Structure updated and intqpipopt files added

1 files changed, 261 insertions, 0 deletions

diff --git a/newstructure/thirdparty/linux/include/coin/IpIpoptNLP.hpp b/newstructure/thirdparty/linux/include/coin/IpIpoptNLP.hpp
new file mode 100644
index 0000000..21951c3
--- /dev/null
+++ b/newstructure/thirdparty/linux/include/coin/IpIpoptNLP.hpp
@@ -0,0 +1,261 @@
+// Copyright (C) 2004, 2006 International Business Machines and others.
+// All Rights Reserved.
+// This code is published under the Eclipse Public License.
+//
+// $Id: IpIpoptNLP.hpp 2594 2015-08-09 14:31:05Z stefan $
+//
+// Authors:  Carl Laird, Andreas Waechter     IBM    2004-08-13
+
+#ifndef __IPIPOPTNLP_HPP__
+#define __IPIPOPTNLP_HPP__
+
+#include "IpNLP.hpp"
+#include "IpJournalist.hpp"
+#include "IpNLPScaling.hpp"
+
+namespace Ipopt
+{
+  // forward declarations
+  class IteratesVector;
+
+  /** This is the abstract base class for classes that map
+   *  the traditional NLP into
+   *  something that is more useful by Ipopt.
+   *  This class takes care of storing the
+   *  calculated model results, handles cacheing,
+   *  and (some day) takes care of addition of slacks.
+   */
+  class IpoptNLP : public ReferencedObject
+  {
+  public:
+    /**@name Constructors/Destructors */
+    //@{
+    IpoptNLP(const SmartPtr<NLPScalingObject> nlp_scaling)
+        :
+        nlp_scaling_(nlp_scaling)
+    {}
+
+    /** Default destructor */
+    virtual ~IpoptNLP()
+    {}
+    //@}
+
+    /** Initialization method.  Set the internal options and
+     *  initialize internal data structures. */
+    virtual bool Initialize(const Journalist& jnlst,
+                            const OptionsList& options,
+                            const std::string& prefix)
+    {
+      bool ret = true;
+      if (IsValid(nlp_scaling_)) {
+        ret = nlp_scaling_->Initialize(jnlst, options, prefix);
+      }
+      return ret;
+    }
+
+    /**@name Possible Exceptions */
+    //@{
+    /** thrown if there is any error evaluating values from the nlp */
+    DECLARE_STD_EXCEPTION(Eval_Error);
+    //@}
+    /** Initialize (create) structures for
+     *  the iteration data */
+    virtual bool InitializeStructures(SmartPtr<Vector>& x,
+                                      bool init_x,
+                                      SmartPtr<Vector>& y_c,
+                                      bool init_y_c,
+                                      SmartPtr<Vector>& y_d,
+                                      bool init_y_d,
+                                      SmartPtr<Vector>& z_L,
+                                      bool init_z_L,
+                                      SmartPtr<Vector>& z_U,
+                                      bool init_z_U,
+                                      SmartPtr<Vector>& v_L,
+                                      SmartPtr<Vector>& v_U
+                                     ) = 0;
+
+    /** Method accessing the GetWarmStartIterate of the NLP */
+    virtual bool GetWarmStartIterate(IteratesVector& warm_start_iterate)=0;
+
+    /** Accessor methods for model data */
+    //@{
+    /** Objective value */
+    virtual Number f(const Vector& x) = 0;
+
+    /** Gradient of the objective */
+    virtual SmartPtr<const Vector> grad_f(const Vector& x) = 0;
+
+    /** Equality constraint residual */
+    virtual SmartPtr<const Vector> c(const Vector& x) = 0;
+
+    /** Jacobian Matrix for equality constraints */
+    virtual SmartPtr<const Matrix> jac_c(const Vector& x) = 0;
+
+    /** Inequality constraint residual (reformulated
+     *  as equalities with slacks */
+    virtual SmartPtr<const Vector> d(const Vector& x) = 0;
+
+    /** Jacobian Matrix for inequality constraints */
+    virtual SmartPtr<const Matrix> jac_d(const Vector& x) = 0;
+
+    /** Hessian of the Lagrangian */
+    virtual SmartPtr<const SymMatrix> h(const Vector& x,
+                                        Number obj_factor,
+                                        const Vector& yc,
+                                        const Vector& yd
+                                       ) = 0;
+
+    /** Lower bounds on x */
+    virtual SmartPtr<const Vector> x_L() const = 0;
+
+    /** Permutation matrix (x_L_ -> x) */
+    virtual SmartPtr<const Matrix> Px_L() const = 0;
+
+    /** Upper bounds on x */
+    virtual SmartPtr<const Vector> x_U() const = 0;
+
+    /** Permutation matrix (x_U_ -> x */
+    virtual SmartPtr<const Matrix> Px_U() const = 0;
+
+    /** Lower bounds on d */
+    virtual SmartPtr<const Vector> d_L() const = 0;
+
+    /** Permutation matrix (d_L_ -> d) */
+    virtual SmartPtr<const Matrix> Pd_L() const = 0;
+
+    /** Upper bounds on d */
+    virtual SmartPtr<const Vector> d_U() const = 0;
+
+    /** Permutation matrix (d_U_ -> d */
+    virtual SmartPtr<const Matrix> Pd_U() const = 0;
+
+    /** x_space */
+    virtual SmartPtr<const VectorSpace> x_space() const = 0;
+
+    /** Accessor method to obtain the MatrixSpace for the Hessian
+     *  matrix (or it's approximation) */
+    virtual SmartPtr<const SymMatrixSpace> HessianMatrixSpace() const = 0;
+    //@}
+
+    /** Accessor method for vector/matrix spaces pointers. */
+    virtual void GetSpaces(SmartPtr<const VectorSpace>& x_space,
+                           SmartPtr<const VectorSpace>& c_space,
+                           SmartPtr<const VectorSpace>& d_space,
+                           SmartPtr<const VectorSpace>& x_l_space,
+                           SmartPtr<const MatrixSpace>& px_l_space,
+                           SmartPtr<const VectorSpace>& x_u_space,
+                           SmartPtr<const MatrixSpace>& px_u_space,
+                           SmartPtr<const VectorSpace>& d_l_space,
+                           SmartPtr<const MatrixSpace>& pd_l_space,
+                           SmartPtr<const VectorSpace>& d_u_space,
+                           SmartPtr<const MatrixSpace>& pd_u_space,
+                           SmartPtr<const MatrixSpace>& Jac_c_space,
+                           SmartPtr<const MatrixSpace>& Jac_d_space,
+                           SmartPtr<const SymMatrixSpace>& Hess_lagrangian_space) = 0;
+
+    /** Method for adapting the variable bounds.  This is called if
+     *  slacks are becoming too small */
+    virtual void AdjustVariableBounds(const Vector& new_x_L,
+                                      const Vector& new_x_U,
+                                      const Vector& new_d_L,
+                                      const Vector& new_d_U)=0;
+
+    /** @name Counters for the number of function evaluations. */
+    //@{
+    virtual Index f_evals() const = 0;
+    virtual Index grad_f_evals() const = 0;
+    virtual Index c_evals() const = 0;
+    virtual Index jac_c_evals() const = 0;
+    virtual Index d_evals() const = 0;
+    virtual Index jac_d_evals() const = 0;
+    virtual Index h_evals() const = 0;
+    //@}
+
+    /** @name Special method for dealing with the fact that the
+     *  restoration phase objective function depends on the barrier
+     *  parameter */
+    //@{
+    /** Method for telling the IpoptCalculatedQuantities class whether
+     *  the objective function depends on the barrier function.  This
+     *  is only used for the restoration phase NLP
+     *  formulation. Probably only RestoIpoptNLP should overwrite
+     *  this. */
+    virtual bool objective_depends_on_mu() const
+    {
+      return false;
+    }
+
+    /** Replacement for the default objective function method which
+     *  knows about the barrier parameter */
+    virtual Number f(const Vector& x, Number mu) = 0;
+
+    /** Replacement for the default objective gradient method which
+     *  knows about the barrier parameter  */
+    virtual SmartPtr<const Vector> grad_f(const Vector& x, Number mu) = 0;
+
+    /** Replacement for the default Lagrangian Hessian method which
+     *  knows about the barrier parameter */
+    virtual SmartPtr<const SymMatrix> h(const Vector& x,
+                                        Number obj_factor,
+                                        const Vector& yc,
+                                        const Vector& yd,
+                                        Number mu) = 0;
+
+    /** Provides a Hessian matrix from the correct matrix space with
+     *  uninitialized values.  This can be used in LeastSquareMults to
+     *  obtain a "zero Hessian". */
+    virtual SmartPtr<const SymMatrix> uninitialized_h() = 0;
+    //@}
+
+    /**@name solution routines */
+    //@{
+    virtual void FinalizeSolution(SolverReturn status,
+                                  const Vector& x, const Vector& z_L, const Vector& z_U,
+                                  const Vector& c, const Vector& d,
+                                  const Vector& y_c, const Vector& y_d,
+                                  Number obj_value,
+                                  const IpoptData* ip_data,
+                                  IpoptCalculatedQuantities* ip_cq)=0;
+
+    virtual bool IntermediateCallBack(AlgorithmMode mode,
+                                      Index iter, Number obj_value,
+                                      Number inf_pr, Number inf_du,
+                                      Number mu, Number d_norm,
+                                      Number regularization_size,
+                                      Number alpha_du, Number alpha_pr,
+                                      Index ls_trials,
+                                      SmartPtr<const IpoptData> ip_data,
+                                      SmartPtr<IpoptCalculatedQuantities> ip_cq)=0;
+    //@}
+
+    /** Returns the scaling strategy object */
+    SmartPtr<NLPScalingObject> NLP_scaling() const
+    {
+      DBG_ASSERT(IsValid(nlp_scaling_));
+      return nlp_scaling_;
+    }
+
+  private:
+
+    /**@name Default Compiler Generated Methods
+     * (Hidden to avoid implicit creation/calling).
+     * These methods are not implemented and 
+     * we do not want the compiler to implement
+     * them for us, so we declare them private
+     * and do not define them. This ensures that
+     * they will not be implicitly created/called. */
+    //@{
+
+    /** Copy Constructor */
+    IpoptNLP(const IpoptNLP&);
+
+    /** Overloaded Equals Operator */
+    void operator=(const IpoptNLP&);
+    //@}
+
+    SmartPtr<NLPScalingObject> nlp_scaling_;
+  };
+
+} // namespace Ipopt
+
+#endif