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diff --git a/newstructure/thirdparty/linux/include/coin/BonQuadRow.hpp b/newstructure/thirdparty/linux/include/coin/BonQuadRow.hpp
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+/// (C) Copyright International Business Machines Corporation 2007
+// All Rights Reserved.
+// This code is published under the Eclipse Public License.
+//
+// Authors :
+// Pierre Bonami, International Business Machines Corporation
+//
+// Date : 10/06/2007
+
+#ifndef BonQuadRow_H
+#define BonQuadRow_H
+
+#include "CoinPackedVector.hpp"
+#include "BonTMatrix.hpp"
+#include "BonQuadCut.hpp"
+
+namespace Bonmin{
+
+  /** Store column and row of the entry.*/
+  typedef std::pair<int, int> matEntry;
+  /** Store the number of times entry is used and its index in the matrix.*/
+  typedef std::pair<int, int> matIdx;
+#if HAS_HASH_MAP
+  typedef std::has_map<matEntry, matIdx, std::hash< matEntry> > AdjustableMat;
+#else
+  typedef std::map<matEntry, matIdx> AdjustableMat;
+#endif
+
+/** Stores a quadratic row of the form l < c + ax + x^T Q x < u. 
+    Does computation usefull for nlp-solver.
+    It can only be initialized from a QuadCut.*/
+class QuadRow {
+ public:
+ /** Default constructor.*/
+ QuadRow();
+
+ /** Copy constructor.*/
+ QuadRow(const QuadRow & other);
+
+ /** Assignment operator.*/
+ QuadRow& operator=(const QuadRow& rhs);
+
+ /** Constructor from a quadratic cut.*/
+ QuadRow(const QuadCut &cut);
+
+ /** Assignment form a quadrattic &cut.*/
+ QuadRow& operator=(const QuadCut & rhs);
+
+ /** Constructor from a linear cut.*/
+ QuadRow(const OsiRowCut &cut);
+
+ /** Assignment form a linear &cut.*/
+ QuadRow& operator=(const OsiRowCut & rhs);
+
+ /** Evaluate quadratic form.*/
+ double eval_f(const double *x, bool new_x);
+
+ /** Get number of non-zeroes in the gradiant.*/
+ int nnz_grad();
+ /** Get structure of gradiant */
+  void gradiant_struct(const int nnz, int * indices, bool offset);
+ /** Evaluate gradiant of quadratic form.*/
+ void eval_grad(const int nnz, const double * x, bool new_x, double * values);
+
+ /** number of non-zeroes in hessian. */
+ int nnz_hessian(){
+   return Q_.nnz_;}
+
+ /** Says if the constraint is linear.*/
+ bool isLinear(){
+   return Q_.nnz_ == 0;}
+
+ /** Return hessian value (i.e. Q_).*/
+ void eval_hessian(double lambda, double * values);
+
+ /** Add row to a bigger hessian.*/
+  void add_to_hessian(AdjustableMat &H, bool offset); 
+
+ /** Remove row from a bigger hessian.*/ 
+  void remove_from_hessian(AdjustableMat &H);
+/** Print quadratic constraint.*/
+void print();
+
+ private:
+ /** Initialize once quadratic form is know.*/
+ void initialize();
+
+ /** Does internal work to evaluate gradiant of this in x.*/
+ void internal_eval_grad(const double *x);
+
+ /** lower bound.*/
+ double lb_;
+ /** upper bound.*/
+ double ub_;
+ /** Constant term.*/
+ double c_;
+ /** linear term in sparse storage.*/
+ CoinPackedVector a_;
+ /** Quadratic term.*/
+ TMat Q_;
+
+
+#if HAS_HASH_MAP
+  typedef  std::has_map<int, std::pair<double, double >, std::hash<int> > gStore;
+#else
+  typedef std::map<int, std::pair<double, double> > gStore;
+#endif
+
+ gStore g_;
+ /** To have fast access to gradiant entries for a_.*/
+ std::vector<gStore::iterator> a_grad_idx_;
+ /** To have fast access to gradient entries for rows Q_*/
+ std::vector<gStore::iterator> Q_row_grad_idx_;
+ /** To have fast access to gradient entries for cols Q_*/
+ std::vector<gStore::iterator> Q_col_grad_idx_;
+ /** To have fast access to entries in full hessian of Q_*/
+ std::vector<AdjustableMat::iterator> Q_hessian_idx_;
+ /** Flag indicating if gradiant has been evaluated.*/
+ bool grad_evaled_;
+};
+}//End Bonmin namespace
+#endif