void function_minimizer::hess_routine_noparallel(void)
{
int nvar=initial_params::nvarcalc(); // get the number of active parameters
//if (adjm_ptr) set_labels_for_hess(nvar);
independent_variables x(1,nvar);
initial_params::xinit(x); // get the initial values into the x vector
double delta=1.e-5;
dvector g1(1,nvar);
dvector g2(1,nvar);
dvector gbest(1,nvar);
dvector hess(1,nvar);
dvector hess1(1,nvar);
dvector hess2(1,nvar);
double eps=.1;
gradient_structure::set_YES_DERIVATIVES();
gbest.fill_seqadd(1.e+50,0.);
adstring tmpstring="admodel.hes";
if (ad_comm::wd_flag)
tmpstring = ad_comm::adprogram_name + ".hes";
uostream ofs((char*)tmpstring);
ofs << nvar;
{
{
dvariable vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
gradcalc(nvar, g1, vf);
}
double sdelta1;
double sdelta2;
for (int i=1;i<=nvar;i++)
{
hess_calcreport(i,nvar);
double xsave=x(i);
sdelta1=x(i)+delta;
sdelta1-=x(i);
x(i)=xsave+sdelta1;
dvariable vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
gradcalc(nvar, g1, vf);
sdelta2=x(i)-delta;
sdelta2-=x(i);
x(i)=xsave+sdelta2;
vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
gradcalc(nvar, g2, vf);
x(i)=xsave;
hess1=(g1-g2)/(sdelta1-sdelta2);
sdelta1=x(i)+eps*delta;
sdelta1-=x(i);
x(i)=xsave+sdelta1;
vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
gradcalc(nvar, g1, vf);
x(i)=xsave-eps*delta;
sdelta2=x(i)-eps*delta;
sdelta2-=x(i);
x(i)=xsave+sdelta2;
vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
gradcalc(nvar, g2, vf);
x(i)=xsave;
vf=initial_params::reset(dvar_vector(x));
double eps2=eps*eps;
hess2=(g1-g2)/(sdelta1-sdelta2);
hess=(eps2*hess1-hess2) /(eps2-1.);
ofs << hess;
//if (adjm_ptr) ad_update_hess_stats_report(nvar,i);
}
}
ofs << gradient_structure::Hybrid_bounded_flag;
dvector tscale(1,nvar); // need to get scale from somewhere
/*int check=*/initial_params::stddev_scale(tscale,x);
ofs << tscale;
}
void function_minimizer::hess_routine_master()
{
int nvar=initial_params::nvarcalc(); // get the number of active parameters
//if (adjm_ptr) set_labels_for_hess(nvar);
independent_variables x(1,nvar);
initial_params::xinit(x); // get the initial values into the x vector
double f;
double delta=1.e-6;
dvector g1(1,nvar);
dvector g2(1,nvar);
dvector gbest(1,nvar);
dvector hess(1,nvar);
dvector hess1(1,nvar);
dvector hess2(1,nvar);
double eps=.1;
gradient_structure::set_YES_DERIVATIVES();
gbest.fill_seqadd(1.e+50,0.);
adstring tmpstring="admodel.hes";
if (ad_comm::wd_flag)
tmpstring = ad_comm::adprogram_name + ".hes";
uostream ofs((char*)tmpstring);
ofs << nvar;
{
pvm_master_function_evaluation(f,x,g1,nvar);
double sdelta1;
double sdelta2;
for (int i=1;i<=nvar;i++)
{
hess_calcreport(i,nvar);
double f=0.0;
double xsave=x(i);
sdelta1=x(i)+delta;
useless(sdelta1);
sdelta1-=x(i);
x(i)=xsave+sdelta1;
pvm_master_function_evaluation(f,x,g1,nvar);
sdelta2=x(i)-delta;
useless(sdelta2);
sdelta2-=x(i);
x(i)=xsave+sdelta2;
pvm_master_function_evaluation(f,x,g2,nvar);
x(i)=xsave;
hess1=(g1-g2)/(sdelta1-sdelta2);
sdelta1=x(i)+eps*delta;
useless(sdelta1);
sdelta1-=x(i);
x(i)=xsave+sdelta1;
pvm_master_function_evaluation(f,x,g1,nvar);
x(i)=xsave-eps*delta;
sdelta2=x(i)-eps*delta;
useless(sdelta2);
sdelta2-=x(i);
x(i)=xsave+sdelta2;
pvm_master_function_evaluation(f,x,g2,nvar);
x(i)=xsave;
dvariable vf=initial_params::reset(dvar_vector(x));
double eps2=eps*eps;
hess2=(g1-g2)/(sdelta1-sdelta2);
hess=(eps2*hess1-hess2) /(eps2-1.);
ofs << hess;
//if (adjm_ptr) ad_update_hess_stats_report(nvar,i);
}
}
gradient_structure::set_NO_DERIVATIVES();
}
void function_minimizer::hess_routine_and_constraint(int iprof,
const dvector& g, dvector& fg)
{
int nvar=initial_params::nvarcalc(); // get the number of active parameters
independent_variables x(1,nvar);
initial_params::xinit(x); // get the initial values into the x vector
double delta=1.e-6;
dvector g1(1,nvar);
dvector g2(1,nvar);
dvector gbest(1,nvar);
dvector hess(1,nvar);
dvector hess1(1,nvar);
dvector hess2(1,nvar);
//double eps=.1;
gradient_structure::set_YES_DERIVATIVES();
gbest.fill_seqadd(1.e+50,0.);
uostream ofs("admodel.hes");
//ofstream ofs5("tmphess");
double lambda=fg*g/norm2(g);
cout << fg-lambda*g << endl;
cout << norm(fg-lambda*g) << " " << fg*g/(norm(g)*norm(fg)) << endl;
ofs << nvar;
{
{
dvariable vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
vf-=lambda*likeprof_params::likeprofptr[iprof]->variable();
gradcalc(nvar, g1, vf);
}
double sdelta1;
double sdelta2;
for (int i=1;i<=nvar;i++)
{
hess_calcreport(i,nvar);
double xsave=x(i);
sdelta1=x(i)+delta;
sdelta1-=x(i);
x(i)=xsave+sdelta1;
dvariable vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
vf-=lambda*likeprof_params::likeprofptr[iprof]->variable();
gradcalc(nvar, g1, vf);
sdelta2=x(i)-delta;
sdelta2-=x(i);
x(i)=xsave+sdelta2;
vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
vf-=lambda*likeprof_params::likeprofptr[iprof]->variable();
gradcalc(nvar, g2, vf);
x(i)=xsave;
hess1=(g1-g2)/(sdelta1-sdelta2);
/*
sdelta1=x(i)+eps*delta;
sdelta1-=x(i);
x(i)=xsave+sdelta1;
vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
vf-=lambda*likeprof_params::likeprofptr[iprof]->variable();
f=value(vf);
gradcalc(nvar,g1);
x(i)=xsave-eps*delta;
sdelta2=x(i)-eps*delta;
sdelta2-=x(i);
x(i)=xsave+sdelta2;
vf=0.0;
vf=0.0;
vf=initial_params::reset(dvar_vector(x));
*objective_function_value::pobjfun=0.0;
pre_userfunction();
vf+=*objective_function_value::pobjfun;
vf-=lambda*likeprof_params::likeprofptr[iprof]->variable();
f=value(vf);
gradcalc(nvar,g2);
x(i)=xsave;
double eps2=eps*eps;
hess2=(g1-g2)/(sdelta1-sdelta2);
hess=(eps2*hess1-hess2) /(eps2-1.);
*/
hess=hess1;
ofs << hess;
}
}
gradient_structure::set_NO_DERIVATIVES();
}
