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/**
\file conjugate_gradient.hpp
\brief powerll optimization method
\author Junhua Gu
*/
#ifndef CONJUGATE_GRADIENT
#define CONJUGATE_GRADIENT
#define OPT_HEADER
#include <core/optimizer.hpp>
//#include <blitz/array.h>
#include <limits>
#include <cassert>
#include <cmath>
#include "../linmin/linmin.hpp"
#include <math/num_diff.hpp>
#include <algorithm>
#include <iostream>
namespace opt_utilities
{
/**
\brief Impliment of an optimization method
\tparam rT return type of the object function
\tparam pT parameter type of the object function
*/
template <typename rT,typename pT>
class conjugate_gradient
:public opt_method<rT,pT>
{
public:
typedef pT array1d_type;
typedef rT T;
private:
func_obj<rT,pT>* p_fo;
optimizer<rT,pT>* p_optimizer;
volatile bool bstop;
//typedef blitz::Array<rT,2> array2d_type;
const char* do_get_type_name()const
{
return "conjugate gradient method";
}
private:
array1d_type start_point;
array1d_type end_point;
private:
rT threshold;
array1d_type g;
array1d_type h;
array1d_type xi;
private:
rT func(const pT& x)
{
assert(p_fo!=0);
return p_fo->eval(x);
}
private:
void clear_xi()
{
}
void init_xi(int n)
{
clear_xi();
g=array1d_type(n);
h=array1d_type(n);
xi=array1d_type(n);
}
void cg(array1d_type& p,const T ftol,
int& iter,T& fret)
{
const int ITMAX=200;
const T EPS=std::numeric_limits<T>::epsilon();
int j,its;
int n=p.size();
T gg,gam,fp,dgg;
fp=func(p);
xi=gradient(*p_fo,p);
for(j=0;j<n;++j)
{
g[j]=-xi[j];
xi[j]=h[j]=g[j];
}
for(its=1;its<=ITMAX;++its)
{
iter=its;
linmin(p,xi,fret,*p_fo);
//std::cerr<<"######:"<<its<<"\t"<<abs(fret-fp)/(abs(fret)+fabs(fp)+EPS)<<std::endl;
if(2.0*abs(fret-fp)<=ftol*(abs(fret)+fabs(fp)+EPS))
{
return;
}
fp=func(p);
xi=gradient(*p_fo,p);
dgg=gg=0;
for(j=0;j<n;++j)
{
gg+=g[j]*g[j];
//dgg+=(xi[j]+g[j])*xi[j];
dgg+=xi[j]*xi[j];
}
std::cerr<<its<<"\t"<<gg<<std::endl;
if(gg==0.0)
{
return;
}
gam=dgg/gg;
for(j=0;j<n;++j)
{
g[j]=-xi[j];
xi[j]=h[j]=g[j]+gam*h[j];
}
}
std::cerr<<"Too many iterations in cg"<<std::endl;
}
public:
conjugate_gradient()
:threshold(1e-4),g(0),h(0),xi(0)
{}
virtual ~conjugate_gradient()
{
clear_xi();
};
conjugate_gradient(const conjugate_gradient<rT,pT>& rhs)
:opt_method<rT,pT>(rhs),p_fo(rhs.p_fo),p_optimizer(rhs.p_optimizer),
start_point(rhs.start_point),
end_point(rhs.end_point),
threshold(rhs.threshold),g(0),h(0),xi(0)
{
}
conjugate_gradient<rT,pT>& operator=(const conjugate_gradient<rT,pT>& rhs)
{
threshold=rhs.threshold;
p_fo=rhs.p_fo;
p_optimizer=rhs.p_optimizer;
start_point=rhs.start_point;
end_point=rhs.end_point;
threshold=rhs.threshold;
}
opt_method<rT,pT>* do_clone()const
{
return new conjugate_gradient<rT,pT>(*this);
}
void do_set_start_point(const array1d_type& p)
{
resize(start_point,get_size(p));
opt_eq(start_point,p);
}
array1d_type do_get_start_point()const
{
return start_point;
}
void do_set_lower_limit(const array1d_type& p)
{}
void do_set_upper_limit(const array1d_type& p)
{}
void do_set_precision(rT t)
{
threshold=t;
}
rT do_get_precision()const
{
return threshold;
}
void do_set_optimizer(optimizer<rT,pT>& o)
{
p_optimizer=&o;
p_fo=p_optimizer->ptr_func_obj();
}
pT do_optimize()
{
bstop=false;
init_xi((int)get_size(start_point));
int iter=100;
opt_eq(end_point,start_point);
rT fret;
#if 0
for(int i=0;i<get_size(start_point);++i)
{
array1d_type direction(start_point.size());
direction[i]=1;
linmin(end_point,direction,fret,(*p_fo));
}
#endif
cg(end_point,threshold,iter,fret);
return end_point;
}
void do_stop()
{
bstop=true;
}
};
}
#endif
//EOF
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