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+// Copyright (C) 2004, 2006 International Business Machines and others.
+// All Rights Reserved.
+// This code is published under the Eclipse Public License.
+//
+// $Id: IpNLP.hpp 2269 2013-05-05 11:32:40Z stefan $
+//
+// Authors:  Carl Laird, Andreas Waechter     IBM    2004-08-13
+
+#ifndef __IPNLP_HPP__
+#define __IPNLP_HPP__
+
+#include "IpUtils.hpp"
+#include "IpVector.hpp"
+#include "IpSmartPtr.hpp"
+#include "IpMatrix.hpp"
+#include "IpSymMatrix.hpp"
+#include "IpOptionsList.hpp"
+#include "IpAlgTypes.hpp"
+#include "IpReturnCodes.hpp"
+
+namespace Ipopt
+{
+  // forward declarations
+  class IpoptData;
+  class IpoptCalculatedQuantities;
+  class IteratesVector;
+
+  /** Brief Class Description.
+   *  Detailed Class Description.
+   */
+  class NLP : public ReferencedObject
+  {
+  public:
+    /**@name Constructors/Destructors */
+    //@{
+    /** Default constructor */
+    NLP()
+    {}
+
+    /** Default destructor */
+    virtual ~NLP()
+    {}
+    //@}
+
+    /** Exceptions */
+    //@{
+    DECLARE_STD_EXCEPTION(USER_SCALING_NOT_IMPLEMENTED);
+    DECLARE_STD_EXCEPTION(INVALID_NLP);
+    //@}
+
+    /** @name NLP Initialization (overload in
+     *  derived classes).*/
+    //@{
+    /** Overload if you want the chance to process options or parameters that
+     *  may be specific to the NLP */
+    virtual bool ProcessOptions(const OptionsList& options,
+                                const std::string& prefix)
+    {
+      return true;
+    }
+
+    /** Method for creating the derived vector / matrix types.  The
+     *  Hess_lagrangian_space pointer can be NULL if a quasi-Newton
+     *  options is chosen. */
+    virtual bool 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 obtaining the bounds information */
+    virtual bool GetBoundsInformation(const Matrix& Px_L,
+                                      Vector& x_L,
+                                      const Matrix& Px_U,
+                                      Vector& x_U,
+                                      const Matrix& Pd_L,
+                                      Vector& d_L,
+                                      const Matrix& Pd_U,
+                                      Vector& d_U)=0;
+
+    /** Method for obtaining the starting point for all the
+     *  iterates. ToDo it might not make sense to ask for initial
+     *  values for v_L and v_U? */
+    virtual bool GetStartingPoint(
+      SmartPtr<Vector> x,
+      bool need_x,
+      SmartPtr<Vector> y_c,
+      bool need_y_c,
+      SmartPtr<Vector> y_d,
+      bool need_y_d,
+      SmartPtr<Vector> z_L,
+      bool need_z_L,
+      SmartPtr<Vector> z_U,
+      bool need_z_U
+    )=0;
+
+    /** Method for obtaining an entire iterate as a warmstart point.
+     *  The incoming IteratesVector has to be filled.  The default
+     *  dummy implementation returns false. */
+    virtual bool GetWarmStartIterate(IteratesVector& warm_start_iterate)
+    {
+      return false;
+    }
+    //@}
+
+    /** @name NLP evaluation routines (overload
+     *  in derived classes. */
+    //@{
+    virtual bool Eval_f(const Vector& x, Number& f) = 0;
+
+    virtual bool Eval_grad_f(const Vector& x, Vector& g_f) = 0;
+
+    virtual bool Eval_c(const Vector& x, Vector& c) = 0;
+
+    virtual bool Eval_jac_c(const Vector& x, Matrix& jac_c) = 0;
+
+    virtual bool Eval_d(const Vector& x, Vector& d) = 0;
+
+    virtual bool Eval_jac_d(const Vector& x, Matrix& jac_d) = 0;
+
+    virtual bool Eval_h(const Vector& x,
+                        Number obj_factor,
+                        const Vector& yc,
+                        const Vector& yd,
+                        SymMatrix& h) = 0;
+    //@}
+
+    /** @name NLP solution routines. Have default dummy
+     *  implementations that can be overloaded. */
+    //@{
+    /** This method is called at the very end of the optimization.  It
+     *  provides the final iterate to the user, so that it can be
+     *  stored as the solution.  The status flag indicates the outcome
+     *  of the optimization, where SolverReturn is defined in
+     *  IpAlgTypes.hpp.  */
+    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)
+    {}
+
+    /** This method is called once per iteration, after the iteration
+     *  summary output has been printed.  It provides the current
+     *  information to the user to do with it anything she wants.  It
+     *  also allows the user to ask for a premature termination of the
+     *  optimization by returning false, in which case Ipopt will
+     *  terminate with a corresponding return status.  The basic
+     *  information provided in the argument list has the quantities
+     *  values printed in the iteration summary line.  If more
+     *  information is required, a user can obtain it from the IpData
+     *  and IpCalculatedQuantities objects.  However, note that the
+     *  provided quantities are all for the problem that Ipopt sees,
+     *  i.e., the quantities might be scaled, fixed variables might be
+     *  sorted out, etc.  The status indicates things like whether the
+     *  algorithm is in the restoration phase...  In the restoration
+     *  phase, the dual variables are probably not not changing. */
+    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,
+                                      const IpoptData* ip_data,
+                                      IpoptCalculatedQuantities* ip_cq)
+    {
+      return true;
+    }
+    //@}
+
+    /** Routines to get the scaling parameters. These do not need to
+     *  be overloaded unless the options are set for User scaling
+     */
+    //@{
+    virtual void GetScalingParameters(
+      const SmartPtr<const VectorSpace> x_space,
+      const SmartPtr<const VectorSpace> c_space,
+      const SmartPtr<const VectorSpace> d_space,
+      Number& obj_scaling,
+      SmartPtr<Vector>& x_scaling,
+      SmartPtr<Vector>& c_scaling,
+      SmartPtr<Vector>& d_scaling) const
+    {
+      THROW_EXCEPTION(USER_SCALING_NOT_IMPLEMENTED,
+                      "You have set options for user provided scaling, but have"
+                      " not implemented GetScalingParameters in the NLP interface");
+    }
+    //@}
+
+    /** Method for obtaining the subspace in which the limited-memory
+     *  Hessian approximation should be done.  This is only called if
+     *  the limited-memory Hessian approximation is chosen.  Since the
+     *  Hessian is zero in the space of all variables that appear in
+     *  the problem functions only linearly, this allows the user to
+     *  provide a VectorSpace for all nonlinear variables, and an
+     *  ExpansionMatrix to lift from this VectorSpace to the
+     *  VectorSpace of the primal variables x.  If the returned values
+     *  are NULL, it is assumed that the Hessian is to be approximated
+     *  in the space of all x variables.  The default instantiation of
+     *  this method returns NULL, and a user only has to overwrite
+     *  this method if the approximation is to be done only in a
+     *  subspace. */
+    virtual void
+    GetQuasiNewtonApproximationSpaces(SmartPtr<VectorSpace>& approx_space,
+                                      SmartPtr<Matrix>& P_approx)
+    {
+      approx_space = NULL;
+      P_approx = NULL;
+    }
+
+  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 */
+    NLP(const NLP&);
+
+    /** Overloaded Equals Operator */
+    void operator=(const NLP&);
+    //@}
+  };
+
+} // namespace Ipopt
+
+#endif