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
|
/*=========================================================================
*
* 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.
*
*=========================================================================*/
#include "itkGradientDescentOptimizerv4.h"
/* This test simulates the use of a metric with a transform
* with local support, testing the proper handling of scales for such a case.
*
* Cribbed originally from itkGradientDescentOptimizerTest */
/**
* \class GradientDescentOptimizerv4Test2Metric for test
*
* The version for this test returns a derivative that simulates
* the return from a metric working with a transform with local support.
* The derivative does not change, it's only meant to test the mechanics
* of applying scales in one iteration of optimization.
*
*/
class GradientDescentOptimizerv4Test2Metric
: public itk::ObjectToObjectMetricBase
{
public:
typedef GradientDescentOptimizerv4Test2Metric Self;
typedef itk::ObjectToObjectMetricBase Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
itkNewMacro( Self );
itkTypeMacro( GradientDescentOptimizerv4Test2Metric, ObjectToObjectMetricBase );
enum { SpaceDimension=3 };
typedef Superclass::ParametersType ParametersType;
typedef Superclass::ParametersValueType ParametersValueType;
typedef Superclass::NumberOfParametersType NumberOfParametersType;
typedef Superclass::DerivativeType DerivativeType;
typedef Superclass::MeasureType MeasureType;
GradientDescentOptimizerv4Test2Metric()
{
m_Parameters.SetSize( this->GetNumberOfParameters() );
m_Parameters.Fill( 0 );
}
virtual void Initialize(void) ITK_OVERRIDE {}
virtual void GetDerivative( DerivativeType & derivative ) const ITK_OVERRIDE
{
MeasureType value;
GetValueAndDerivative( value, derivative );
}
void GetValueAndDerivative( MeasureType & value,
DerivativeType & derivative ) const ITK_OVERRIDE
{
if( derivative.Size() != this->GetNumberOfParameters() )
derivative.SetSize( this->GetNumberOfParameters() );
value = 0.0;
for( NumberOfParametersType i=0; i < this->GetNumberOfParameters(); i++ )
{
derivative[i] = i;
}
std::cout << "derivative: " << derivative << std::endl;
}
virtual MeasureType GetValue() const ITK_OVERRIDE
{
return 0.0;
}
virtual void UpdateTransformParameters( const DerivativeType & update, ParametersValueType ) ITK_OVERRIDE
{
m_Parameters += update;
}
virtual unsigned int GetNumberOfParameters(void) const ITK_OVERRIDE
{
return SpaceDimension * 3;
}
virtual bool HasLocalSupport() const ITK_OVERRIDE
{
return false;
}
virtual unsigned int GetNumberOfLocalParameters() const ITK_OVERRIDE
{
return SpaceDimension;
}
/* These Set/Get methods are only needed for this test derivation that
* isn't using a transform */
virtual void SetParameters( ParametersType & parameters ) ITK_OVERRIDE
{
m_Parameters = parameters;
}
virtual const ParametersType & GetParameters() const ITK_OVERRIDE
{
return m_Parameters;
}
private:
ParametersType m_Parameters;
};
///////////////////////////////////////////////////////////
int itkGradientDescentOptimizerv4Test2(int, char* [] )
{
std::cout << "Gradient Descent Object Optimizer Test ";
std::cout << std::endl << std::endl;
typedef itk::GradientDescentOptimizerv4 OptimizerType;
typedef OptimizerType::ScalesType ScalesType;
// Declaration of a itkOptimizer
OptimizerType::Pointer itkOptimizer = OptimizerType::New();
// Declaration of the Metric
GradientDescentOptimizerv4Test2Metric::Pointer metric = GradientDescentOptimizerv4Test2Metric::New();
itkOptimizer->SetMetric( metric );
typedef GradientDescentOptimizerv4Test2Metric::ParametersType ParametersType;
typedef GradientDescentOptimizerv4Test2Metric::NumberOfParametersType NumberOfParametersType;
ParametersType initialPosition( metric->GetNumberOfParameters() );
initialPosition.Fill(0);
metric->SetParameters( initialPosition );
itkOptimizer->SetLearningRate( 1.0 );
itkOptimizer->SetNumberOfIterations( 1 );
ScalesType scales( metric->GetNumberOfLocalParameters() );
for( NumberOfParametersType i=0; i < metric->GetNumberOfLocalParameters(); i++ )
{
scales[i] = i+2;
}
itkOptimizer->SetScales( scales );
ParametersType truth( metric->GetNumberOfParameters() );
NumberOfParametersType numLocal = metric->GetNumberOfLocalParameters();
NumberOfParametersType numLoops = metric->GetNumberOfParameters() / numLocal;
for( NumberOfParametersType i=0; i < numLoops; i++ )
{
for( NumberOfParametersType j=0; j < numLocal; j++ )
{
NumberOfParametersType ind = i * numLocal + j;
truth[ind] = initialPosition[ind] + (ind) / scales[j];
}
}
std::cout << "truth: " << truth << std::endl;
try
{
itkOptimizer->StartOptimization();
}
catch( itk::ExceptionObject & e )
{
std::cout << "Exception thrown ! " << std::endl;
std::cout << "An error occurred during Optimization" << std::endl;
std::cout << "Location = " << e.GetLocation() << std::endl;
std::cout << "Description = " << e.GetDescription() << std::endl;
return EXIT_FAILURE;
}
ParametersType finalPosition = metric->GetParameters();
std::cout << "finalPosition = " << finalPosition << std::endl;
//
// check results to see if it is within range
//
for( NumberOfParametersType j = 0; j < metric->GetNumberOfParameters(); j++ )
{
if( itk::Math::abs( finalPosition[j] - truth[j] ) > 0.000001 )
{
std::cerr << "Results do not match: " << std::endl
<< "expected: " << truth << std::endl
<< "actual: " << finalPosition << std::endl;
return EXIT_FAILURE;
}
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
|
