aimsalgo  5.0.5
Neuroimaging image processing
optimizer.h
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33 
34 
35 #ifndef AIMS_OPTIMIZATION_OPTIMIZER_H
36 #define AIMS_OPTIMIZATION_OPTIMIZER_H
37 
38 #include <aims/math/mathelem.h>
39 #include <aims/vector/vector.h>
42 
43 //
44 // class Optimizer
45 //
46 
47 template <class T, int D>
49 public :
51  virtual ~OptimizerProbe() {}
52 
53  virtual OptimizerProbe * clone() { return new OptimizerProbe ; }
54  virtual void iteration( const AimsVector<T,D> &,
56  const float * = 0) {}
57  virtual void test( const AimsVector<T,D> &,
59  const float * = 0) {}
60  virtual void end() {}
61 } ;
62 
63 
64 template <class T, int D>
65 class Optimizer
66 {
67 public:
68  Optimizer( const ObjectiveFunc< T,D >& func, T error,
69  OptimizerProbe<T, D> * probe = 0 ) :
70  _func( func ), _error( error )
71  {
72  if ( probe != 0 )
73  _probe = probe->clone() ;
74  else
75  _probe = new OptimizerProbe<T,D>() ;
76  }
77 
78  virtual ~Optimizer() { }
79 
81  const AimsVector<T,D> & )
82  { return AimsVector<T,D>( (T)0 ); }
83 
84  void setProbe( OptimizerProbe<T,D> * probe )
85  { _probe = probe->clone() ; }
86 
87 protected:
89  T _error;
90 
92 };
93 
94 #endif
virtual AimsVector< T, D > doit(const AimsVector< T, D > &, const AimsVector< T, D > &)
Definition: optimizer.h:80
virtual void iteration(const AimsVector< T, D > &, const carto::AttributedObject &, const float *=0)
Definition: optimizer.h:54
OptimizerProbe< T, D > * _probe
Definition: optimizer.h:91
virtual ~Optimizer()
Definition: optimizer.h:78
Optimizer(const ObjectiveFunc< T, D > &func, T error, OptimizerProbe< T, D > *probe=0)
Definition: optimizer.h:68
void setProbe(OptimizerProbe< T, D > *probe)
Definition: optimizer.h:84
const ObjectiveFunc< T, D > & _func
Definition: optimizer.h:88
virtual OptimizerProbe * clone()
Definition: optimizer.h:53
virtual void test(const AimsVector< T, D > &, const carto::AttributedObject &, const float *=0)
Definition: optimizer.h:57
virtual ~OptimizerProbe()
Definition: optimizer.h:51
virtual void end()
Definition: optimizer.h:60