VALUES_INFEASIBLE;
} else {
goc.informOut = INFORM_ITERATION_LIMIT;
}
} else if (code == NLOPT_ROUNDOFF_LIMITED) {
if (fc->iterations - priorIterations <= 2) {
Rf_error("%s: Failed due to singular matrix E or C in LSQ subproblem or "
"rank-deficient equality constraint subproblem or "
"positive directional derivative in line search", goc.optName);
} else {
goc.informOut = INFORM_NOT_AT_OPTIMUM; // is this correct? TODO
}
} else if (code < 0) {
Rf_error("NLOPT fatal error %d", code);
} else if (code == NLOPT_MAXEVAL_REACHED) {
goc.informOut = INFORM_ITERATION_LIMIT;
} else {
goc.informOut = INFORM_CONVERGED_OPTIMUM;
}
}
int CNLopt::run(double (*error_func)(unsigned int nParams, const double* params, double* grad, void* misc))
{
// Create a member function pointer
unsigned int n_data = mWorkerThread->GetDataSize();
mOpt = nlopt_create(mAlgorithm, mNParams);
// xopt = new double [mNParams];
lb = new double [mNParams];
ub = new double [mNParams];
// Copy out the initial values for the parameters:
CModelListPtr model_list = mWorkerThread->GetModelList();
model_list->GetFreeParameters(mParams, mNParams, false);
vector<string> names = model_list->GetFreeParamNames();
vector< pair<double, double> > min_max = model_list->GetFreeParamMinMaxes();
// Init parameter values
for(int i = 0; i < mNParams; i++)
{
lb[i] = min_max[i].first;
ub[i] = min_max[i].second;
// xopt = mParams[i];
}
nlopt_set_lower_bounds(mOpt,lb);
nlopt_set_upper_bounds(mOpt,ub);
nlopt_set_ftol_rel(mOpt, 1e-4); // stopping criterion = when chi2 changes by less than 0.1%
nlopt_set_min_objective(mOpt, error_func, (void*)this);
int major=0, minor=0, bugfix=0;
nlopt_version(&major, &minor, &bugfix);
printf("Starting NLopt version %d.%d.%d\n", major, minor, bugfix);
printf("Algorithm = %s \n", nlopt_algorithm_name(mAlgorithm));
if(mAlgorithm == NLOPT_G_MLSL_LDS) // set local optimizer to be used with a global search
{
printf("Secondary Algorithm = %s \n", nlopt_algorithm_name(mAlgorithmSecondary));
mOptSecondary = nlopt_create(mAlgorithmSecondary, mNParams);
nlopt_set_lower_bounds(mOptSecondary,lb);
nlopt_set_upper_bounds(mOptSecondary,ub);
nlopt_set_ftol_rel(mOptSecondary, 1e-4); // stopping criterion = when chi2 changes by less than 0.1%
nlopt_set_min_objective(mOptSecondary, error_func, (void*)this);
nlopt_set_local_optimizer(mOpt, mOptSecondary);
}
mIsRunning = true;
mEvals = 0;
double minf;
// Call NLopt. Note, the results are saved in mParams upon completion.
nlopt_result result = nlopt_optimize(mOpt, mParams, &minf);
mIsRunning = false;
printresult(mParams, mNParams, n_data, names, minf, result);
delete(lb);
delete(ub);
nlopt_destroy(mOpt);
if(mAlgorithm == NLOPT_G_MLSL_LDS) // also destroy local optimizer
{
nlopt_destroy(mOptSecondary);
}
return mEvals;
}
void minim_nlopt(density_t *ndft){
nlopt_opt opt;
double minf;
int i, status;
double *x;
nlopt_function_data function_data;
nlopt_par par;
x = (double *)malloc(ipf.npar*sizeof(double));
for(i = 0; i < ipf.npar; i++) x[i] = gsl_vector_get(ipf.gamma, i);
/* Here we choose the minimization method from NLOPT (check the
avaible algorithms at
http://ab-initio.mit.edu/wiki/index.php/NLopt_Algorithms)
and specify the dimension of the problem */
par.algorithm = 1; parse_int("nlopt_algorithm", &par.algorithm);
switch(par.algorithm){
case 1 :
opt = nlopt_create(NLOPT_LN_BOBYQA, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_LN_BOBYQA));
break;
case 2 :
opt = nlopt_create(NLOPT_GN_DIRECT, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_GN_DIRECT));
break;
case 3 :
opt = nlopt_create(NLOPT_GD_STOGO, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_GD_STOGO));
break;
case 4:
opt = nlopt_create(NLOPT_GN_ESCH, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_GN_ESCH));
break;
default :
if(myid == 0) printf("\n\nWARNING: wrong choice for the NLOPT algorithm\nTHe optimization will start with the default algorithm:");
opt = nlopt_create(NLOPT_GN_DIRECT_L, ipf.npar);
if(myid == 0) printf("\n%s", nlopt_algorithm_name(NLOPT_GN_DIRECT_L));
break;
}
nlopt_set_min_objective(opt, nlopt_gfunction, &function_data);
par.rel_tol = 1e-4; parse_double("nlopt_rel_tol", &par.rel_tol);
nlopt_set_xtol_rel(opt, par.rel_tol);
/* Set the lower and upper bounds of the optimization
to a single constant lb or ub respectively */
par.lb = -2.0; parse_double("nlopt_lb", &par.lb);
par.ub = 2.0; parse_double("nlopt_ub", &par.ub);
nlopt_set_lower_bounds1(opt, par.lb);
nlopt_set_upper_bounds1(opt, par.ub);
function_data.counter = 0;
function_data.ndft = density_get_val(ndft);
messages_basic("\n\n\nStarting the optimization.\n\n\n");
if ((status = nlopt_optimize(opt, x, &minf)) < 0){
if (myid == 0) printf("nlopt failed! status = %d\n", status);
parallel_end(EXIT_FAILURE);
}
if(myid == 0) printf("Success. status = %d, iterations = %d, minf = %.12lg\n", status, function_data.counter, minf);
if(myid == 0) {for(i = 0; i < ipf.npar; i++) printf("%.5f ", x[i]);}
nlopt_destroy(opt);
for(i = 0; i < ipf.npar; i++) gsl_vector_set(ipf.gamma, i, x[i]);
ipf_write(ipf, ipf_ref, "pot");
parallel_end(EXIT_SUCCESS);
}
double Optimize_Torsion_Parameters(void)
{
double lb[N_TOR_PARA] = {
-20.0, -PI,
-20.0, -PI,
-20.0, -PI,
-20.0, -PI,
-20.0, -PI,
-100 };
double ub[N_TOR_PARA] = {
+20.0, +PI,
+20.0, +PI,
+20.0, +PI,
+20.0, +PI,
+20.0, +PI,
+100 };
// double ub[N_TOR_PARA] = { 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 100.0 }; /* lower bounds */
nlopt_opt opt;
double Chi_SQ;
int i, j;
Chi_SQ_Min = 1.0E100;
for(i=0; i<NRUN; i++) { // was 32
ActiveRun = i;
Chi_SQ_Min_Local[i] = 1.0E200;
FailCount = Iteration = 0;
// for(j=0; j<5; j++) {
// Para_Tor[2*j] = 0.1+1.0*rand(iseed);
// }
for( i=0; i<11; i++ ) {
Para_Tor[i] = 0.;
IsPara_Fixed[i] = 0.;
} // inital values
//opt = nlopt_create(NLOPT_LD_LBFGS, N_TOR_PARA);
printf("=== Fitting ===\n" );
opt = nlopt_create(NLOPT_LN_COBYLA, N_TOR_PARA);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-8);
if (nlopt_optimize(opt, Para_Tor, &Chi_SQ) < 0) {
printf("nlopt didn't converge %lf %lf\n Please check carefully the rotamer results\n",Chi_SQ_Min, Chi_SQ);
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
nlopt_destroy(opt);
}
memcpy(Para_Tor, Para_Best, sizeof(double)*N_TOR_PARA);
CalObjectiveFunction_Tor(Para_Tor);
return Chi_SQ_Min;
}
void mexFunction(int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[])
{
unsigned n;
double *x, *x0, opt_f;
nlopt_result ret;
mxArray *x_mx, *mx;
user_function_data d, dpre, *dfc = NULL, *dh = NULL;
nlopt_opt opt = NULL;
CHECK(nrhs == 2 && nlhs <= 3, "wrong number of arguments");
/* options = prhs[0] */
CHECK(mxIsStruct(prhs[0]), "opt must be a struct");
/* x0 = prhs[1] */
CHECK(mxIsDouble(prhs[1]) && !mxIsComplex(prhs[1])
&& (mxGetM(prhs[1]) == 1 || mxGetN(prhs[1]) == 1),
"x must be real row or column vector");
n = mxGetM(prhs[1]) * mxGetN(prhs[1]),
x0 = mxGetPr(prhs[1]);
CHECK(opt = make_opt(prhs[0], n), "error initializing nlopt options");
d.neval = 0;
d.verbose = (int) struct_val_default(prhs[0], "verbose", 0);
d.opt = opt;
/* function f = prhs[1] */
mx = struct_funcval(prhs[0], "min_objective");
if (!mx) mx = struct_funcval(prhs[0], "max_objective");
CHECK(mx, "either opt.min_objective or opt.max_objective must exist");
if (mxIsChar(mx)) {
CHECK(mxGetString(mx, d.f, FLEN) == 0,
"error reading function name string (too long?)");
d.nrhs = 1;
d.xrhs = 0;
}
else {
d.prhs[0] = mx;
strcpy(d.f, "feval");
d.nrhs = 2;
d.xrhs = 1;
}
d.prhs[d.xrhs] = mxCreateDoubleMatrix(1, n, mxREAL);
if ((mx = struct_funcval(prhs[0], "pre"))) {
CHECK(mxIsChar(mx) || mxIsFunctionHandle(mx),
"pre must contain function handles or function names");
if (mxIsChar(mx)) {
CHECK(mxGetString(mx, dpre.f, FLEN) == 0,
"error reading function name string (too long?)");
dpre.nrhs = 2;
dpre.xrhs = 0;
}
else {
dpre.prhs[0] = mx;
strcpy(dpre.f, "feval");
dpre.nrhs = 3;
dpre.xrhs = 1;
}
dpre.verbose = d.verbose > 2;
dpre.opt = opt;
dpre.neval = 0;
dpre.prhs[dpre.xrhs] = d.prhs[d.xrhs];
dpre.prhs[d.xrhs+1] = mxCreateDoubleMatrix(1, n, mxREAL);
d.dpre = &dpre;
if (struct_funcval(prhs[0], "min_objective"))
nlopt_set_precond_min_objective(opt, user_function,user_pre,&d);
else
nlopt_set_precond_max_objective(opt, user_function,user_pre,&d);
}
else {
dpre.nrhs = 0;
if (struct_funcval(prhs[0], "min_objective"))
nlopt_set_min_objective(opt, user_function, &d);
else
nlopt_set_max_objective(opt, user_function, &d);
}
if ((mx = mxGetField(prhs[0], 0, "fc"))) {
int j, m;
double *fc_tol;
CHECK(mxIsCell(mx), "fc must be a Cell array");
m = mxGetM(mx) * mxGetN(mx);;
dfc = (user_function_data *) mxCalloc(m, sizeof(user_function_data));
fc_tol = struct_arrval(prhs[0], "fc_tol", m, NULL);
for (j = 0; j < m; ++j) {
mxArray *fc = mxGetCell(mx, j);
CHECK(mxIsChar(fc) || mxIsFunctionHandle(fc),
"fc must contain function handles or function names");
if (mxIsChar(fc)) {
CHECK(mxGetString(fc, dfc[j].f, FLEN) == 0,
"error reading function name string (too long?)");
dfc[j].nrhs = 1;
dfc[j].xrhs = 0;
}
else {
dfc[j].prhs[0] = fc;
strcpy(dfc[j].f, "feval");
dfc[j].nrhs = 2;
dfc[j].xrhs = 1;
}
dfc[j].verbose = d.verbose > 1;
dfc[j].opt = opt;
dfc[j].neval = 0;
dfc[j].prhs[dfc[j].xrhs] = d.prhs[d.xrhs];
CHECK(nlopt_add_inequality_constraint(opt, user_function,
dfc + j,
fc_tol ? fc_tol[j] : 0)
> 0, "nlopt error adding inequality constraint");
}
}
if ((mx = mxGetField(prhs[0], 0, "h"))) {
int j, m;
double *h_tol;
CHECK(mxIsCell(mx), "h must be a Cell array");
m = mxGetM(mx) * mxGetN(mx);;
dh = (user_function_data *) mxCalloc(m, sizeof(user_function_data));
h_tol = struct_arrval(prhs[0], "h_tol", m, NULL);
for (j = 0; j < m; ++j) {
mxArray *h = mxGetCell(mx, j);
CHECK(mxIsChar(h) || mxIsFunctionHandle(h),
"h must contain function handles or function names");
if (mxIsChar(h)) {
CHECK(mxGetString(h, dh[j].f, FLEN) == 0,
"error reading function name string (too long?)");
dh[j].nrhs = 1;
dh[j].xrhs = 0;
}
else {
dh[j].prhs[0] = h;
strcpy(dh[j].f, "feval");
dh[j].nrhs = 2;
dh[j].xrhs = 1;
}
dh[j].verbose = d.verbose > 1;
dh[j].opt = opt;
dh[j].neval = 0;
dh[j].prhs[dh[j].xrhs] = d.prhs[d.xrhs];
CHECK(nlopt_add_equality_constraint(opt, user_function,
dh + j,
h_tol ? h_tol[j] : 0)
> 0, "nlopt error adding equality constraint");
}
}
x_mx = mxCreateDoubleMatrix(mxGetM(prhs[1]), mxGetN(prhs[1]), mxREAL);
x = mxGetPr(x_mx);
memcpy(x, x0, sizeof(double) * n);
ret = nlopt_optimize(opt, x, &opt_f);
mxFree(dh);
mxFree(dfc);
mxDestroyArray(d.prhs[d.xrhs]);
if (dpre.nrhs > 0) mxDestroyArray(dpre.prhs[d.xrhs+1]);
nlopt_destroy(opt);
plhs[0] = x_mx;
if (nlhs > 1) {
plhs[1] = mxCreateDoubleMatrix(1, 1, mxREAL);
*(mxGetPr(plhs[1])) = opt_f;
}
if (nlhs > 2) {
plhs[2] = mxCreateDoubleMatrix(1, 1, mxREAL);
*(mxGetPr(plhs[2])) = (int) ret;
}
}
void
FitOrientation(
const int NrOfFiles,
const int nLayers,
const double ExcludePoleAngle,
double Lsd[nLayers],
const long long int SizeObsSpots,
const double XGrain[3],
const double YGrain[3],
double RotMatTilts[3][3],
const double OmegaStart,
const double OmegaStep,
const double px,
double ybc[nLayers],
double zbc[nLayers],
const double gs,
double OmegaRanges[MAX_N_OMEGA_RANGES][2],
const int NoOfOmegaRanges,
double BoxSizes[MAX_N_OMEGA_RANGES][4],
double P0[nLayers][3],
const int NrPixelsGrid,
int *ObsSpotsInfo,
double EulerIn[3],
double tol,
double *EulerOutA,
double *EulerOutB,
double *EulerOutC,
double *ResultFracOverlap,
double hkls[5000][4],
double Thetas[5000],
int n_hkls)
{
unsigned n;
long int i,j;
n = 3;
double x[n],xl[n],xu[n];
for( i=0; i<n; i++)
{
x[i] = EulerIn[i];
xl[i] = x[i] - (tol*M_PI/180);
xu[i] = x[i] + (tol*M_PI/180);
}
struct my_func_data f_data;
f_data.NrOfFiles = NrOfFiles;
f_data.nLayers = nLayers;
f_data.n_hkls = n_hkls;
for (i=0;i<5000;i++){
f_data.hkls[i][0] = hkls[i][0];
f_data.hkls[i][1] = hkls[i][1];
f_data.hkls[i][2] = hkls[i][2];
f_data.hkls[i][3] = hkls[i][3];
f_data.Thetas[i] = Thetas[i];
}
f_data.ExcludePoleAngle = ExcludePoleAngle;
f_data.SizeObsSpots = SizeObsSpots;
f_data.P0 = allocMatrixF(nLayers,3);
for (i=0;i<3;i++){
f_data.XGrain[i] = XGrain[i];
f_data.YGrain[i] = YGrain[i];
for (j=0;j<nLayers;j++){
f_data.P0[j][i] = P0[j][i];
}
for (j=0;j<3;j++){
f_data.RotMatTilts[i][j] = RotMatTilts[i][j];
}
}
for (i=0;i<MAX_N_OMEGA_RANGES;i++){
for (j=0;j<2;j++){
f_data.OmegaRanges[i][j] = OmegaRanges[i][j];
}
for (j=0;j<4;j++){
f_data.BoxSizes[i][j] = BoxSizes[i][j];
}
}
f_data.ObsSpotsInfo = &ObsSpotsInfo[0];
f_data.Lsd = &Lsd[0];
f_data.ybc = &ybc[0];
f_data.zbc = &zbc[0];
f_data.OmegaStart = OmegaStart;
f_data.OmegaStep = OmegaStep;
f_data.px = px;
f_data.gs = gs;
f_data.NoOfOmegaRanges = NoOfOmegaRanges;
f_data.NrPixelsGrid = NrPixelsGrid;
struct my_func_data *f_datat;
f_datat = &f_data;
void* trp = (struct my_func_data *) f_datat;
double tole = 1e-3;
nlopt_opt opt;
opt = nlopt_create(NLOPT_LN_NELDERMEAD, n);
nlopt_set_lower_bounds(opt, xl);
nlopt_set_upper_bounds(opt, xu);
nlopt_set_min_objective(opt, problem_function, trp);
double minf=1;
nlopt_optimize(opt, x, &minf);
nlopt_destroy(opt);
*ResultFracOverlap = minf;
*EulerOutA = x[0];
*EulerOutB = x[1];
*EulerOutC = x[2];
}
double Optimize_Torsion_Parameters(void)
{
double lb[N_PARA_MAX], ub[N_PARA_MAX];
double Chi_SQ;
int i, j, Pos;
n_Para = 10*n_Phi + 1;
memset(Is_Para_Fixed, 0, sizeof(int)*n_Para);
// memset(lb, 0, sizeof(double)*n_Para);
lb[n_Phi*10] = -HUGE_VAL;
for(i=0; i<n_Phi; i++) {
Pos = 10*i;
for(j=0; j<10; j+=2) { // ten parameters
lb[Pos+j] = -15.0;
ub[Pos+j] = 15.0;
}
for(j=1; j<10; j+=2) { // ten parameters
lb[Pos+j] = -M_PI;
ub[Pos+j] = +M_PI;
}
}
ub[n_Phi*10] = HUGE_VAL;
opt = nlopt_create(NLOPT_LN_COBYLA, n_Para);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-6);
Collect_Torsion_Parameters();
Assign_Torsion_Parameters();
Cal_E_MM_Scaned();
Cal_E_MM_Rotamer();
Para_List[n_Phi*10] = E_Scan_QM_Mean-E_Scan_MM_Mean; // energy shift
E_Shift_0 = fabs(E_Scan_QM_Mean-E_Scan_MM_Mean);
for(i=0; i<n_Phi; i++) {
Pos = 10*i;
for(j=1; j<10; j+=2) { // the phase is fixed
Is_Para_Fixed[Pos+j] = 1;
}
}
Read_Parameters("saved-para.dat");
Chi_SQ_Min = 1.0E100;
memcpy(Para_Best, Para_List, sizeof(double)*n_Para);
Chi_SQ = CalObjectiveFunction(Para_List, 0);
if(ProgID == 0) {
fprintf(fFitting, "Iteration %4d Chi^2 = %.8lf Chi^2(1D) = %.8lf Chi^2(rotamer) = %.8lf\n",
0, Chi_SQ, Chi_SQ_1D, Chi_SQ_Rotamer);
fflush(fFitting);
}
FailCount = 0;
int ret= nlopt_optimize(opt, Para_List, &Chi_SQ);
if (ret < 0) {
printf("nlopt failed! :%d\n", ret);
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
memcpy(Para_List, Para_Best, sizeof(double)*n_Para);
CalObjectiveFunction(Para_List, 1);
nlopt_destroy(opt);
return Chi_SQ_Min;
}
int main(int argc, char *argv[]) {
int opt=0, verb=0;
int max_harm = 64, max_lag=0;
int isub = 1;
while ((opt=getopt(argc,argv,"hvI:H:L:"))!=-1) {
switch (opt) {
case 'v':
verb++;
break;
case 'I':
isub = atoi(optarg);
break;
case 'H':
max_harm = atoi(optarg);
break;
case 'L':
max_lag = atoi(optarg);
break;
case 'h':
usage();
exit(0);
break;
}
}
if (optind==argc) {
usage();
exit(1);
}
int i, rv;
/* Open file */
fitsfile *f;
int status;
fits_open_file(&f, argv[optind], READONLY, &status);
fits_error_check_fatal();
/* Get basic dims */
struct cyclic_work w;
cyclic_load_params(f, &w, &status);
fits_error_check_fatal();
if (verb) {
printf("Read nphase=%d npol=%d nchan=%d\n",
w.nphase, w.npol, w.nchan);
fflush(stdout);
}
int orig_npol = w.npol;
w.npol = 1;
/* Init FFTs */
fftwf_init_threads();
fftwf_plan_with_nthreads(4);
if (verb) { printf("Planning FFTs\n"); fflush(stdout); }
#define WF "/home/pdemores/share/cyclic_wisdom.dat"
FILE *wf = fopen(WF,"r");
if (wf!=NULL) { fftwf_import_wisdom_from_file(wf); fclose(wf); }
rv = cyclic_init_ffts(&w);
if (rv) {
fprintf(stderr, "Error planning ffts (rv=%d)\n", rv);
exit(1);
}
wf = fopen(WF,"w");
if (wf!=NULL) { fftwf_export_wisdom_to_file(wf); fclose(wf); }
/* Alloc some stuff */
struct periodic_spectrum raw;
struct cyclic_spectrum cs, model_cs;
struct filter_time ht;
struct filter_freq hf;
struct profile_phase pp;
struct profile_harm ph;
raw.nphase = pp.nphase = w.nphase;
raw.nchan = cs.nchan = hf.nchan = w.nchan;
cs.nharm = ph.nharm = w.nharm;
ht.nlag = w.nlag;
raw.npol = orig_npol;
cs.npol = 1;
model_cs.nchan = cs.nchan;
model_cs.nharm = cs.nharm;
model_cs.npol = cs.npol;
cyclic_alloc_ps(&raw);
cyclic_alloc_cs(&cs);
cyclic_alloc_cs(&model_cs);
filter_alloc_time(&ht);
filter_alloc_freq(&hf);
profile_alloc_phase(&pp);
profile_alloc_harm(&ph);
#if 0 // XXX not implemented yet
/* Check bounds */
if (max_harm > w.nharm) { max_harm = w.nharm; }
if (max_lag > w.nlag/2) { max_lag = w.nlag/2; }
if (verb) {
printf("Using max of %d harmonics and %d lags\n", max_harm, max_lag);
}
#endif
/* Load data */
cyclic_load_ps(f, &raw, isub, &status);
fits_error_check_fatal();
/* Add polns w/o calibration */
cyclic_pscrunch_ps(&raw, 1.0, 1.0);
/* Initialize H, profile guesses */
cyclic_fscrunch_ps(&pp, &raw);
profile_phase2harm(&pp, &ph, &w);
ht.data[0] = 1.0;
for (i=1; i<ht.nlag; i++) { ht.data[i] = 0.0; }
filter_profile_norm(&ht, &ph, w.nharm);
profile_harm2phase(&ph, &pp, &w);
/* convert input data to cyclic spectrum */
cyclic_ps2cs(&raw, &cs, &w);
/* could output initial profile */
/* Fill in data struct for nlopt */
struct cyclic_data cdata;
cdata.cs = &cs;
cdata.s0 = &ph;
cdata.ht = &ht;
cdata.model_cs = &model_cs;
cdata.w = &w;
/* Set up minimizer */
const int dim = 2*(w.nharm-1) + 2*w.nlag; /* number of free params */
printf("number of fit params = %d\n", dim);
nlopt_opt op;
op = nlopt_create(NLOPT_LN_COBYLA, dim);
nlopt_set_min_objective(op, cyclic_ms_difference_nlopt, &cdata);
nlopt_set_xtol_rel(op, 1e-4);
/* Set up initial params */
double *x = (double *)malloc(sizeof(double) * dim);
double *xtmp = x;
for (i=1; i<ph.nharm; i++) {
xtmp[0] = creal(ph.data[i]);
xtmp[1] = cimag(ph.data[i]);
xtmp += 2;
}
for (i=0; i<ht.nlag; i++) {
xtmp[0] = creal(ht.data[i]);
xtmp[1] = cimag(ht.data[i]);
xtmp += 2;
}
/* Run optimization */
double min;
if (nlopt_optimize(op, x, &min)) {
fprintf(stderr, "nlopt_optimize failed\n");
exit(1);
}
/* TODO: some kind of output */
/* All done :) */
nlopt_destroy(op);
exit(0);
}
void NloptOptimizationSolver<T>::solve ()
{
START_LOG("solve()", "NloptOptimizationSolver");
this->init ();
unsigned int nlopt_size = this->system().solution->size();
// We have to have an objective function
libmesh_assert( this->objective_object );
// Set routine for objective and (optionally) gradient evaluation
{
nlopt_result ierr =
nlopt_set_min_objective(_opt,
__libmesh_nlopt_objective,
this);
if (ierr < 0)
libmesh_error_msg("NLopt failed to set min objective: " << ierr);
}
if (this->lower_and_upper_bounds_object)
{
// Need to actually compute the bounds vectors first
this->lower_and_upper_bounds_object->lower_and_upper_bounds(this->system());
std::vector<Real> nlopt_lb(nlopt_size);
std::vector<Real> nlopt_ub(nlopt_size);
for(unsigned int i=0; i<nlopt_size; i++)
{
nlopt_lb[i] = this->system().get_vector("lower_bounds")(i);
nlopt_ub[i] = this->system().get_vector("upper_bounds")(i);
}
nlopt_set_lower_bounds(_opt, &nlopt_lb[0]);
nlopt_set_upper_bounds(_opt, &nlopt_ub[0]);
}
// If we have an equality constraints object, tell NLopt about it.
if (this->equality_constraints_object)
{
// NLopt requires a vector to specify the tolerance for each constraint.
// NLopt makes a copy of this vector internally, so it's safe for us to
// let it go out of scope.
std::vector<double> equality_constraints_tolerances(this->system().C_eq->size(),
_constraints_tolerance);
// It would be nice to call the C interface directly, at least it should return an error
// code we could parse... unfortunately, there does not seem to be a way to extract
// the underlying nlopt_opt object from the nlopt::opt class!
nlopt_result ierr =
nlopt_add_equality_mconstraint(_opt,
equality_constraints_tolerances.size(),
__libmesh_nlopt_equality_constraints,
this,
&equality_constraints_tolerances[0]);
if (ierr < 0)
libmesh_error_msg("NLopt failed to add equality constraint: " << ierr);
}
// If we have an inequality constraints object, tell NLopt about it.
if (this->inequality_constraints_object)
{
// NLopt requires a vector to specify the tolerance for each constraint
std::vector<double> inequality_constraints_tolerances(this->system().C_ineq->size(),
_constraints_tolerance);
nlopt_add_inequality_mconstraint(_opt,
inequality_constraints_tolerances.size(),
__libmesh_nlopt_inequality_constraints,
this,
&inequality_constraints_tolerances[0]);
}
// Set a relative tolerance on the optimization parameters
nlopt_set_ftol_rel(_opt, this->objective_function_relative_tolerance);
// Set the maximum number of allowed objective function evaluations
nlopt_set_maxeval(_opt, this->max_objective_function_evaluations);
// Reset internal iteration counter
this->_iteration_count = 0;
// Perform the optimization
std::vector<Real> x(nlopt_size);
Real min_val = 0.;
_result = nlopt_optimize(_opt, &x[0], &min_val);
if (_result < 0)
libMesh::out << "NLopt failed!" << std::endl;
else
libMesh::out << "NLopt obtained optimal value: "
<< min_val
<< " in "
<< this->get_iteration_count()
<< " iterations."
<< std::endl;
STOP_LOG("solve()", "NloptOptimizationSolver");
}
double Geoometry_Optimization_With_Constraint(CMol *pMol)
{
return (pMol->Cal_E(0));
nlopt_opt opt, opt_AugLag;
int Return_Opt, nAtom, nDim, i, iPos;
double E_min, x[MAX_NUM_ATOM*3];
Mol_ESP.Restrain_All_Torsions(1); // apply soft restraints on all soft dihedrals
nAtom = pMol->nAtom;
nDim = 3 * nAtom;
printf("\nMM before:\t");
for(i=0; i<n_Phi; i++) {
printf("%3d %3d %3d %3d %8.4lf\n", DihList[i][0], DihList[i][1], DihList[i][2], DihList[i][3],
Mol_ESP.Query_Dihedral(DihList[i][0], DihList[i][1], DihList[i][2], DihList[i][3], 0, NULL));
}
double AUG_LAG_ICM_TOL = 1.0E-17;
opt_AugLag = nlopt_create(NLOPT_LD_LBFGS_GEO, nDim);
nlopt_set_min_objective(opt_AugLag, func_Geo_Opt_Constraint, pMol);
// pMol->SavePdb("opt-free.pdb");
for(i=0; i<pMol->nBond_Fixed; i++) {
int ret=0;
pMol->Geo_Fix_r0[i].pMol = pMol;
ret =nlopt_add_equality_constraint(opt_AugLag, Geo_Constraint_Bond, &(pMol->Geo_Fix_r0[i]), 2.0E-6);
printf(" Fixing bond %d\n", i );
}
for(i=0; i<pMol->nAngle_Fixed; i++) {
int ret=0;
pMol->Geo_Fix_theta0[i].pMol = pMol;
ret=nlopt_add_equality_constraint(opt_AugLag, Geo_Constraint_Angle, &(pMol->Geo_Fix_theta0[i]), 2.0E-6);
printf(" Fixing angle %d\n", i );
}
for(i=0; i<pMol->nPhi_Fixed; i++) {
int ret=0;
pMol->Geo_Fix_phi0[i].pMol = pMol;
ret=nlopt_add_equality_constraint(opt_AugLag, Geo_Constraint_Dihedral, &(pMol->Geo_Fix_phi0[i]), 2.0E-6);
printf(" Fixing phi %d : %d\n", i, ret );
}
nlopt_set_xtol_rel(opt_AugLag, 2E-7);
// opt = nlopt_create(NLOPT_LD_LBFGS_GEO, nDim);
// opt = nlopt_create(NLOPT_LN_COBYLA, nDim);
// nlopt_set_min_objective(opt, func_Geo_Opt_Constraint, pMol);
// nlopt_set_xtol_rel(opt, 1E-7);
// nlopt_set_local_optimizer(opt_AugLag, opt);
// nlopt_destroy(opt);
for(i=0; i<nAtom; i++) {
iPos = 3*i;
x[iPos ] = pMol->x[i];
x[iPos+1] = pMol->y[i];
x[iPos+2] = pMol->z[i];
}
Iter_Opt_Constrained = 0;
Return_Opt = nlopt_optimize(opt_AugLag, x, &E_min);
if (Return_Opt < 0) {
printf("nlopt failed : %d\n", Return_Opt);
}
// else {
// printf("After constrained optimization, E = %12.6lf\n", E_min);
// }
nlopt_destroy(opt_AugLag);
printf("MM after:\t");
for(i=0; i<n_Phi; i++) {
printf("%3d %3d %3d %3d %8.4lf\n", DihList[i][0], DihList[i][1], DihList[i][2], DihList[i][3],
Mol_ESP.Query_Dihedral(DihList[i][0], DihList[i][1], DihList[i][2], DihList[i][3], 0, NULL));
}
Mol_ESP.Restrain_All_Torsions(0); // lift soft restraints on all soft dihedrals
return (pMol->Cal_E(0));
}
double Optimize_Torsion_Parameters(void)
{
double lb[N_TOR_PARA] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -100.0 }; /* lower bounds */
double ub[N_TOR_PARA] = { 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 100.0 }; /* lower bounds */
// double ub[N_TOR_PARA] = { 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 100.0 }; /* lower bounds */
double Phase[32][5]={{0, 0, 0, 0, 0}, {0, 0, 0, 0, PI}, {0, 0, 0, PI, 0}, {0, 0, 0, PI, PI}, {0, 0, PI, 0, 0}, {0, 0, PI, 0, PI}, {0, 0, PI, PI, 0}, {0, 0, PI, PI, PI}, {0, PI, 0, 0, 0}, {0, PI, 0, 0, PI},
{0, PI, 0, PI, 0}, {0, PI, 0, PI, PI}, {0, PI, PI, 0, 0}, {0, PI, PI, 0, PI}, {0, PI, PI, PI, 0}, {0, PI, PI, PI, PI}, {PI, 0, 0, 0, 0}, {PI, 0, 0, 0, PI}, {PI, 0, 0, PI, 0}, {PI, 0, 0, PI, PI},
{PI, 0, PI, 0, 0}, {PI, 0, PI, 0, PI}, {PI, 0, PI, PI, 0}, {PI, 0, PI, PI, PI}, {PI, PI, 0, 0, 0}, {PI, PI, 0, 0, PI}, {PI, PI, 0, PI, 0}, {PI, PI, 0, PI, PI}, {PI, PI, PI, 0, 0}, {PI, PI, PI, 0, PI},
{PI, PI, PI, PI, 0}, {PI, PI, PI, PI, PI}};
nlopt_opt opt;
double Chi_SQ;
int i, j;
Chi_SQ_Min = 1.0E100;
iseed = time(NULL);
for(i=0; i<32; i++) {
ActiveRun = i;
Chi_SQ_Min_Local[i] = 1.0E200;
FailCount = Iteration = 0;
// for(j=0; j<5; j++) {
// Para_Tor[2*j] = 0.1+1.0*rand(iseed);
// }
Para_Tor[0] = Para_Tor[2] = Para_Tor[4] = Para_Tor[6] = Para_Tor[8] = 1.0;
for(j=0; j<5; j++) {
Para_Tor[2*j+1] = Phase[i][j];
lb[2*j+1] = Para_Tor[2*j+1];
ub[2*j+1] = Para_Tor[2*j+1];
}
// Para_Tor[1] = Para_Tor[3] = Para_Tor[5] = Para_Tor[7] = Para_Tor[9] = 0.0;
Para_Tor[10] = 0.0;
IsPara_Fixed[1] = IsPara_Fixed[3] = IsPara_Fixed[5] = IsPara_Fixed[7] = IsPara_Fixed[9] = 1;
//for test
// IsPara_Fixed[6] = 1; Para_Tor[6] = 0.0;
opt = nlopt_create(NLOPT_LD_LBFGS, N_TOR_PARA);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-8);
if (nlopt_optimize(opt, Para_Tor, &Chi_SQ) < 0) {
printf("nlopt didn't converge %lf %lf\n Please check carefully the rotamer results\n",Chi_SQ_Min, Chi_SQ);
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
nlopt_destroy(opt);
}
memcpy(Para_Tor, Para_Best, sizeof(double)*N_TOR_PARA);
CalObjectiveFunction_Tor(Para_Tor);
return Chi_SQ_Min;
}
