RhodeCode

    }

    ///Erase a column (i.e a variable) from the LP

    ///\param c is the column to be deleted

    void erase(Col c) {

      _eraseCol(cols(id(c)));

      _eraseColId(cols(id(c)));

    }

    ///Erase a row (i.e a constraint) from the LP

    ///\param r is the row to be deleted

    void erase(Row r) {

      _eraseRow(rows(id(r)));

      _eraseRowId(rows(id(r)));

    }

    /// Get the name of a column

    ///\param c is the coresponding column

    ///\return The name of the colunm

    std::string colName(Col c) const {

      std::string name;

      _getColName(cols(id(c)), name);

      return name;

    }

    /// Set the name of a column

    ///\param c is the coresponding column

    ///\param name The name to be given

    void colName(Col c, const std::string& name) {

      _setColName(cols(id(c)), name);

    }

    /// Get the column by its name

    ///\param name The name of the column

    ///\return the proper column or \c INVALID

    Col colByName(const std::string& name) const {

      int k = _colByName(name);

      return k != -1 ? Col(cols[k]) : Col(INVALID);

    }

    /// Get the name of a row

    ///\param r is the coresponding row

    ///\return The name of the row

    std::string rowName(Row r) const {

      std::string name;

      _getRowName(rows(id(r)), name);

      return name;

    }

    /// Set the name of a row

    ///\param r is the coresponding row

    ///\param name The name to be given

    void rowName(Row r, const std::string& name) {

      _setRowName(rows(id(r)), name);

    }

    /// Get the row by its name

    ///\param name The name of the row

    ///\return the proper row or \c INVALID

    Row rowByName(const std::string& name) const {

      int k = _rowByName(name);

      return k != -1 ? Row(rows[k]) : Row(INVALID);

    }

    /// Set an element of the coefficient matrix of the LP

    ///\param r is the row of the element to be modified

    ///\param c is the column of the element to be modified

    ///\param val is the new value of the coefficient

    void coeff(Row r, Col c, Value val) {

      _setCoeff(rows(id(r)),cols(id(c)), val);

    }

    /// Get an element of the coefficient matrix of the LP

    ///\param r is the row of the element

    ///\param c is the column of the element

    ///\return the corresponding coefficient

    Value coeff(Row r, Col c) const {

      return _getCoeff(rows(id(r)),cols(id(c)));

    }

    /// Set the lower bound of a column (i.e a variable)

    /// The lower bound of a variable (column) has to be given by an

    /// extended number of type Value, i.e. a finite number of type

    /// Value or -\ref INF.

    void colLowerBound(Col c, Value value) {

      _setColLowerBound(cols(id(c)),value);

    }

    /// Get the lower bound of a column (i.e a variable)

    /// This function returns the lower bound for column (variable) \c c

    /// (this might be -\ref INF as well).

    ///\return The lower bound for column \c c

    Value colLowerBound(Col c) const {

      return _getColLowerBound(cols(id(c)));

    }

    ///\brief Set the lower bound of  several columns

    ///(i.e variables) at once

    ///

    ///This magic function takes a container as its argument

    ///and applies the function on all of its elements.

    ///The lower bound of a variable (column) has to be given by an

    ///extended number of type Value, i.e. a finite number of type

    ///Value or -\ref INF.

#ifdef DOXYGEN

    template<class T>

    void colLowerBound(T &t, Value value) { return 0;}

#else

    template<class T>

    typename enable_if<typename T::value_type::LpCol,void>::type

    colLowerBound(T &t, Value value,dummy<0> = 0) {

      for(typename T::iterator i=t.begin();i!=t.end();++i) {

        colLowerBound(*i, value);

      }

    }

    template<class T>

    typename enable_if<typename T::value_type::second_type::LpCol,

                       void>::type

    colLowerBound(T &t, Value value,dummy<1> = 1) {

      for(typename T::iterator i=t.begin();i!=t.end();++i) {

        colLowerBound(i->second, value);

      }

    }

    template<class T>

    typename enable_if<typename T::MapIt::Value::LpCol,

                       void>::type

    colLowerBound(T &t, Value value,dummy<2> = 2) {

      for(typename T::MapIt i(t); i!=INVALID; ++i){

        colLowerBound(*i, value);

      }

    }

#endif

    /// Set the upper bound of a column (i.e a variable)

    /// The upper bound of a variable (column) has to be given by an

    /// extended number of type Value, i.e. a finite number of type

    /// Value or \ref INF.

    void colUpperBound(Col c, Value value) {

      _setColUpperBound(cols(id(c)),value);

    };

    /// Get the upper bound of a column (i.e a variable)

    /// This function returns the upper bound for column (variable) \c c

    /// (this might be \ref INF as well).

    /// \return The upper bound for column \c c

    Value colUpperBound(Col c) const {

      return _getColUpperBound(cols(id(c)));

    }

    ///\brief Set the upper bound of  several columns

    ///(i.e variables) at once

    ///

    ///This magic function takes a container as its argument

    ///and applies the function on all of its elements.

    ///The upper bound of a variable (column) has to be given by an

    ///extended number of type Value, i.e. a finite number of type

    ///Value or \ref INF.

#ifdef DOXYGEN

    template<class T>

    void colUpperBound(T &t, Value value) { return 0;}

#else

    template<class T1>

    typename enable_if<typename T1::value_type::LpCol,void>::type

    colUpperBound(T1 &t, Value value,dummy<0> = 0) {

      for(typename T1::iterator i=t.begin();i!=t.end();++i) {

        colUpperBound(*i, value);

      }

    }

    template<class T1>

    typename enable_if<typename T1::value_type::second_type::LpCol,

                       void>::type

    colUpperBound(T1 &t, Value value,dummy<1> = 1) {

      for(typename T1::iterator i=t.begin();i!=t.end();++i) {

        colUpperBound(i->second, value);

      }

    }

    template<class T1>

    typename enable_if<typename T1::MapIt::Value::LpCol,

                       void>::type

    colUpperBound(T1 &t, Value value,dummy<2> = 2) {

      for(typename T1::MapIt i(t); i!=INVALID; ++i){

        colUpperBound(*i, value);

      }

    }

#endif

    /// Set the lower and the upper bounds of a column (i.e a variable)

    /// The lower and the upper bounds of

    /// a variable (column) have to be given by an

    /// extended number of type Value, i.e. a finite number of type

    /// Value, -\ref INF or \ref INF.

    void colBounds(Col c, Value lower, Value upper) {

      _setColLowerBound(cols(id(c)),lower);

      _setColUpperBound(cols(id(c)),upper);

    }

    ///\brief Set the lower and the upper bound of several columns

    ///(i.e variables) at once

    ///

    ///This magic function takes a container as its argument

    ///and applies the function on all of its elements.

    /// The lower and the upper bounds of

    /// a variable (column) have to be given by an

    /// extended number of type Value, i.e. a finite number of type

    /// Value, -\ref INF or \ref INF.

#ifdef DOXYGEN

    template<class T>

    void colBounds(T &t, Value lower, Value upper) { return 0;}

#else

    template<class T2>

    typename enable_if<typename T2::value_type::LpCol,void>::type

    colBounds(T2 &t, Value lower, Value upper,dummy<0> = 0) {

      for(typename T2::iterator i=t.begin();i!=t.end();++i) {

        colBounds(*i, lower, upper);

      }

    }

    template<class T2>

    typename enable_if<typename T2::value_type::second_type::LpCol, void>::type

    colBounds(T2 &t, Value lower, Value upper,dummy<1> = 1) {

      for(typename T2::iterator i=t.begin();i!=t.end();++i) {

        colBounds(i->second, lower, upper);

      }

    }

    template<class T2>

    typename enable_if<typename T2::MapIt::Value::LpCol, void>::type

    colBounds(T2 &t, Value lower, Value upper,dummy<2> = 2) {

      for(typename T2::MapIt i(t); i!=INVALID; ++i){

        colBounds(*i, lower, upper);

      }

    }

#endif

    /// Set the lower bound of a row (i.e a constraint)

    /// The lower bound of a constraint (row) has to be given by an

    /// extended number of type Value, i.e. a finite number of type

    /// Value or -\ref INF.

    void rowLowerBound(Row r, Value value) {

      _setRowLowerBound(rows(id(r)),value);

    }

    /// Get the lower bound of a row (i.e a constraint)

    /// This function returns the lower bound for row (constraint) \c c

    /// (this might be -\ref INF as well).

    ///\return The lower bound for row \c r

    Value rowLowerBound(Row r) const {

      return _getRowLowerBound(rows(id(r)));

    }

    /// Set the upper bound of a row (i.e a constraint)

    /// The upper bound of a constraint (row) has to be given by an

    /// extended number of type Value, i.e. a finite number of type

    /// Value or -\ref INF.

    void rowUpperBound(Row r, Value value) {

      _setRowUpperBound(rows(id(r)),value);

    }

    /// Get the upper bound of a row (i.e a constraint)

    /// This function returns the upper bound for row (constraint) \c c

    /// (this might be -\ref INF as well).

    ///\return The upper bound for row \c r

    Value rowUpperBound(Row r) const {

      return _getRowUpperBound(rows(id(r)));

    }

    ///Set an element of the objective function

    void objCoeff(Col c, Value v) {_setObjCoeff(cols(id(c)),v); };

    ///Get an element of the objective function

    Value objCoeff(Col c) const { return _getObjCoeff(cols(id(c))); };

    ///Set the objective function

    ///\param e is a linear expression of type \ref Expr.

    ///

    void obj(const Expr& e) {

      _setObjCoeffs(ExprIterator(e.comps.begin(), cols),

                    ExprIterator(e.comps.end(), cols));

      obj_const_comp = *e;

    }

    ///Get the objective function

    ///\return the objective function as a linear expression of type

    ///Expr.

    Expr obj() const {

      Expr e;

      _getObjCoeffs(InsertIterator(e.comps, cols));

      *e = obj_const_comp;

      return e;

    }

    ///Set the direction of optimization

    void sense(Sense sense) { _setSense(sense); }

    ///Query the direction of the optimization

    Sense sense() const {return _getSense(); }

    ///Set the sense to maximization

    void max() { _setSense(MAX); }

    ///Set the sense to maximization

    void min() { _setSense(MIN); }

    ///Clears the problem

    void clear() { _clear(); }

    /// Sets the message level of the solver

    void messageLevel(MessageLevel level) { _messageLevel(level); }

    ///@}

  };

  /// Addition

  ///\relates LpBase::Expr

  ///

  inline LpBase::Expr operator+(const LpBase::Expr &a, const LpBase::Expr &b) {

    LpBase::Expr tmp(a);

    tmp+=b;

    return tmp;

  }

  ///Substraction

  ///\relates LpBase::Expr

  ///

  inline LpBase::Expr operator-(const LpBase::Expr &a, const LpBase::Expr &b) {

    LpBase::Expr tmp(a);

    tmp-=b;

    return tmp;

  }

  ///Multiply with constant

  ///\relates LpBase::Expr

  ///

  inline LpBase::Expr operator*(const LpBase::Expr &a, const LpBase::Value &b) {

    LpBase::Expr tmp(a);

    tmp*=b;

    return tmp;

  }

  ///Multiply with constant

  ///\relates LpBase::Expr

  ///

  inline LpBase::Expr operator*(const LpBase::Value &a, const LpBase::Expr &b) {

    LpBase::Expr tmp(b);

    tmp*=a;

    return tmp;

  }

  ///Divide with constant

  ///\relates LpBase::Expr

  ///

  inline LpBase::Expr operator/(const LpBase::Expr &a, const LpBase::Value &b) {

    LpBase::Expr tmp(a);

    tmp/=b;

    return tmp;

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator<=(const LpBase::Expr &e,

                                   const LpBase::Expr &f) {

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator<=(const LpBase::Value &e,

                                   const LpBase::Expr &f) {

    return LpBase::Constr(e, f, LpBase::NaN);

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator<=(const LpBase::Expr &e,

                                   const LpBase::Value &f) {

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator>=(const LpBase::Expr &e,

                                   const LpBase::Expr &f) {

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator>=(const LpBase::Value &e,

                                   const LpBase::Expr &f) {

    return LpBase::Constr(LpBase::NaN, f, e);

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator>=(const LpBase::Expr &e,

                                   const LpBase::Value &f) {

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator==(const LpBase::Expr &e,

                                   const LpBase::Value &f) {

    return LpBase::Constr(f, e, f);

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator==(const LpBase::Expr &e,

                                   const LpBase::Expr &f) {

    return LpBase::Constr(0, f - e, 0);

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator<=(const LpBase::Value &n,

                                   const LpBase::Constr &c) {

    LpBase::Constr tmp(c);

    LEMON_ASSERT(isNaN(tmp.lowerBound()), "Wrong LP constraint");

    tmp.lowerBound()=n;

    return tmp;

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator<=(const LpBase::Constr &c,

                                   const LpBase::Value &n)

  {

    LpBase::Constr tmp(c);

    LEMON_ASSERT(isNaN(tmp.upperBound()), "Wrong LP constraint");

    tmp.upperBound()=n;

    return tmp;

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator>=(const LpBase::Value &n,

                                   const LpBase::Constr &c) {

    LpBase::Constr tmp(c);

    LEMON_ASSERT(isNaN(tmp.upperBound()), "Wrong LP constraint");

    tmp.upperBound()=n;

    return tmp;

  }

  ///Create constraint

  ///\relates LpBase::Constr

  ///

  inline LpBase::Constr operator>=(const LpBase::Constr &c,

                                   const LpBase::Value &n)

  {

    LpBase::Constr tmp(c);

    LEMON_ASSERT(isNaN(tmp.lowerBound()), "Wrong LP constraint");

    tmp.lowerBound()=n;

    return tmp;

  }

  ///Addition

  ///\relates LpBase::DualExpr

  ///

  inline LpBase::DualExpr operator+(const LpBase::DualExpr &a,

                                    const LpBase::DualExpr &b) {

    LpBase::DualExpr tmp(a);

    tmp+=b;

    return tmp;

  }

  ///Substraction

  ///\relates LpBase::DualExpr

  ///

  inline LpBase::DualExpr operator-(const LpBase::DualExpr &a,

                                    const LpBase::DualExpr &b) {

    LpBase::DualExpr tmp(a);

    tmp-=b;

    return tmp;

  }

  ///Multiply with constant

  ///\relates LpBase::DualExpr

  ///

  inline LpBase::DualExpr operator*(const LpBase::DualExpr &a,

                                    const LpBase::Value &b) {

    LpBase::DualExpr tmp(a);

    tmp*=b;

    return tmp;

  }

  ///Multiply with constant

  ///\relates LpBase::DualExpr

  ///

  inline LpBase::DualExpr operator*(const LpBase::Value &a,

                                    const LpBase::DualExpr &b) {

    LpBase::DualExpr tmp(b);

    tmp*=a;

    return tmp;

  }

  ///Divide with constant

  ///\relates LpBase::DualExpr

  ///

  inline LpBase::DualExpr operator/(const LpBase::DualExpr &a,

                                    const LpBase::Value &b) {

    LpBase::DualExpr tmp(a);

    tmp/=b;

    return tmp;

  }

  /// \ingroup lp_group

  ///

  /// \brief Common base class for LP solvers

  ///

  /// This class is an abstract base class for LP solvers. This class

  /// provides a full interface for set and modify an LP problem,

  /// solve it and retrieve the solution. You can use one of the

  /// descendants as a concrete implementation, or the \c Lp

  /// default LP solver. However, if you would like to handle LP

  /// solvers as reference or pointer in a generic way, you can use

  /// this class directly.

  class LpSolver : virtual public LpBase {

  public:

    /// The problem types for primal and dual problems

    enum ProblemType {

      /// = 0. Feasible solution hasn't been found (but may exist).

      UNDEFINED = 0,

      /// = 1. The problem has no feasible solution.

      INFEASIBLE = 1,

      /// = 2. Feasible solution found.

      FEASIBLE = 2,

      /// = 3. Optimal solution exists and found.

      OPTIMAL = 3,

      /// = 4. The cost function is unbounded.

      UNBOUNDED = 4

    };

    ///The basis status of variables

    enum VarStatus {

      /// The variable is in the basis

      BASIC, 

      /// The variable is free, but not basic

      FREE,

      /// The variable has active lower bound 

      LOWER,

      /// The variable has active upper bound

      UPPER,

      /// The variable is non-basic and fixed

      FIXED

    };

  protected:

    virtual SolveExitStatus _solve() = 0;

    virtual Value _getPrimal(int i) const = 0;

    virtual Value _getDual(int i) const = 0;

    virtual Value _getPrimalRay(int i) const = 0;

    virtual Value _getDualRay(int i) const = 0;

    virtual Value _getPrimalValue() const = 0;

    virtual VarStatus _getColStatus(int i) const = 0;

    virtual VarStatus _getRowStatus(int i) const = 0;

    virtual ProblemType _getPrimalType() const = 0;

    virtual ProblemType _getDualType() const = 0;

  public:

    ///Allocate a new LP problem instance

    virtual LpSolver* newSolver() const = 0;

    ///Make a copy of the LP problem

    virtual LpSolver* cloneSolver() const = 0;

    ///\name Solve the LP

    ///@{

    ///\e Solve the LP problem at hand

    ///

    ///\return The result of the optimization procedure. Possible

    ///values and their meanings can be found in the documentation of

    ///\ref SolveExitStatus.

    SolveExitStatus solve() { return _solve(); }

    ///@}

    ///\name Obtain the Solution

    ///@{

    /// The type of the primal problem

    ProblemType primalType() const {

      return _getPrimalType();

    }

    /// The type of the dual problem

    ProblemType dualType() const {

      return _getDualType();

    }

    /// Return the primal value of the column

    /// Return the primal value of the column.

    /// \pre The problem is solved.

    Value primal(Col c) const { return _getPrimal(cols(id(c))); }

    /// Return the primal value of the expression

    /// Return the primal value of the expression, i.e. the dot

    /// product of the primal solution and the expression.

    /// \pre The problem is solved.

    Value primal(const Expr& e) const {

      double res = *e;

      for (Expr::ConstCoeffIt c(e); c != INVALID; ++c) {

        res += *c * primal(c);

      }

      return res;

    }

    /// Returns a component of the primal ray

    /// The primal ray is solution of the modified primal problem,

    /// where we change each finite bound to 0, and we looking for a

    /// negative objective value in case of minimization, and positive

    /// objective value for maximization. If there is such solution,

    /// that proofs the unsolvability of the dual problem, and if a

    /// feasible primal solution exists, then the unboundness of

    /// primal problem.

    ///

    /// \pre The problem is solved and the dual problem is infeasible.

    /// \note Some solvers does not provide primal ray calculation

    /// functions.

    Value primalRay(Col c) const { return _getPrimalRay(cols(id(c))); }

    /// Return the dual value of the row

    /// Return the dual value of the row.

    /// \pre The problem is solved.

    Value dual(Row r) const { return _getDual(rows(id(r))); }

    /// Return the dual value of the dual expression

    /// Return the dual value of the dual expression, i.e. the dot

    /// product of the dual solution and the dual expression.

    /// \pre The problem is solved.

    Value dual(const DualExpr& e) const {

      double res = 0.0;

      for (DualExpr::ConstCoeffIt r(e); r != INVALID; ++r) {

        res += *r * dual(r);

      }

      return res;

    }

    /// Returns a component of the dual ray

    /// The dual ray is solution of the modified primal problem, where

    /// we change each finite bound to 0 (i.e. the objective function

    /// coefficients in the primal problem), and we looking for a

    /// ositive objective value. If there is such solution, that

    /// proofs the unsolvability of the primal problem, and if a

    /// feasible dual solution exists, then the unboundness of

    /// dual problem.

    ///

    /// \pre The problem is solved and the primal problem is infeasible.

    /// \note Some solvers does not provide dual ray calculation

    /// functions.

    Value dualRay(Row r) const { return _getDualRay(rows(id(r))); }

    /// Return the basis status of the column

    /// \see VarStatus

    VarStatus colStatus(Col c) const { return _getColStatus(cols(id(c))); }

    /// Return the basis status of the row

    /// \see VarStatus

    VarStatus rowStatus(Row r) const { return _getRowStatus(rows(id(r))); }

    ///The value of the objective function

    ///\return

    ///- \ref INF or -\ref INF means either infeasibility or unboundedness

    /// of the primal problem, depending on whether we minimize or maximize.

    ///- \ref NaN if no primal solution is found.

    ///- The (finite) objective value if an optimal solution is found.

    Value primal() const { return _getPrimalValue()+obj_const_comp;}

    ///@}

  protected:

  };

  /// \ingroup lp_group

  ///

  /// \brief Common base class for MIP solvers

  ///

  /// This class is an abstract base class for MIP solvers. This class

  /// provides a full interface for set and modify an MIP problem,

  /// solve it and retrieve the solution. You can use one of the

  /// descendants as a concrete implementation, or the \c Lp

  /// default MIP solver. However, if you would like to handle MIP

  /// solvers as reference or pointer in a generic way, you can use

  /// this class directly.

  class MipSolver : virtual public LpBase {

  public:

    /// The problem types for MIP problems

    enum ProblemType {

      /// = 0. Feasible solution hasn't been found (but may exist).

      UNDEFINED = 0,

      /// = 1. The problem has no feasible solution.

      INFEASIBLE = 1,

      /// = 2. Feasible solution found.

      FEASIBLE = 2,

      /// = 3. Optimal solution exists and found.

      OPTIMAL = 3,

      /// = 4. The cost function is unbounded.

      ///The Mip or at least the relaxed problem is unbounded.

      UNBOUNDED = 4

    };

    ///Allocate a new MIP problem instance

    virtual MipSolver* newSolver() const = 0;

    ///Make a copy of the MIP problem

    virtual MipSolver* cloneSolver() const = 0;

    ///\name Solve the MIP

    ///@{

    /// Solve the MIP problem at hand

    ///

    ///\return The result of the optimization procedure. Possible

    ///values and their meanings can be found in the documentation of

    ///\ref SolveExitStatus.

    SolveExitStatus solve() { return _solve(); }

    ///@}

    ///\name Set Column Type

    ///@{

    ///Possible variable (column) types (e.g. real, integer, binary etc.)

    enum ColTypes {

      /// = 0. Continuous variable (default).

      REAL = 0,

      /// = 1. Integer variable.

      INTEGER = 1

    };

    ///Sets the type of the given column to the given type

    ///Sets the type of the given column to the given type.

    ///

    void colType(Col c, ColTypes col_type) {

      _setColType(cols(id(c)),col_type);

    }

    ///Gives back the type of the column.

    ///Gives back the type of the column.

    ///

    ColTypes colType(Col c) const {

      return _getColType(cols(id(c)));

    }

    ///@}

    ///\name Obtain the Solution

    ///@{

/* -*- mode: C++; indent-tabs-mode: nil; -*-

 *

 * This file is a part of LEMON, a generic C++ optimization library.

 *

 * Copyright (C) 2003-2009

 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport

 * (Egervary Research Group on Combinatorial Optimization, EGRES).

 *

 * Permission to use, modify and distribute this software is granted

 * provided that this copyright notice appears in all copies. For

 * precise terms see the accompanying LICENSE file.

 *

 * This software is provided "AS IS" with no warranty of any kind,

 * express or implied, and with no claim as to its suitability for any

 * purpose.

 *

 */

#include <sstream>

#include <lemon/lp_skeleton.h>

#include "test_tools.h"

#include <lemon/tolerance.h>

#include <lemon/config.h>

#ifdef LEMON_HAVE_GLPK

#include <lemon/glpk.h>

#endif

#ifdef LEMON_HAVE_CPLEX

#include <lemon/cplex.h>

#endif

#ifdef LEMON_HAVE_SOPLEX

#include <lemon/soplex.h>

#endif

#ifdef LEMON_HAVE_CLP

#include <lemon/clp.h>

#endif

using namespace lemon;

void lpTest(LpSolver& lp)

{

  typedef LpSolver LP;

  std::vector<LP::Col> x(10);

  //  for(int i=0;i<10;i++) x.push_back(lp.addCol());

  lp.addColSet(x);

  lp.colLowerBound(x,1);

  lp.colUpperBound(x,1);

  lp.colBounds(x,1,2);

  std::vector<LP::Col> y(10);

  lp.addColSet(y);

  lp.colLowerBound(y,1);

  lp.colUpperBound(y,1);

  lp.colBounds(y,1,2);

  std::map<int,LP::Col> z;

  z.insert(std::make_pair(12,INVALID));

  z.insert(std::make_pair(2,INVALID));

  z.insert(std::make_pair(7,INVALID));

  z.insert(std::make_pair(5,INVALID));

  lp.addColSet(z);

  lp.colLowerBound(z,1);

  lp.colUpperBound(z,1);

  lp.colBounds(z,1,2);

  {

    LP::Expr e,f,g;

    LP::Col p1,p2,p3,p4,p5;

    LP::Constr c;

    p1=lp.addCol();

    p2=lp.addCol();

    p3=lp.addCol();

    p4=lp.addCol();

    p5=lp.addCol();

    e[p1]=2;

    *e=12;

    e[p1]+=2;

    *e+=12;

    e[p1]-=2;

    *e-=12;

    e=2;

    e=2.2;

    e=p1;

    e=f;

    e+=2;

    e+=2.2;

    e+=p1;

    e+=f;

    e-=2;

    e-=2.2;

    e-=p1;

    e-=f;

    e*=2;

    e*=2.2;

    e/=2;

    e/=2.2;

    e=((p1+p2)+(p1-p2)+(p1+12)+(12+p1)+(p1-12)+(12-p1)+

       (f+12)+(12+f)+(p1+f)+(f+p1)+(f+g)+

       (f-12)+(12-f)+(p1-f)+(f-p1)+(f-g)+

       2.2*f+f*2.2+f/2.2+

       2*f+f*2+f/2+

       2.2*p1+p1*2.2+p1/2.2+

       2*p1+p1*2+p1/2

       );

    c = (e  <= f  );

    c = (e  <= 2.2);

    c = (e  <= 2  );

    c = (e  <= p1 );

    c = (2.2<= f  );

    c = (2  <= f  );

    c = (p1 <= f  );

    c = (p1 <= p2 );

    c = (p1 <= 2.2);

    c = (p1 <= 2  );

    c = (2.2<= p2 );

    c = (2  <= p2 );

    c = (e  >= f  );

    c = (e  >= 2.2);

    c = (e  >= 2  );

    c = (e  >= p1 );

    c = (2.2>= f  );

    c = (2  >= f  );

    c = (p1 >= f  );

    c = (p1 >= p2 );

    c = (p1 >= 2.2);

    c = (p1 >= 2  );

    c = (2.2>= p2 );

    c = (2  >= p2 );

    c = (e  == f  );

    c = (e  == 2.2);

    c = (e  == 2  );

    c = (e  == p1 );

    c = (2.2== f  );

    c = (2  == f  );

    c = (p1 == f  );

    //c = (p1 == p2 );

    c = (p1 == 2.2);

    c = (p1 == 2  );

    c = (2.2== p2 );

    c = (2  == p2 );

    c = ((2 <= e) <= 3);

    c = ((2 <= p1) <= 3);

    c = ((2 >= e) >= 3);

    c = ((2 >= p1) >= 3);

    e[x[3]]=2;

    e[x[3]]=4;

    e[x[3]]=1;

    *e=12;

    lp.addRow(-LP::INF,e,23);

    lp.addRow(-LP::INF,3.0*(x[1]+x[2]/2)-x[3],23);

    lp.addRow(-LP::INF,3.0*(x[1]+x[2]*2-5*x[3]+12-x[4]/3)+2*x[4]-4,23);

    lp.addRow(x[1]+x[3]<=x[5]-3);

    lp.addRow((-7<=x[1]+x[3]-12)<=3);

    lp.addRow(x[1]<=x[5]);

    std::ostringstream buf;

    e=((p1+p2)+(p1-0.99*p2));

    //e.prettyPrint(std::cout);

    //(e<=2).prettyPrint(std::cout);

    double tolerance=0.001;

    e.simplify(tolerance);

    buf << "Coeff. of p2 should be 0.01";

    check(e[p2]>0, buf.str());

    tolerance=0.02;

    e.simplify(tolerance);

    buf << "Coeff. of p2 should be 0";

    check(const_cast<const LpSolver::Expr&>(e)[p2]==0, buf.str());

    //Test for clone/new

    LP* lpnew = lp.newSolver();

    LP* lpclone = lp.cloneSolver();

    delete lpnew;

    delete lpclone;

  }

  {

    LP::DualExpr e,f,g;

    LP::Row p1 = INVALID, p2 = INVALID, p3 = INVALID,

      p4 = INVALID, p5 = INVALID;

    e[p1]=2;

    e[p1]+=2;

    e[p1]-=2;

    e=p1;

    e=f;

    e+=p1;

    e+=f;

    e-=p1;

    e-=f;

    e*=2;

    e*=2.2;

    e/=2;

    e/=2.2;

    e=((p1+p2)+(p1-p2)+

       (p1+f)+(f+p1)+(f+g)+

       (p1-f)+(f-p1)+(f-g)+

       2.2*f+f*2.2+f/2.2+

       2*f+f*2+f/2+

       2.2*p1+p1*2.2+p1/2.2+

       2*p1+p1*2+p1/2

       );

  }

}

void solveAndCheck(LpSolver& lp, LpSolver::ProblemType stat,

                   double exp_opt) {

  using std::string;

  lp.solve();

  std::ostringstream buf;

  buf << "PrimalType should be: " << int(stat) << int(lp.primalType());

  check(lp.primalType()==stat, buf.str());

  if (stat ==  LpSolver::OPTIMAL) {

    std::ostringstream sbuf;

    sbuf << "Wrong optimal value (" << lp.primal() <<") with "

         << lp.solverName() <<"\n     the right optimum is " << exp_opt;

    check(std::abs(lp.primal()-exp_opt) < 1e-3, sbuf.str());

  }

}

void aTest(LpSolver & lp)

{

  typedef LpSolver LP;

 //The following example is very simple

  typedef LpSolver::Row Row;

  typedef LpSolver::Col Col;

  Col x1 = lp.addCol();

  Col x2 = lp.addCol();

  //Constraints

  Row upright=lp.addRow(x1+2*x2 <=1);

  lp.addRow(x1+x2 >=-1);

  lp.addRow(x1-x2 <=1);

  lp.addRow(x1-x2 >=-1);

  //Nonnegativity of the variables

  lp.colLowerBound(x1, 0);

  lp.colLowerBound(x2, 0);

  //Objective function

  lp.obj(x1+x2);

  lp.sense(lp.MAX);