test_vars_constr_cost.h

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#include <ifopt/constraint_set.h>
#include <ifopt/cost_term.h>
#include <ifopt/variable_set.h>
 
namespace ifopt {
using Eigen::Vector2d;
 
class ExVariables : public VariableSet {
 public:
  // Every variable set has a name, here "var_set1". this allows the constraints
  // and costs to define values and Jacobians specifically w.r.t this variable set.
  ExVariables() : ExVariables("var_set1"){};
  ExVariables(const std::string& name) : VariableSet(2, name)
  {
    // the initial values where the NLP starts iterating from
    x0_ = 3.5;
    x1_ = 1.5;
  }
 
  // Here is where you can transform the Eigen::Vector into whatever
  // internal representation of your variables you have (here two doubles, but
  // can also be complex classes such as splines, etc..
  void SetVariables(const VectorXd& x) override
  {
    x0_ = x(0);
    x1_ = x(1);
  };
 
  // Here is the reverse transformation from the internal representation to
  // to the Eigen::Vector
  VectorXd GetValues() const override { return Vector2d(x0_, x1_); };
 
  // Each variable has an upper and lower bound set here
  VecBound GetBounds() const override
  {
    VecBound bounds(GetRows());
    bounds.at(0) = Bounds(-1.0, 1.0);
    bounds.at(1) = NoBound;
    return bounds;
  }
 
 private:
  double x0_, x1_;
};
 
class ExConstraint : public ConstraintSet {
 public:
  ExConstraint() : ExConstraint("constraint1") {}
 
  // This constraint set just contains 1 constraint, however generally
  // each set can contain multiple related constraints.
  ExConstraint(const std::string& name) : ConstraintSet(1, name) {}
 
  // The constraint value minus the constant value "1", moved to bounds.
  VectorXd GetValues() const override
  {
    VectorXd g(GetRows());
    Vector2d x = GetVariables()->GetComponent("var_set1")->GetValues();
    g(0)       = std::pow(x(0), 2) + x(1);
    return g;
  };
 
  // The only constraint in this set is an equality constraint to 1.
  // Constant values should always be put into GetBounds(), not GetValues().
  // For inequality constraints (<,>), use Bounds(x, inf) or Bounds(-inf, x).
  VecBound GetBounds() const override
  {
    VecBound b(GetRows());
    b.at(0) = Bounds(1.0, 1.0);
    return b;
  }
 
  // This function provides the first derivative of the constraints.
  // In case this is too difficult to write, you can also tell the solvers to
  // approximate the derivatives by finite differences and not overwrite this
  // function, e.g. in ipopt.cc::use_jacobian_approximation_ = true
  // Attention: see the parent class function for important information on sparsity pattern.
  void FillJacobianBlock(std::string var_set,
                         Jacobian& jac_block) const override
  {
    // must fill only that submatrix of the overall Jacobian that relates
    // to this constraint and "var_set1". even if more constraints or variables
    // classes are added, this submatrix will always start at row 0 and column 0,
    // thereby being independent from the overall problem.
    if (var_set == "var_set1") {
      Vector2d x = GetVariables()->GetComponent("var_set1")->GetValues();
 
      jac_block.coeffRef(0, 0) =
          2.0 * x(0);  // derivative of first constraint w.r.t x0
      jac_block.coeffRef(0, 1) =
          1.0;  // derivative of first constraint w.r.t x1
    }
  }
};
 
class ExCost : public CostTerm {
 public:
  ExCost() : ExCost("cost_term1") {}
  ExCost(const std::string& name) : CostTerm(name) {}
 
  double GetCost() const override
  {
    Vector2d x = GetVariables()->GetComponent("var_set1")->GetValues();
    return -std::pow(x(1) - 2, 2);
  };
 
  void FillJacobianBlock(std::string var_set, Jacobian& jac) const override
  {
    if (var_set == "var_set1") {
      Vector2d x = GetVariables()->GetComponent("var_set1")->GetValues();
 
      jac.coeffRef(0, 0) = 0.0;                  // derivative of cost w.r.t x0
      jac.coeffRef(0, 1) = -2.0 * (x(1) - 2.0);  // derivative of cost w.r.t x1
    }
  }
};
 
}  // namespace ifopt