ITK  4.6.0
Insight Segmentation and Registration Toolkit
itkSPSAOptimizer.h
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18 #ifndef __itkSPSAOptimizer_h
19 #define __itkSPSAOptimizer_h
20 
23 
24 namespace itk
25 {
45 {
46 public:
47 
53 
55  itkNewMacro(Self);
56 
59 
61  typedef enum {
67 
69  virtual void AdvanceOneStep(void);
70 
72  virtual void StartOptimization(void) ITK_OVERRIDE;
73 
76  void ResumeOptimization(void);
77 
80  void StopOptimization(void);
81 
83  virtual MeasureType GetValue(void) const;
84 
86  virtual MeasureType GetValue(const ParametersType & parameters) const;
87 
101  virtual void GuessParameters(
102  SizeValueType numberOfGradientEstimates,
103  double initialStepSize);
104 
106  itkGetConstMacro(CurrentIteration, SizeValueType);
107 
109  itkGetConstMacro(StopCondition, StopConditionType);
110 
112  itkGetConstMacro(LearningRate, double);
113 
115  itkGetConstMacro(GradientMagnitude, double);
116 
118  itkGetConstReferenceMacro(Gradient, DerivativeType);
119 
121  itkSetMacro(Sa, double);
122  itkGetConstMacro(Sa, double);
123  // For backward compatibility
124  void Seta(double a) { SetSa(a); }
125  double Geta() { return GetSa(); }
127 
129  itkSetMacro(Sc, double);
130  itkGetConstMacro(Sc, double);
131  // For backward compatibility
132  void Setc(double c) { SetSc(c); }
133  double Getc() { return GetSc(); }
135 
137  itkSetMacro(A, double);
138  itkGetConstMacro(A, double);
140 
142  itkSetMacro(Alpha, double);
143  itkGetConstMacro(Alpha, double);
145 
147  itkSetMacro(Gamma, double);
148  itkGetConstMacro(Gamma, double);
150 
152  itkGetConstMacro(Maximize, bool);
153  itkSetMacro(Maximize, bool);
154  itkBooleanMacro(Maximize);
155  bool GetMinimize() const
156  { return !m_Maximize; }
157  void SetMinimize(bool v)
158  { this->SetMaximize(!v); }
159  void MinimizeOn()
160  { this->MaximizeOff(); }
161  void MinimizeOff()
162  { this->MaximizeOn(); }
164 
170  itkSetMacro(NumberOfPerturbations, SizeValueType);
171  itkGetConstMacro(NumberOfPerturbations, SizeValueType);
173 
185  itkGetConstMacro(StateOfConvergence, double);
186 
188  itkSetMacro(StateOfConvergenceDecayRate, double);
189  itkGetConstMacro(StateOfConvergenceDecayRate, double);
191 
193  itkSetMacro(MinimumNumberOfIterations, SizeValueType);
194  itkGetConstMacro(MinimumNumberOfIterations, SizeValueType);
196 
199  itkGetConstMacro(MaximumNumberOfIterations, SizeValueType);
201 
203  itkSetMacro(Tolerance, double);
204  itkGetConstMacro(Tolerance, double);
206 
208  virtual const std::string GetStopConditionDescription() const ITK_OVERRIDE;
209 
210 protected:
211 
212  SPSAOptimizer();
213  virtual ~SPSAOptimizer() {}
214 
216  virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
217 
220 
222 
224 
225  bool m_Stop;
226 
228 
230 
232 
235 
237  virtual double Compute_a(SizeValueType k) const;
238 
243  virtual double Compute_c(SizeValueType k) const;
244 
246  virtual void GenerateDelta(const unsigned int spaceDimension);
247 
252  virtual void ComputeGradient(
253  const ParametersType & parameters,
254  DerivativeType & gradient);
255 
256 private:
257 
258  SPSAOptimizer(const Self &); // purposely not implemented
259  void operator=(const Self &); // purposely not implemented
260 
265  double m_Tolerance;
269 
271  double m_Sa;
272  double m_Sc;
273  double m_A;
274  double m_Alpha;
275  double m_Gamma;
276 }; // end class SPSAOptimizer
277 } // end namespace itk
278 
279 #endif // end #ifndef __itkSPSAOptimizer_h
SmartPointer< const Self > ConstPointer
Array class with size defined at construction time.
Definition: itkArray.h:50
virtual void GenerateDelta(const unsigned int spaceDimension)
virtual void SetSa(double _arg)
Light weight base class for most itk classes.
void Setc(double c)
SPSAOptimizer Self
virtual void MaximizeOn()
virtual void ComputeGradient(const ParametersType &parameters, DerivativeType &gradient)
void ResumeOptimization(void)
virtual double Compute_c(SizeValueType k) const
void SetMinimize(bool v)
virtual void AdvanceOneStep(void)
An optimizer based on simultaneous perturbation...
virtual void GuessParameters(SizeValueType numberOfGradientEstimates, double initialStepSize)
This class is a base for the Optimization methods that optimize a single valued function.
StopConditionType m_StopCondition
DerivativeType m_Delta
virtual double GetSa() const
void Seta(double a)
unsigned long SizeValueType
Definition: itkIntTypes.h:143
virtual void StartOptimization(void) ITK_OVERRIDE
virtual const std::string GetStopConditionDescription() const ITK_OVERRIDE
virtual void SetMaximize(bool _arg)
void operator=(const Self &)
double m_StateOfConvergenceDecayRate
SizeValueType m_CurrentIteration
SmartPointer< Self > Pointer
virtual MeasureType GetValue(void) const
virtual double GetSc() const
SizeValueType m_NumberOfPerturbations
virtual double Compute_a(SizeValueType k) const
DerivativeType m_Gradient
virtual void SetSc(double _arg)
Statistics::MersenneTwisterRandomVariateGenerator::Pointer m_Generator
SizeValueType m_MinimumNumberOfIterations
bool GetMinimize() const
virtual void MaximizeOff()
SizeValueType m_MaximumNumberOfIterations
SingleValuedNonLinearOptimizer Superclass
Control indentation during Print() invocation.
Definition: itkIndent.h:49
virtual void PrintSelf(std::ostream &os, Indent indent) const ITK_OVERRIDE
void StopOptimization(void)