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
|
/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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
*
* http://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 itkTrainingFunctionBase_hxx
#define itkTrainingFunctionBase_hxx
#include "itkTrainingFunctionBase.h"
namespace itk
{
namespace Statistics
{
template<typename TSample, typename TTargetVector, typename ScalarType>
TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::TrainingFunctionBase()
{
m_PerformanceFunction = DefaultPerformanceType::New();
m_Iterations = 0;
m_TrainingSamples = ITK_NULLPTR;
m_SampleTargets = ITK_NULLPTR;
m_LearningRate = 1.0;
}
template<typename TSample, typename TTargetVector, typename ScalarType>
void TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::SetTrainingSamples(TSample* samples)
{
m_TrainingSamples = samples;
std::cout << "Training functionSample Size=" << samples->Size() << std::endl;
typename TSample::ConstIterator iter = samples->Begin();
while (iter != samples->End())
{
//m_InputSamples.push_back(defaultconverter(iter.GetMeasurementVector()));
m_InputSamples.push_back(iter.GetMeasurementVector());
++iter;
}
}
template<typename TSample, typename TTargetVector, typename ScalarType>
void TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::SetTargetValues(TTargetVector* targets)
{
typename TTargetVector::ConstIterator iter = targets->Begin();
while (iter != targets->End())
{
//m_Targets.push_back(targetconverter(iter.GetMeasurementVector()));
m_Targets.push_back(iter.GetMeasurementVector());
++iter;
}
std::cout << "Num of Sample Targets converted= " << m_Targets.size()
<< std::endl;
this->Modified();
}
template<typename TSample, typename TTargetVector, typename ScalarType>
void
TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::SetLearningRate(ValueType lr)
{
m_LearningRate = lr;
this->Modified();
}
template<typename TSample, typename TTargetVector, typename ScalarType>
typename TrainingFunctionBase<TSample,TTargetVector,ScalarType>::ValueType
TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::GetLearningRate()
{
return m_LearningRate;
}
template<typename TSample, typename TTargetVector, typename ScalarType>
void TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::SetPerformanceFunction(PerformanceFunctionType* f)
{
m_PerformanceFunction=f;
this->Modified();
}
/** Print the object */
template<typename TSample, typename TTargetVector, typename ScalarType>
void
TrainingFunctionBase<TSample,TTargetVector,ScalarType>
::PrintSelf( std::ostream& os, Indent indent ) const
{
os << indent << "TrainingFunctionBase(" << this << ")" << std::endl;
os << indent << "m_PerformanceFunction = " << m_PerformanceFunction << std::endl;
os << indent << "m_Iterations = " << m_Iterations << std::endl;
if(m_TrainingSamples)
{
os << indent << "m_TrainingSamples = " << m_TrainingSamples << std::endl;
}
if(m_SampleTargets)
{
os << indent << "m_SampleTargets = " << m_SampleTargets << std::endl;
}
//os << indent << "m_InputSamples = " << m_InputSamples << std::endl;
//os << indent << "m_Targets = " << m_Targets << std::endl;
os << indent << "m_LearningRate = " << m_LearningRate << std::endl;
Superclass::PrintSelf( os, indent );
}
} // end namespace Statistics
} // end namespace itk
#endif
|
