problem.cc

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#include <ifopt/problem.h>
#include <iostream>
#include <iomanip>
 
 
namespace ifopt {
 
Problem::Problem ()
    :constraints_("constraint-sets", false),
     costs_("cost-terms", true)
{
  variables_ = std::make_shared<Composite>("variable-sets", false);
}
 
void
Problem::AddVariableSet(VariableSet::Ptr variable_set)
{
  variables_->AddComponent(variable_set);
}
 
void
Problem::AddConstraintSet(ConstraintSet::Ptr constraint_set)
{
  constraint_set->LinkWithVariables(variables_);
  constraints_.AddComponent(constraint_set);
}
 
void
Problem::AddCostSet(CostTerm::Ptr cost_set)
{
  cost_set->LinkWithVariables(variables_);
  costs_.AddComponent(cost_set);
}
 
int
Problem::GetNumberOfOptimizationVariables () const
{
  return variables_->GetRows();
}
 
Problem::VecBound
Problem::GetBoundsOnOptimizationVariables () const
{
  return variables_->GetBounds();
}
 
Problem::VectorXd
Problem::GetVariableValues () const
{
  return variables_->GetValues();
}
 
void
Problem::SetVariables (const double* x)
{
  variables_->SetVariables(ConvertToEigen(x));
}
 
double
Problem::EvaluateCostFunction (const double* x)
{
  VectorXd g = VectorXd::Zero(1);
  if (HasCostTerms()) {
    SetVariables(x);
    g = costs_.GetValues();
  }
  return g(0);
}
 
Problem::VectorXd
Problem::EvaluateCostFunctionGradient (const double* x, bool use_finite_difference_approximation, double epsilon)
{
  int n = GetNumberOfOptimizationVariables();
  Jacobian jac = Jacobian(1,n);
  if (HasCostTerms()) {
    if(use_finite_difference_approximation) {
      double step_size = epsilon;
      
      // calculate forward difference by disturbing each optimization variable
      double g = EvaluateCostFunction(x);
      std::vector<double> x_new(x, x + n);
      for (int i=0; i<n; ++i) {
        x_new[i] += step_size; // disturb
        double g_new = EvaluateCostFunction(x_new.data());
        jac.coeffRef(0,i) = (g_new - g)/step_size;
        x_new[i] = x[i]; // reset for next iteration
      }
    } else {
      SetVariables(x);
      jac = costs_.GetJacobian();
    }
  }
 
  return jac.row(0).transpose();
}
 
Problem::VecBound
Problem::GetBoundsOnConstraints () const
{
  return constraints_.GetBounds();
}
 
int
Problem::GetNumberOfConstraints () const
{
  return GetBoundsOnConstraints().size();
}
 
Problem::VectorXd
Problem::EvaluateConstraints (const double* x)
{
  SetVariables(x);
  return constraints_.GetValues();
}
 
bool
Problem::HasCostTerms () const
{
  return costs_.GetRows()>0;
}
 
void
Problem::EvalNonzerosOfJacobian (const double* x, double* values)
{
  SetVariables(x);
  Jacobian jac = GetJacobianOfConstraints();
 
  jac.makeCompressed(); // so the valuePtr() is dense and accurate
  std::copy(jac.valuePtr(), jac.valuePtr() + jac.nonZeros(), values);
}
 
Problem::Jacobian
Problem::GetJacobianOfConstraints () const
{
  return constraints_.GetJacobian();
}
 
Problem::Jacobian
Problem::GetJacobianOfCosts () const
{
  return costs_.GetJacobian();
}
 
void
Problem::SaveCurrent()
{
  x_prev.push_back(variables_->GetValues());
}
 
Composite::Ptr
Problem::GetOptVariables () const
{
  return variables_;
}
 
void
Problem::SetOptVariables (int iter)
{
  variables_->SetVariables(x_prev.at(iter));
}
 
void
Problem::SetOptVariablesFinal ()
{
  variables_->SetVariables(x_prev.at(GetIterationCount()-1));
}
 
void
Problem::PrintCurrent() const
{
  using namespace std;
  cout << "\n"
       << "************************************************************\n"
       << "    IFOPT - Interface to Nonlinear Optimizers (v2.0)\n"
       << "                \u00a9 Alexander W. Winkler\n"
       << "           https://github.com/ethz-adrl/ifopt\n"
       << "************************************************************"
       << "\n"
       << "Legend:\n"
       << "c - number of variables, constraints or cost terms" << std::endl
       << "i - indices of this set in overall problem" << std::endl
       << "v - number of [violated variable- or constraint-bounds] or [cost term value]"
       << "\n\n"
       << std::right
       << std::setw(33) << ""
       << std::setw(5)  << "c  "
       << std::setw(16) << "i    "
       << std::setw(11) << "v "
       << std::left
       << "\n";
 
  variables_->PrintAll();
  constraints_.PrintAll();
  costs_.PrintAll();
};
 
Problem::VectorXd
Problem::ConvertToEigen(const double* x) const
{
  return Eigen::Map<const VectorXd>(x,GetNumberOfOptimizationVariables());
}
 
} /* namespace opt */