File: itkSPSAOptimizerTest.cxx

package info (click to toggle)
insighttoolkit4 4.13.3withdata-dfsg2-4
  • links: PTS, VCS
  • area: main
  • in suites: bookworm
  • size: 491,256 kB
  • sloc: cpp: 557,600; ansic: 180,546; fortran: 34,788; python: 16,572; sh: 2,187; lisp: 2,070; tcl: 993; java: 362; perl: 200; makefile: 133; csh: 81; pascal: 69; xml: 19; ruby: 10
file content (224 lines) | stat: -rw-r--r-- 6,173 bytes parent folder | download | duplicates (5)
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
218
219
220
221
222
223
224
/*=========================================================================
 *
 *  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 "itkSPSAOptimizer.h"


/**
 * \class
 *  The objective function is the quadratic form:
 *
 *  1/2 x^T A x - b^T x
 *
 *  Where A is a matrix and b is a vector
 *  The system in this example is:
 *
 *     | 3  2 ||x|   | 2|   |0|
 *     | 2  6 ||y| + |-8| = |0|
 *
 *
 *   the solution is the vector | 2 -2 |
 *
 */
class SPSACostFunction : public itk::SingleValuedCostFunction
{
 public:

  typedef SPSACostFunction               Self;
  typedef itk::SingleValuedCostFunction  Superclass;
  typedef itk::SmartPointer<Self>        Pointer;
  typedef itk::SmartPointer<const Self>  ConstPointer;
  itkNewMacro( Self );

  enum { SpaceDimension=2 };

  typedef Superclass::ParametersType      ParametersType;
  typedef Superclass::DerivativeType      DerivativeType;
  typedef Superclass::MeasureType         MeasureType;


  SPSACostFunction()
  {
  }


  virtual MeasureType  GetValue( const ParametersType & parameters ) const ITK_OVERRIDE
  {

    double x = parameters[0];
    double y = parameters[1];

    std::cout << "GetValue( ";
    std::cout << x << " ";
    std::cout << y << ") = ";

    MeasureType measure = 0.5*(3*x*x+4*x*y+6*y*y) - 2*x + 8*y;

    std::cout << measure << std::endl;
    return measure;

  }

  void GetDerivative( const ParametersType & parameters,
                      DerivativeType  & derivative ) const ITK_OVERRIDE
  {

    double x = parameters[0];
    double y = parameters[1];

    std::cout << "GetDerivative( ";
    std::cout << x << " ";
    std::cout << y << ") = ";

    derivative = DerivativeType( SpaceDimension );
    derivative[0] = 3 * x + 2 * y -2;
    derivative[1] = 2 * x + 6 * y +8;

  }


  virtual unsigned int GetNumberOfParameters(void) const ITK_OVERRIDE
  {
    return SpaceDimension;
  }

 private:
};

int itkSPSAOptimizerTest(int, char* [] )
{
  std::cout << "SPSAOptimizer Test ";
  std::cout << std::endl << std::endl;

  typedef  itk::SPSAOptimizer                   OptimizerType;
  typedef  OptimizerType::ScalesType            ScalesType;

  // Declaration of a itkOptimizer
  OptimizerType::Pointer  itkOptimizer = OptimizerType::New();

  // Declaration of the CostFunction
  SPSACostFunction::Pointer costFunction = SPSACostFunction::New();
  itkOptimizer->SetCostFunction( costFunction.GetPointer() );

  typedef SPSACostFunction::ParametersType    ParametersType;
  const unsigned int spaceDimension =
    costFunction->GetNumberOfParameters();

  ScalesType    parametersScale( spaceDimension );
  parametersScale[0] = 1.0;
  parametersScale[1] = 2.0;
  itkOptimizer->SetScales( parametersScale );

  itkOptimizer->MinimizeOn();
  itkOptimizer->SetMaximumNumberOfIterations(100);
  itkOptimizer->Seta( 1.0 );
  itkOptimizer->SetA( 10.0 );
  itkOptimizer->SetAlpha( 0.602 );
  itkOptimizer->Setc( 0.0001 );
  itkOptimizer->SetGamma( 0.101 );
  itkOptimizer->SetTolerance(1e-5);
  itkOptimizer->SetStateOfConvergenceDecayRate(0.5);
  itkOptimizer->SetMinimumNumberOfIterations(10);
  itkOptimizer->SetNumberOfPerturbations(1);

  // We start not so far from  | 2 -2 |
  ParametersType  initialPosition( spaceDimension );
  initialPosition[0] =  100;
  initialPosition[1] = -100;
  itkOptimizer->SetInitialPosition( initialPosition );

  try
    {
    itkOptimizer->GuessParameters(50, 70.0);
    }
  catch( itk::ExceptionObject & e )
    {
    std::cout << "Exception thrown ! " << std::endl;
    std::cout << "An error occurred during Guessing Parameters" << std::endl;
    std::cout << "Location    = " << e.GetLocation()    << std::endl;
    std::cout << "Description = " << e.GetDescription() << std::endl;
    return EXIT_FAILURE;
    }
  std::cout << "\nEstimated parameter: a = " << itkOptimizer->Geta();
  std::cout << "\nEstimated parameter: A = " << itkOptimizer->GetA() << "\n" << 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 = itkOptimizer->GetCurrentPosition();
  std::cout << "Solution        = (";
  std::cout << finalPosition[0] << ",";
  std::cout << finalPosition[1] << ")" << std::endl;

  std::cout
    << "StateOfConvergence in last iteration: "
    << itkOptimizer->GetStateOfConvergence()
    << std::endl;
  std::cout
    << "NumberOfIterations: "
    << itkOptimizer->GetCurrentIteration()
    << std::endl;

  std::cout
    << "Stop condition: "
    << itkOptimizer->GetStopConditionDescription()
    << std::endl;


  //
  // check results to see if it is within range
  //
  bool pass = true;
  double trueParameters[2] = { 2, -2 };
  for( unsigned int j = 0; j < 2; j++ )
    {
    if( itk::Math::abs( finalPosition[j] - trueParameters[j] ) > 0.01 )
      pass = false;
    }
  if (itkOptimizer->GetStopCondition() == itk::SPSAOptimizer::Unknown)
    {
    pass = false;
    }
  if (itkOptimizer->GetStopCondition() == itk::SPSAOptimizer::MetricError)
    {
    pass = false;
    }

  if( !pass )
    {
    std::cout << "Test failed." << std::endl;
    return EXIT_FAILURE;
    }

  itkOptimizer->Print( std::cout );

  std::cout << "Test passed." << std::endl;
  return EXIT_SUCCESS;


}