From f945de88af78d98ba63b7ac91df5d659406a4cd3 Mon Sep 17 00:00:00 2001
From: astrojhgu <astrojhgu@ed2142bd-67ad-457f-ba7c-d818d4011675>
Date: Tue, 18 Aug 2009 13:58:35 +0000
Subject: git-svn-id: file:///home/svn/opt_utilities@43
 ed2142bd-67ad-457f-ba7c-d818d4011675

---
 methods/aga/aga.hpp | 249 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 249 insertions(+)
 create mode 100644 methods/aga/aga.hpp

diff --git a/methods/aga/aga.hpp b/methods/aga/aga.hpp
new file mode 100644
index 0000000..f5edff3
--- /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
-- 
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