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/* minimize
Tim Behrens, FMRIB Image Analysis Group
Copyright (C) 1999-2000 University of Oxford */
/* CCOPYRIGHT */
#if !defined(minimize_h)
#define minimize_h
#include <string>
#include <iostream>
#include <fstream>
//#include <unistd.h>
#include <vector>
#include <algorithm>
#include "newmatap.h"
#include "newmatio.h"
#include "miscmaths.h"
#define WANT_STREAM
#define WANT_MATH
using namespace MISCMATHS;
using namespace NEWMAT;
using namespace std;
///////////////////////////////////////////////////////
//fminsearch.m
namespace MISCMATHS {
class pair_comparer
{
public:
bool operator()(const pair<float,ColumnVector>& p1,const pair<float,ColumnVector>& p2) const
{
return p1.first < p2.first;
}
};
class EvalFunction;
class gEvalFunction;
float diff1(const ColumnVector& x, const EvalFunction& func, int i,float h,int errorord=4);// finite diff derivative
float diff2(const ColumnVector& x, const EvalFunction& func, int i,float h,int errorord=4);// finite diff 2nd derivative
float diff2(const ColumnVector& x, const EvalFunction& func, int i,int j,float h,int errorord=4);// finite diff cross derivative
ReturnMatrix gradient(const ColumnVector& x, const EvalFunction& func,float h,int errorord=4);// finite diff derivative vector
ReturnMatrix hessian(const ColumnVector& x, const EvalFunction& func,float h,int errorord=4);// finite diff hessian
void minsearch(ColumnVector& x, const EvalFunction& func, ColumnVector& paramstovary);
void scg(ColumnVector& x, const gEvalFunction& func, ColumnVector& paramstovary, float tol = 0.0000001, float eps=1e-16, int niters=500);
class EvalFunction
{//Function where gradient is not analytic (or you are too lazy to work it out) (required for fminsearch)
public:
EvalFunction(){}
virtual float evaluate(const ColumnVector& x) const = 0; //evaluate the function
virtual ~EvalFunction(){};
virtual void minimize(ColumnVector& x)
{
ColumnVector paramstovary(x.Nrows());
paramstovary = 1;
minsearch(x,*this,paramstovary);
}
virtual void minimize(ColumnVector& x, ColumnVector& paramstovary)
{
minsearch(x,*this,paramstovary);
}
private:
const EvalFunction& operator=(EvalFunction& par);
EvalFunction(const EvalFunction&);
};
class gEvalFunction : public EvalFunction
{//Function where gradient is analytic (required for scg)
public:
gEvalFunction() : EvalFunction(){}
// evaluate is inherited from EvalFunction
virtual ReturnMatrix g_evaluate(const ColumnVector& x) const = 0; //evaluate the gradient
virtual ~gEvalFunction(){};
virtual void minimize(ColumnVector& x)
{
ColumnVector paramstovary(x.Nrows());
paramstovary = 1;
scg(x,*this,paramstovary);
}
virtual void minimize(ColumnVector& x, ColumnVector& paramstovary)
{
scg(x,*this,paramstovary);
}
private:
const gEvalFunction& operator=(gEvalFunction& par);
gEvalFunction(const gEvalFunction&);
};
}
#endif
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