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
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
|
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkSampleClassifierFilter.txx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkSampleClassifierFilter_txx
#define __itkSampleClassifierFilter_txx
#include "itkSampleClassifierFilter.h"
namespace itk {
namespace Statistics {
template< class TSample >
SampleClassifierFilter< TSample >
::SampleClassifierFilter()
{
this->m_NumberOfClasses = 0;
this->SetNumberOfRequiredInputs( 3 );
this->SetNumberOfRequiredOutputs( 1 );
this->ProcessObject::SetNthOutput( 0, this->MakeOutput(0) );
/** Initialize decision rule */
m_DecisionRule = NULL;
}
template< class TSample >
void
SampleClassifierFilter< TSample >
::PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os,indent);
os << indent << "NumberofClasses: "
<< this->GetNumberOfClasses() << std::endl;
os << indent << "DecisionRule: "
<< this->GetDecisionRule() << std::endl;
}
template< class TSample >
void
SampleClassifierFilter< TSample >
::SetInput( const TSample* sample )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(0,
const_cast< SampleType * >( sample ) );
}
template< class TSample >
const TSample *
SampleClassifierFilter< TSample >
::GetInput( ) const
{
if (this->GetNumberOfInputs() < 1)
{
return 0;
}
return static_cast<const SampleType * >
(this->ProcessObject::GetInput(0) );
}
template< class TSample >
void
SampleClassifierFilter< TSample >
::SetClassLabels( const ClassLabelVectorObjectType * classLabels )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(1,
const_cast< ClassLabelVectorObjectType * >( classLabels ) );
}
template< class TSample >
void
SampleClassifierFilter< TSample >
::SetMembershipFunctions( const MembershipFunctionVectorObjectType * membershipFunctions )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(2,
const_cast< MembershipFunctionVectorObjectType * >( membershipFunctions ) );
}
template< class TSample >
void
SampleClassifierFilter< TSample >
::SetMembershipFunctionsWeightsArray( const
MembershipFunctionsWeightsArrayObjectType * weightsArray )
{
// Process object is not const-correct so the const_cast is required here
this->ProcessObject::SetNthInput(3,
const_cast<
MembershipFunctionsWeightsArrayObjectType * >( weightsArray ) );
}
template< class TSample >
typename SampleClassifierFilter< TSample >::DataObjectPointer
SampleClassifierFilter< TSample >
::MakeOutput(unsigned int)
{
return static_cast<DataObject*>( MembershipSampleType::New().GetPointer() );
}
template< class TSample >
void
SampleClassifierFilter< TSample >
::GenerateData()
{
const ClassLabelVectorObjectType * classLabelsDecorated =
static_cast< const ClassLabelVectorObjectType * >( this->ProcessObject::GetInput( 1 ) );
const MembershipFunctionVectorObjectType * membershipFunctionsDecorated =
static_cast< const MembershipFunctionVectorObjectType * >( this->ProcessObject::GetInput( 2 ) );
const MembershipFunctionsWeightsArrayObjectType *
membershipFunctionsWeightsArrayDecorated =
static_cast< const MembershipFunctionsWeightsArrayObjectType * >( this->ProcessObject::GetInput( 3 ) );
const ClassLabelVectorType & classLabels = classLabelsDecorated->Get();
const MembershipFunctionVectorType & membershipFunctions = membershipFunctionsDecorated->Get();
// Check number of Labels and MembershipSamples against the number of classes */
if( membershipFunctions.size() != this->m_NumberOfClasses )
{
itkExceptionMacro("Number of Membership functions does not match the number of classes");
}
if( classLabels.size() != this->m_NumberOfClasses )
{
itkExceptionMacro("Number of class labels does not match the number of classes");
}
if( m_DecisionRule.IsNull())
{
itkExceptionMacro("Decision rule is not set");
}
MembershipFunctionsWeightsArrayType membershipFunctionsWeightsArray;
if( membershipFunctionsWeightsArrayDecorated == NULL )
{
// no weights array is set and hence all membership functions will have equal
// weight
membershipFunctionsWeightsArray.SetSize( this->m_NumberOfClasses );
membershipFunctionsWeightsArray.Fill(1.0);
}
else
{
membershipFunctionsWeightsArray = membershipFunctionsWeightsArrayDecorated->Get();
}
if ( membershipFunctionsWeightsArray.Size() != this->m_NumberOfClasses
)
{
itkExceptionMacro("Membership functions weight array size does not match the\
number of classes ");
}
const SampleType * sample =
static_cast< const SampleType * >( this->ProcessObject::GetInput( 0 ) );
std::vector< double > discriminantScores;
discriminantScores.resize( this->m_NumberOfClasses );
MembershipSampleType * output = dynamic_cast< MembershipSampleType * >(
this->ProcessObject::GetOutput(0));
output->SetSample( this->GetInput() );
output->SetNumberOfClasses( this->m_NumberOfClasses );
typename TSample::ConstIterator iter = sample->Begin();
typename TSample::ConstIterator end = sample->End();
while (iter != end)
{
typename TSample::MeasurementVectorType measurements;
measurements = iter.GetMeasurementVector();
for (unsigned int i = 0; i < this->m_NumberOfClasses; i++)
{
discriminantScores[i] = membershipFunctionsWeightsArray[i] *
membershipFunctions[i]->Evaluate(measurements);
}
unsigned int classIndex;
classIndex = m_DecisionRule->Evaluate(discriminantScores);
output->AddInstance(classLabels[classIndex], iter.GetInstanceIdentifier());
++iter;
}
}
template< class TSample >
const typename SampleClassifierFilter< TSample >::MembershipSampleType *
SampleClassifierFilter< TSample >
::GetOutput() const
{
return static_cast< const MembershipSampleType * >(this->ProcessObject::GetOutput(0));
}
} // end of namespace Statistics
} // end of namespace itk
#endif
|
