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authorastrojhgu <astrojhgu@ed2142bd-67ad-457f-ba7c-d818d4011675>2009-08-18 13:58:35 +0000
committerastrojhgu <astrojhgu@ed2142bd-67ad-457f-ba7c-d818d4011675>2009-08-18 13:58:35 +0000
commitf945de88af78d98ba63b7ac91df5d659406a4cd3 (patch)
tree18d033b5df131430355d4b8e5008674e6a2310b3 /methods
parent690ef57ffb01349cece73b10ae45a12581c60abf (diff)
downloadopt-utilities-f945de88af78d98ba63b7ac91df5d659406a4cd3.tar.bz2
git-svn-id: file:///home/svn/opt_utilities@43 ed2142bd-67ad-457f-ba7c-d818d4011675
Diffstat (limited to 'methods')
-rw-r--r--methods/aga/aga.hpp249
1 files changed, 249 insertions, 0 deletions
diff --git a/methods/aga/aga.hpp b/methods/aga/aga.hpp
new file mode 100644
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--- /dev/null
+++ b/methods/aga/aga.hpp
@@ -0,0 +1,249 @@
+#ifndef AGA_METHOD
+#define AGA_METHOD
+#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;
+ }
+ };
+
+ 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));
+ 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))
+ );
+
+ }
+ }
+
+ }
+
+ void do_set_lower_limit(const array1d_type& p)
+ {
+ opt_eq(lower_bound,p);
+ }
+
+
+ void do_set_upper_limit(const array1d_type& p)
+ {
+ opt_eq(upper_bound,p);
+ }
+
+
+ void do_set_precision(rT t)
+ {
+ threshold=t;
+ }
+
+ 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<double,std::vector<double> >());
+ if(sum2/samples.size()-pow(sum/samples.size(),2)<threshold)
+ {
+ return false;
+ }
+
+ for(int i=0;i<n2;++i)
+ {
+ pT p(samples[i].p);
+ for(int j=0;j<get_size(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.);
+ }
+ }
+ }
+ for(int i=0;i<get_size(reproduction_box);++i)
+ {
+ set_element(reproduction_box,i,
+ get_element(reproduction_box,i)*decay_factor);
+ }
+ 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