1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
|
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkSingleValuedNonLinearVnlOptimizer_h
#define itkSingleValuedNonLinearVnlOptimizer_h
#include "itkSingleValuedNonLinearOptimizer.h"
#include "itkSingleValuedVnlCostFunctionAdaptor.h"
#include "itkCommand.h"
#include "ITKOptimizersExport.h"
namespace itk
{
/** \class SingleValuedNonLinearVnlOptimizer
* \brief This class is a base for the Optimization methods that
* optimize a single valued function.
*
* It is an Adaptor class for optimizers provided by the vnl library
*
* \ingroup Numerics Optimizers
* \ingroup ITKOptimizers
*/
class ITKOptimizers_EXPORT SingleValuedNonLinearVnlOptimizer : public SingleValuedNonLinearOptimizer
{
public:
ITK_DISALLOW_COPY_AND_MOVE(SingleValuedNonLinearVnlOptimizer);
/** Standard class type aliases. */
using Self = SingleValuedNonLinearVnlOptimizer;
using Superclass = SingleValuedNonLinearOptimizer;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(SingleValuedNonLinearVnlOptimizer);
/** Command observer that will interact with the ITKVNL cost-function
* adaptor in order to generate iteration events. This will allow to overcome
* the limitation of VNL optimizers not offering callbacks for every
* iteration */
using CommandType = ReceptorMemberCommand<Self>;
/** Set the cost Function. This method has to be overloaded
* by derived classes because the CostFunctionAdaptor requires
* to know the number of parameters at construction time. This
* number of parameters is obtained at run-time from the itkCostFunction.
* As a consequence each derived optimizer should construct its own
* CostFunctionAdaptor when overloading this method */
void
SetCostFunction(SingleValuedCostFunction * costFunction) override = 0;
/** Methods to define whether the cost function will be maximized or
* minimized. By default the VNL amoeba optimizer is only a minimizer.
* Maximization is implemented here by notifying the CostFunctionAdaptor
* which in its turn will multiply the function values and its derivative by
* -1.0. */
itkGetConstReferenceMacro(Maximize, bool);
itkSetMacro(Maximize, bool);
itkBooleanMacro(Maximize);
bool
GetMinimize() const
{
return !m_Maximize;
}
void
SetMinimize(bool v)
{
this->SetMaximize(!v);
}
void
MinimizeOn()
{
this->MaximizeOff();
}
void
MinimizeOff()
{
this->MaximizeOn();
}
/** Return Cached Values. These method have the advantage of not triggering a
* recomputation of the metric value, but it has the disadvantage of returning
* a value that may not be the one corresponding to the current parameters. For
* GUI update purposes, this method is a good option, for mathematical
* validation you should rather call GetValue(). */
itkGetConstReferenceMacro(CachedValue, MeasureType);
itkGetConstReferenceMacro(CachedDerivative, DerivativeType);
itkGetConstReferenceMacro(CachedCurrentPosition, ParametersType);
/** Returns true if derived optimizer supports using scales.
* For optimizers that do not support scaling, this
* default function is overridden to return false.*/
virtual bool
CanUseScales() const
{
return true;
}
protected:
SingleValuedNonLinearVnlOptimizer();
~SingleValuedNonLinearVnlOptimizer() override;
using CostFunctionAdaptorType = SingleValuedVnlCostFunctionAdaptor;
void
SetCostFunctionAdaptor(CostFunctionAdaptorType * adaptor);
const CostFunctionAdaptorType *
GetCostFunctionAdaptor() const;
CostFunctionAdaptorType *
GetCostFunctionAdaptor();
/** The purpose of this method is to get around the lack of
* const-correctness in VNL cost-functions and optimizers */
CostFunctionAdaptorType *
GetNonConstCostFunctionAdaptor() const;
/** Print out internal state */
void
PrintSelf(std::ostream & os, Indent indent) const override;
private:
/** Callback function for the Command Observer */
void
IterationReport(const EventObject & event);
CostFunctionAdaptorType * m_CostFunctionAdaptor{};
bool m_Maximize{};
CommandType::Pointer m_Command{};
mutable ParametersType m_CachedCurrentPosition{};
mutable MeasureType m_CachedValue{};
mutable DerivativeType m_CachedDerivative{};
};
} // end namespace itk
#endif
|
