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/**
\file aga.hpp
\brief asexual genetic algorithm method
*/
#ifndef AGA_METHOD
#define AGA_METHOD
#define OPT_HEADER
#include <core/optimizer.hpp>
//#include <blitz/array.h>
#include <limits>
#include <cstdlib>
#include <core/opt_traits.hpp>
#include <cassert>
#include <cmath>
#include <vector>
#include <algorithm>
/*
*
*/
#include <iostream>
using std::cout;
using std::endl;
namespace opt_utilities
{
template <typename rT,typename pT>
struct vp_pair
{
rT v;
pT p;
};
template <typename rT,typename pT>
class vp_comp
{
public:
bool operator()(const vp_pair<rT,pT>& x1,
const vp_pair<rT,pT>& x2)
{
return x1.v<x2.v;
}
};
/**
\brief Implement of the asexual genetic algorithm
2009A&A...501.1259C
http://adsabs.harvard.edu/abs/2009arXiv0905.3712C
\tparam rT return type of the object function
\tparam pT parameter type of the object function
*/
template <typename rT,typename pT>
class aga_method
:public opt_method<rT,pT>
{
public:
typedef pT array1d_type;
private:
int n1,n2,n0;
func_obj<rT,pT>* p_fo;
optimizer<rT,pT>* p_optimizer;
rT threshold;
pT lower_bound;
pT upper_bound;
typename element_type_trait<pT>::element_type decay_factor;
pT reproduction_box;
std::vector<vp_pair<rT,pT> > samples;
std::vector<pT> buffer;
private:
typename element_type_trait<pT>::element_type uni_rand
(typename element_type_trait<pT>::element_type x1,
typename element_type_trait<pT>::element_type x2)
{
return rand()/(double)RAND_MAX*(x2-x1)+x1;
}
private:
rT func(const pT& x)
{
assert(p_fo!=0);
return p_fo->eval(x);
}
public:
aga_method(int _n1,int _n2)
:threshold(1e-4),p_fo(0),p_optimizer(0),
n1(_n1),n2(_n2),samples(n1*n2+n1),n0(n1*n2+n1),
decay_factor(.999)
{
}
aga_method()
:threshold(1e-4),p_fo(0),p_optimizer(0),
n1(50),n2(20),samples(n1*n2+n1),n0(n1*n2+n1),
decay_factor(.999)
{
}
virtual ~aga_method()
{
};
aga_method(const aga_method<rT,pT>& rhs)
:threshold(rhs.threshold),
p_fo(rhs.p_fo),p_optimizer(rhs.p_optimizer),
n1(rhs.n1),n2(rhs.n2),
samples(rhs.samples),n0(rhs.n0)
{
}
aga_method<rT,pT>& operator=(const aga_method<rT,pT>& rhs)
{
threshold=rhs.threshold;
p_fo=rhs.p_fo;
p_optimizer=rhs.p_optimizer;
samples=rhs.samples;
n1=rhs.n1;
n2=rhs.n2;
n0=rhs.n0;
}
void set_decay_factor(typename element_type_trait<pT>::element_type _decay_factor)
{
decay_factor=_decay_factor;
}
opt_method<rT,pT>* do_clone()const
{
return new aga_method<rT,pT>(*this);
}
void do_set_start_point(const array1d_type& p)
{
for(int i=0;i<samples.size();++i)
{
// cout<<i<<" ";
resize(samples[i].p,get_size(p));
// std::cout<<samples[i].p.size()<<std::endl;;
for(int j=0;j<get_size(p);++j)
{
set_element(samples[i].p,j,
uni_rand(get_element(lower_bound,j),
get_element(upper_bound,j))
);
}
}
}
array1d_type do_get_start_point()const
{
return array1d_type();
}
void do_set_lower_limit(const array1d_type& p)
{
opt_eq(lower_bound,p);
}
array1d_type do_get_lower_limit()const
{
return lower_bound;
}
void do_set_upper_limit(const array1d_type& p)
{
opt_eq(upper_bound,p);
}
array1d_type do_get_upper_limit()const
{
return upper_bound;
}
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();
}
bool iter()
{
rT sum2=0;
rT sum=0;
for(int i=0;i<samples.size();++i)
{
samples[i].v=func(samples[i].p);
sum2+=samples[i].v*samples[i].v;
sum+=samples[i].v;
}
std::sort(samples.begin(),samples.end(),vp_comp<rT,pT>());
if(sum2/samples.size()-pow(sum/samples.size(),2)<threshold)
{
return false;
}
pT lb(get_size(samples[0].p));
pT ub(get_size(samples[0].p));
for(int i=0;i<n2;++i)
{
pT p(samples[i].p);
for(int j=0;j<get_size(p);++j)
{
if(i==0)
{
ub[j]=p[j];
lb[j]=p[j];
}
ub[j]=std::max(ub[j],p[j]);
lb[j]=std::min(lb[j],p[j]);
set_element(p,j,
get_element(p,j)+
uni_rand(-get_element(reproduction_box,j),
get_element(reproduction_box,j)));
if(get_element(p,j)>get_element(upper_bound,j))
{
set_element(p,j,get_element(upper_bound,j));
}
if(get_element(p,j)<get_element(lower_bound,j))
{
set_element(p,j,get_element(lower_bound,j));
}
}
buffer[i]=p;
}
for(int i=0;i<n1;++i)
{
for(int j=0;j<n2;++j)
{
pT p(samples[i].p);
for(int k=0;k<get_size(p);++k)
{
set_element(samples[i*n2+j+n1].p,k,
(get_element(samples[i].p,k)+
get_element(buffer[j],k))/2.);
ub[k]=std::max(ub[k],samples[i*n2+j+n1].p[k]);
lb[k]=std::min(lb[k],samples[i*n2+j+n1].p[k]);
}
}
}
double n_per_dim=pow((double)n0,1./get_size(lower_bound));
for(int i=0;i<get_size(reproduction_box);++i)
{
// set_element(reproduction_box,i,
//get_element(reproduction_box,i)*decay_factor);
set_element(reproduction_box,i,
(get_element(ub,i)-
get_element(ub,i))/n_per_dim);
}
return true;
}
pT do_optimize()
{
srand(time(0));
buffer.resize(n2);
double n_per_dim=pow((double)n0,1./get_size(lower_bound));
resize(reproduction_box,get_size(lower_bound));
for(int i=0;i<get_size(lower_bound);++i)
{
set_element(reproduction_box,i,
(get_element(upper_bound,i)-
get_element(lower_bound,i))/n_per_dim);
}
while(iter()){}
return samples.begin()->p;
}
};
}
#endif
//EOF
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