ITK 配准框架中的 Subject/Observer 模式及优化过程模拟演示-4
其余几个头文件对应的代码实现如下：
7.Optimizer 优化函数类：
1:
2: //MyOptimizer.cpp
3: #include "MyOptimizer.h"
4:
5: //MyOptimizer
6: MyOptimizer::MyOptimizer()
7: {
8: m_InitialPosition = 0;
9: m_CurrentPosition = 0;
10: m_LastPosition = 0;
11:
12: m_Stop = false;
13: m_CurrentIteration = 0;
14: m_NumberOfIterations = 0;
15:
16: m_Value = 0;
17: }
18:
19: //Set/Get the cost function.
20: void MyOptimizer::SetCostFunction(CostFunctionType * costFunction)
21: {
22: m_CostFunction = costFunction;
23: m_Value = 100; //初始测度值, 将其设为一较大值
24: }
25: //
26: MyOptimizer::CostFunctionPointer MyOptimizer::GetCostFunction() const
27: {
28: return m_CostFunction;
29: }
30: //设置初始化值
31: void MyOptimizer::SetInitialPosition(ParametersType initialPosition)
32: {
33: m_InitialPosition = initialPosition;
34: m_CurrentPosition = m_InitialPosition;
35: }
36: //取得当前优化的参数值
37: MyOptimizer::ParametersType MyOptimizer::GetCurrentPosition() const
38: {
39: return m_CurrentPosition;
40: }
41: //设置, 取得最终参数值
42: void MyOptimizer::SetLastPosition(ParametersType LastPosition)
43: {
44: m_LastPosition = LastPosition;
45: }
46: MyOptimizer::ParametersType MyOptimizer::GetLastPosition() const
47: {
48: return m_LastPosition;
49: }
50: //设置迭代次数上限
51: void MyOptimizer::SetNumberOfIteration(unsigned long max)
52: {
53: m_NumberOfIterations = max;
54: }
55: //返回当前迭代次数
56: unsigned long MyOptimizer::GetCurrentIteration() const
57: {
58: return m_CurrentIteration;
59: }
60:
61: //返回当前测度值
62: MyOptimizer::MeasureType MyOptimizer::GetValue() const
63: {
64: return this->GetCostFunction()->GetValue(m_CurrentPosition);
65: }
66:
67: //开始优化过程:
68: //优化是一个迭代的过程, 每进行一次迭代, 便触发 MyIterationEvent() 事件
69: void MyOptimizer::StartOptimization()
70: {
71: //进行适当初始化
72: m_CurrentIteration = 0;
73: m_Stop = false;
74:
75: //优化开始,开始进行迭代, 触发 StartEvent() 事件.
76: this->InvokeEvent(MyStartEvent());
77:
78: while(!m_Stop)
79: {
80: //迭代次数达到最在限制
81: if(m_CurrentIteration >= m_NumberOfIterations)
82: {
83: this->StopOptimization();
84: break;
85: }
86:
87: //根据当前参数空间, 计算测度值
88: m_Value = m_CostFunction->GetValue( m_CurrentPosition );
89:
90: //前进一步, 迭代一次, 根据优化策略以及当前参数值计算出新的参数值
91: m_CurrentIteration++;
92: this->AdvanceOneStep();
93: }
94: };
95:
96: //停止优化过程
97: void MyOptimizer::StopOptimization()
98: {
99: //优化过程结束,停止迭代, 触发 EndEvent() 事件
100: m_Stop = true;
101: m_LastPosition = m_CurrentPosition;
102: this->InvokeEvent( MyEndEvent() );
103: }
104:
105: //打印相关信息
106: void MyOptimizer::PrintSelf( std::ostream& os, MyIndent indent ) const
107: {
108: Superclass::PrintSelf(os, indent);
109:
110: MyIndent nextIndent = indent.GetNextIndent();
111:
112: os << std::endl << nextIndent << "SomeParameters: " << std::endl;
113: os << nextIndent << "CostFunction = "
114: << m_CostFunction->GetNameOfClass() << std::endl;
115: os << nextIndent << "InitialPosition = "
116: << m_InitialPosition << std::endl;
117: os << nextIndent << "CurrentPosition = "
118: << m_CurrentPosition << std::endl;
119: os << nextIndent << "NumberOfIteration = "
120: << m_NumberOfIterations << std::endl;
121: os << nextIndent << "CurrentMetricValue = "
122: << m_Value << std::endl;
123: }
124:
125: ////////////////////
126: //MyConcreteOptimizer, 具体的优化策略子类, 实现优化修改参数的策略
127: //New()
128: MyConcreteOptimizer* MyConcreteOptimizer::New(){ return new Self; }
129:
130: //Delete()
131: void MyConcreteOptimizer::Delete(){ delete this; }
132:
133: //
134: MyConcreteOptimizer::MyConcreteOptimizer()
135: {
136: m_StepLength = 2; //前进步长, 默认为 2
137: }
138: void MyConcreteOptimizer::SetStepLength(ParametersType step)
139: {
140: m_StepLength = step;
141: }
142:
143: //前进一步, 迭代一次, 这里只为了演示,进行如下功能:
144: //使 m_CurrentPosition = 100;
145: void MyConcreteOptimizer::AdvanceOneStep()
146: {
147: if(m_Value == 0)
148: {
149: this->StopOptimization();
150: return;
151: }
152:
153: //测度值越小, 表明越接近目标
154: //但是如果测度值为负, 则减少 m_CurrentPosition
155: if(m_Value < 0)
156: {
157: m_CurrentPosition = m_CurrentPosition - 1;
158: }
159: else
160: {
161: m_CurrentPosition = m_CurrentPosition + m_StepLength;
162: }
163:
164: this->InvokeEvent( MyIterationEvent() );
165: }
166:
167: //打印相关信息
168: void MyConcreteOptimizer::PrintSelf( std::ostream& os, MyIndent indent ) const
169: {
170: Superclass::PrintSelf(os, indent);
171:
172: MyIndent nextIndent = indent.GetNextIndent();
173: os << nextIndent << "StepLength = "
174: << m_StepLength << std::endl << std::endl;
175: }
8.Metric 相似性测度模拟类：
1: //MySimpleMetric.cpp
2: #include "MySimpleMetric.h"
3:
4: //
5: void MyCostFunction::Initialize(void)
6: {
7: m_Value = 100;
8: }
9: MyCostFunction::MeasureType MyCostFunction::GetValue() const
10: {
11: return m_Value;
12: }
13: void MyCostFunction::PrintSelf(std::ostream& os, MyIndent indent) const
14: {
15: Superclass::PrintSelf(os, indent);
16:
17: MyIndent nextIndent = indent.GetNextIndent();
18: std::cout << nextIndent << "Current MetricValue = " << GetValue() << std::endl;
19: }
20:
21: //根据输入参数, 计算相似性测度值, 这里只是进行简单的功能演示
22: //这里将传入的值与 100 相比, 当最接近 100 时, 测度值最小.
23: //当返回的测度值为 0 时, 表明大于 100, 这时需要在优化函数中减小参数
24: MySimpleMetric::MeasureType
25: MySimpleMetric::GetValue(const ParametersType& parameters)
26: {
27: return m_Value = 100 - parameters;
28: }
29: //
30: void MySimpleMetric::PrintSelf(std::ostream& os, MyIndent indent) const
31: {
32: Superclass::PrintSelf(os, indent);
33: os << std::endl;
34: }
9.MyRegistrationMethod 连接各个组件:
1: //MyRegistrationMethod.cpp
2: #include "MyRegistrationMethod.h"
3:
4: //
5: MyRegistrationMethod::~MyRegistrationMethod()
6: {
7: m_Metric = NULL;
8: m_Optimizer = NULL;
9: }
10: //New() 创建对象实例
11: MyRegistrationMethod* MyRegistrationMethod::New()
12: {
13: return new Self;
14: }
15:
16: //Delete()
17: void MyRegistrationMethod::Delete()
18: {
19: delete this;
20: }
21: MyRegistrationMethod::ParametersType
22: MyRegistrationMethod::GetLastParameters() const
23: {
24: return m_Optimizer->GetLastPosition();
25: }
26: //初始化各个组件
27: void MyRegistrationMethod::Initialize()
28: {
29: if ( !m_Metric ){
30: std::cout <<"Metric is not present" << std::endl;
31: }
32: if ( !m_Optimizer ){
33: std::cout << "Optimizer is not present" << std::endl;
34: }
35:
36: //初始化配准框架的各个组件, 这里为了模拟省略了大部分内容
37: m_Metric->Initialize();
38: m_Optimizer->SetCostFunction( m_Metric );
39: }
40:
41: //ITK 的管道机制中, 调用管道上一个组件的 Update() 会更新管道, 触发管道的执行
42: //这里只为模拟,以展示 ITK 配准框架的大体过程, 它调用了 GenerateData() 以生成数据
43: void MyRegistrationMethod::Update()
44: {
45: this->GenerateData();
46: }
47:
48: //ITK 配准框架中, 这个函数是非常重要，它由管道触发，生成输出数据
49: //它调用了 StartRegistration() 开始配准过程, StartRegistration 进行适当的准备后又调用了
50: //Initialize() 进行必要初始化, 然后调用 StartOptimization() 开始优化过程
51: void MyRegistrationMethod::GenerateData ()
52: {
53: this->StartRegistration();
54: }
55: //
56: void MyRegistrationMethod::StartRegistration ()
57: {
58: this->Initialize();
59: this->StartOptimization();
60: }
61:
62: //StartOptimization 又调用了其指针成员 m_Optimizer 的同名函数
63: void MyRegistrationMethod::StartOptimization(void)
64: {
65: m_Optimizer->StartOptimization();
66: }
67:
68: //打印自身相关信息:
69: void MyRegistrationMethod::PrintSelf(std::ostream& os, MyIndent indent) const
70: {
71: Superclass::PrintSelf( os, indent );
72:
73: MyIndent nextIndent = indent.GetNextIndent();
74: os << nextIndent << "Metric: " << typeid(m_Metric).name() << std::endl;
75: os << nextIndent << "Optimizer: " << typeid(m_Optimizer).name() << std::endl;
76: }
10. test 测试代码，这里只测试了用于演示使用 Subject/Observer 模式监视优化迭代过程的代码：
1:
2: //test.cpp
3: #include "MyCommand.h"
4: #include "MyRegistrationMethod.h"
5: #include <iomanip>
6: #include <iostream>
7:
8: //客户定义一个具体的 Command 子类, 并实现其成员函数 Execute()
9: //Exectue() 功能相当于一个回调函数(callback)
10: //所以只应该完成一些简单的任务, 一般情况下使用 Command 监视迭代过程
11: //而在多分辨策略情况下, 使用 Command 在不同级间改变优化策略,这个问题以后再研究.
12: class MyCommandIterationUpdate : public MyCommand
13: {
14: public:
15: typedef MyCommandIterationUpdate Self;
16: typedef MyCommand Superclass;
17: typedef MyCommandIterationUpdate* Pointer;
18: typedef MyCommandIterationUpdate* const ConstPointer;
19:
20: //New(), itk 中 New() 为宏, 通过对象工厂创建对象
21: //并使用引用计数与智能指针保证对象只有一个真正的实例, 减少空间占用
22: //关于智能指针与引用计数,以及使用对象工厂创建对象, 另外再进行专门的演示
23: static Self* New(){ return new Self; };
24:
25: //Delete()
26: virtual void Delete() { delete this; }
27:
28: protected:
29: MyCommandIterationUpdate() { };
30:
31: public:
32: typedef MyConcreteOptimizer OptimizerType;
33: typedef const OptimizerType *OptimizerPointer;
34:
35: void Execute(MyObject *caller, const MyEventObject & event)
36: {
37: Execute( (const MyObject *)caller, event);
38: }
39: void Execute(const MyObject * object, const MyEventObject & event)
40: {
41: OptimizerPointer optimizer = dynamic_cast< OptimizerPointer >( object );
42:
43: //检查 MyCommandIterationUpdate 是否观察该事件
44: //主程序中注册了 Start, End, Iteration 三个感兴趣事件
45: if( !MyStartEvent().CheckEvent( &event ) && !MyEndEvent().CheckEvent( &event) &&
46: !MyIterationEvent().CheckEvent( &event ) )
47: {
48: std::cout << "I doesn't observe the event: " << event.GetEventName() << std::endl;
49: return;
50: }
51: if( MyStartEvent().CheckEvent( &event ) ){
52: std::cout << "StartOptimization: ";
53: std::cout << "InitialPosition = "
54: << std::setw(3) << optimizer->GetCurrentPosition();
55: std::cout << " CurrentIteration = "
56: << std::setw(3) << optimizer->GetCurrentIteration();
57: std::cout << " MetricValue = "
58: << std::setw(3) << optimizer->GetValue() << std::endl << std::endl;
59: }
60: if( MyEndEvent().CheckEvent( &event ) ){
61: std::cout << std::endl
62: << "StopOptimization...... End." << std::endl << std::endl;
63: }
64: if( MyIterationEvent().CheckEvent( &event ) )
65: {
66: std::cout << "MyIterationEvent: ";
67: std::cout << "CurrentPosition = "
68: << std::setw(3) << optimizer->GetCurrentPosition();
69: std::cout << " CurrentIteration = "
70: << std::setw(3) << optimizer->GetCurrentIteration();
71: std::cout << " MetricValue = "
72: << std::setw(3) << optimizer->GetValue() << std::endl;
73: }
74: }
75: };
76:
77: int main()
78: {
79: //1.声明并定义相关组件, 这里只是简单模拟了: 相似性测度, 优化, 配准方法组件
80: typedef MySimpleMetric metricType;
81: typedef MyConcreteOptimizer optimizerType;
82: typedef MyRegistrationMethod registrationType; //用于连接其它各个组件
83:
84: metricType::Pointer metric = metricType::New();
85: optimizerType::Pointer optimizer = optimizerType::New();
86: registrationType::Pointer registration = registrationType::New();
87:
88: //2.连接各个组件:
89: registration->SetMetric( metric );
90: registration->SetOptimizer( optimizer);
91:
92: //3.声明并定义一个 Command 实例, 输出迭代执行过程
93: MyCommandIterationUpdate::Pointer observer = MyCommandIterationUpdate::New();
94:
95: //4.注册观察者以及其感兴趣的事件
96: optimizer->AddObserver(MyStartEvent(), observer);
97: optimizer->AddObserver(MyIterationEvent(), observer);
98: optimizer->AddObserver(MyEndEvent(), observer);
99:
100: //5.进行适当的初始设置
101: typedef registrationType::ParametersType ParametersType;
102:
103: //初始值, 这里随便给一个初值; 最终目的是使其达到 100
104: ParametersType initialPosition = 9;
105: optimizer->SetInitialPosition(initialPosition);
106:
107: //前进步长, 程序中默认值为 2
108: ParametersType stepLength = 5;
109: optimizer->SetStepLength(stepLength);
110:
111: //设置最大迭代次数限制
112: optimizer->SetNumberOfIteration(50);
113:
114: ///////////////////////
115: //6.Update(), 开始优化迭代过程
116: registration->Update();
117: ///////////////////////
118:
119: //7.取得最后结果:
120: ParametersType finalParameters = registration->GetLastParameters();
121: const unsigned int numberOfIterations = optimizer->GetCurrentIteration();
122: const int bestValue = optimizer->GetValue();
123:
124: std::cout << "|----------------------------------------" << std::endl;
125: std::cout << "Result = " << std::endl;
126: std::cout << " LastPosition = " << finalParameters << std::endl;
127: std::cout << " Iterations = " << numberOfIterations << std::endl;
128: std::cout << " Metric value = " << bestValue << std::endl;
129: std::cout << "|----------------------------------------" << std::endl;
130: std::cout << std::endl;
131:
132: //打印一些相关的信息, 测试 Print() 函数:
133: std::cout << "Print some information about registrationMethod: " << std::endl;
134: registration->Print(std::cout, 0);
135:
136: std::cout << "/nNext Print some information about the optimizer: " << std::endl;
137: optimizer->Print(std::cout, 0);
138:
139: //这里没有使用智能指针,所以必须手动销毁在堆上创建的对象
140: //关于智能指针以及对象工厂的原理及使用,另外进行演示
141: registration->Delete();
142: optimizer->Delete();
143: metric->Delete();
144: observer->Delete();
145:
146: return EXIT_SUCCESS;
147: }
//根据程序中设置的初值，执行过程如下：
StartOptimization: InitialPosition = 9 CurrentIteration = 0 MetricValue = 91
MyIterationEvent: CurrentPosition = 14 CurrentIteration = 1 MetricValue = 86
MyIterationEvent: CurrentPosition = 19 CurrentIteration = 2 MetricValue = 81
MyIterationEvent: CurrentPosition = 24 CurrentIteration = 3 MetricValue = 76
MyIterationEvent: CurrentPosition = 29 CurrentIteration = 4 MetricValue = 71
MyIterationEvent: CurrentPosition = 34 CurrentIteration = 5 MetricValue = 66
MyIterationEvent: CurrentPosition = 39 CurrentIteration = 6 MetricValue = 61
MyIterationEvent: CurrentPosition = 44 CurrentIteration = 7 MetricValue = 56
MyIterationEvent: CurrentPosition = 49 CurrentIteration = 8 MetricValue = 51
MyIterationEvent: CurrentPosition = 54 CurrentIteration = 9 MetricValue = 46
MyIterationEvent: CurrentPosition = 59 CurrentIteration = 10 MetricValue = 41
MyIterationEvent: CurrentPosition = 64 CurrentIteration = 11 MetricValue = 36
MyIterationEvent: CurrentPosition = 69 CurrentIteration = 12 MetricValue = 31
MyIterationEvent: CurrentPosition = 74 CurrentIteration = 13 MetricValue = 26
MyIterationEvent: CurrentPosition = 79 CurrentIteration = 14 MetricValue = 21
MyIterationEvent: CurrentPosition = 84 CurrentIteration = 15 MetricValue = 16
MyIterationEvent: CurrentPosition = 89 CurrentIteration = 16 MetricValue = 11
MyIterationEvent: CurrentPosition = 94 CurrentIteration = 17 MetricValue = 6
MyIterationEvent: CurrentPosition = 99 CurrentIteration = 18 MetricValue = 1
MyIterationEvent: CurrentPosition = 104 CurrentIteration = 19 MetricValue = -4
MyIterationEvent: CurrentPosition = 103 CurrentIteration = 20 MetricValue = -3
MyIterationEvent: CurrentPosition = 102 CurrentIteration = 21 MetricValue = -2
MyIterationEvent: CurrentPosition = 101 CurrentIteration = 22 MetricValue = -1
MyIterationEvent: CurrentPosition = 100 CurrentIteration = 23 MetricValue = 0
StopOptimization...... End.
|----------------------------------------
Result =
LastPosition = 100
Iterations = 24
Metric value = 0
|----------------------------------------
Print some information about registrationMethod:
RTTI typeinfo: class MyRegistrationMethod
Observers:
none
Metric: class MyCostFunction *
Optimizer: class MyOptimizer *
Next Print some information about the optimizer:
RTTI typeinfo: class MyConcreteOptimizer
Observers:
MyStartEvent(MyCommand)
MyIterationEvent(MyCommand)
MyEndEvent(MyCommand)
SomeParameters:
CostFunction = MySimpleMetric
InitialPosition = 9
CurrentPosition = 100
NumberOfIteration = 50
CurrentMetricValue = 0
StepLength = 5
可以看到，初值为 9，步长为 5 的，即如果测度值为正，则 CurrentPosition += 5；否则，CurrentPosition –= 1；则迭代了总共 24 次，最终值达到了 100，当值达到 100 时，测度值达到最佳值 0。
最后还测试了 Print() 函数，这个很容易看懂。