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Comparing trunk/OOPSE/libmdtools/NLModel.hpp (file contents):
Revision 1000 by tim, Fri Jan 30 21:47:22 2004 UTC vs.
Revision 1015 by tim, Tue Feb 3 22:54:52 2004 UTC

# Line 3 | Line 3
3  
4   #include <vector>
5   #include <utility>
6 + #include <math.h>
7  
8   #include "SymMatrix.hpp"
9   #include "Functor.hpp"
10 + #include "ConstraintList.hpp"
11  
12   using namespace std;
13  
14  
15 < typedef enum FDType {backward, forward, central} ;
15 > typedef enum  {backward, forward, central} FDType;
16  
17   // special property of nonlinear object function
18 < typedef enum NLOFProp{linear, quadratic, general};
18 > typedef enum {linear, quadratic, general} NLOFProp;
19  
20   //abstract class of nonlinear optimization model
21   class NLModel{
# Line 22 | Line 24 | class NLModel{
24      virtual ~NLModel() {  if (constraints != NULL) delete constraints;}
25  
26      virtual void setX(const vector<double>& x)= 0;
27 +    virtual vector<double> getX() = 0;
28  
29 <    virtual int  getDim() const = 0;
29 >    virtual void setF(double f) = 0;
30 >    virtual double getF() = 0;
31  
32 +    virtual int  getDim() {return ndim;}
33 +
34      bool hasConstraints() {  return constraints == NULL ? false : true;}
35 <    int getConsType() {  return constrains->getConsType();}
35 >    int getConsType() {  return constraints->getConsType();}
36  
37      virtual double calcF()  = 0;
38      virtual double calcF(const vector<double>& x)  = 0;
# Line 45 | Line 51 | class NLModel{
51    protected:
52      ConstraintList* constraints;       //constraints of nonlinear optimization model
53      int numOfFunEval;                  //number of function evaluation
54 +    int ndim;
55  
56   #ifdef IS_MPI
57      bool mpiInitFlag;
# Line 65 | Line 72 | class NLModel0 : public NLModel{
72      NLModel0(int dim,  ConstraintList* cons = NULL);
73      ~NLModel0() {}
74  
75 <    virtual void setX(const vector<double>& x);
75 >    virtual void setX(const vector<double>& x) {currentX = x;}
76 >    vector<double>  getX() {return currentX;}
77  
78 +    void setF(double f) {currentF = f;}
79 +    double getF() {return currentF;}
80 +
81      //Using finite difference methods to approximate the gradient
82      //It is inappropriate to apply these methods in large scale problem
83      
84 <    vector<double> BackwardGrad(const vector<double>& x, double& fx, vector<double>& grad);
85 <    vector<double> ForwardGrad(const vector<double>& x, double& fx, vector<double>& grad);
86 <    vector<double> CentralGrad(const vector<double>& x, double& fx, vector<double>& grad);
84 >    vector<double> BackwardGrad(const vector<double>& x, double& fx, vector<double>& grad, const vector<double>& h);
85 >    vector<double> ForwardGrad(const vector<double>& x, double& fx, vector<double>& grad, const vector<double>& h);
86 >    vector<double> CentralGrad(const vector<double>& x, double& fx, vector<double>& grad, const vector<double>& h);
87  
88      //Using finite difference methods to approximate the hessian
89      //It is inappropriate to apply this method in large scale problem
90 <    virtual SymMatrix FiniteHessian(vector<double>& x, double fx, vector<double>& h);
91 <
90 >    //virtual SymMatrix FiniteHessian(vector<double>& x, double fx, vector<double>& h);
91 >    SymMatrix FiniteHessian(vector<double>& x, double fx, vector<double>& h);
92    protected:
93  
94      FDType fdType;
95      vector<double> currentX;
96 <    double curretF;
96 >    double currentF;
97   };
98  
99   //concrete class of nonlinear optimization model without derivatives
# Line 95 | Line 106 | class ConcreteNLMode0 : public NLModel0{
106      ConcreteNLMode0(int dim, ConstraintList* cons = NULL);
107  
108      virtual double calcF();
109 <    virtual double calcF(const vector<double>& x);
109 >    virtual double calcF(vector<double>& x);
110      virtual vector<double> calcGrad();
111      virtual vector<double> calcGrad(vector<double>& x);
112      virtual SymMatrix calcHessian() ;
# Line 114 | Line 125 | class NLModel1 : public NLModel0{
125      
126      //Using finite difference methods to approximate the hessian
127      //It is inappropriate to apply this method in large scale problem    
128 <    virtual SymMatrix FiniteHessian(vector<double>& x, double fx, vector<double>& h);
129 <    
128 >    virtual SymMatrix FiniteHessian(vector<double>& x, vector<double>& h);
129 >
130 >    void setGrad(vector<double>& grad) {currentGrad = grad;}
131 >    vector<double> getGrad() {return currentGrad;}
132    protected:
133  
134      vector<double> currentGrad;
# Line 130 | Line 143 | class ConcreteNLMode1 : NLModel1{
143      ConcreteNLMode1(int dim, ConstraintList* cons = NULL);
144      
145      virtual double calcF();
146 <    virtual double calcF(const vector<double>& x);
146 >    virtual double calcF(vector<double>& x);
147      virtual vector<double> calcGrad();
148 <    virtual vector<double> calcGrad(vector<double>& x);
148 >    virtual vector<double> calcGrad( vector<double>& x);
149      virtual SymMatrix calcHessian() ;
150      virtual SymMatrix calcHessian(vector<double>& x) ;
151  
# Line 159 | Line 172 | class ConcreteNLModel2 : public NLModel2{
172      ConcreteNLModel2(int dim, ConstraintList* cons = NULL);
173      
174      virtual double calcF();
175 <    virtual double calcF(const vector<double>& x);
175 >    virtual double calcF(vector<double>& x);
176      virtual vector<double> calcGrad();
177      virtual vector<double> calcGrad(vector<double>& x);
178      virtual SymMatrix calcHessian() ;

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