Esempio n. 1
0
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;
}
Esempio n. 2
0
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();
}
Esempio n. 3
0
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();
}