File: itkExhaustiveOptimizerTest.cxx

package info (click to toggle)
insighttoolkit5 5.4.3-5
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 704,384 kB
  • sloc: cpp: 783,592; ansic: 628,724; xml: 44,704; fortran: 34,250; python: 22,874; sh: 4,078; pascal: 2,636; lisp: 2,158; makefile: 464; yacc: 328; asm: 205; perl: 203; lex: 146; tcl: 132; javascript: 98; csh: 81
file content (281 lines) | stat: -rw-r--r-- 7,979 bytes parent folder | download
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
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  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
 *
 *         https://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 <algorithm>

#include "itkCommand.h"
#include "itkExhaustiveOptimizer.h"

#include "itkMath.h"
#include "itkTestingMacros.h"

/**
 *  The objectif 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 RSGCostFunction
 */
class RSGCostFunction : public itk::SingleValuedCostFunction
{
public:
  using Self = RSGCostFunction;
  using Superclass = itk::SingleValuedCostFunction;
  using Pointer = itk::SmartPointer<Self>;
  using ConstPointer = itk::SmartPointer<const Self>;
  itkNewMacro(Self);

  enum
  {
    SpaceDimension = 2
  };

  using ParametersType = Superclass::ParametersType;
  using DerivativeType = Superclass::DerivativeType;
  using MeasureType = Superclass::MeasureType;

  RSGCostFunction() = default;


  MeasureType
  GetValue(const ParametersType & parameters) const 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 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;
  }


  unsigned int
  GetNumberOfParameters() const override
  {
    return SpaceDimension;
  }
};

class IndexObserver : public itk::Command
{
public:
  using Self = IndexObserver;
  using Superclass = itk::Command;
  using Pointer = itk::SmartPointer<Self>;

  itkNewMacro(IndexObserver);

  void
  Execute(const itk::Object * caller, const itk::EventObject &) override
  {
    using OptimizerType = itk::ExhaustiveOptimizer;
    const auto * optimizer = dynamic_cast<const OptimizerType *>(caller);

    if (nullptr != optimizer)
    {
      OptimizerType::ParametersType currentIndex = optimizer->GetCurrentIndex();

      if (currentIndex.GetSize() == 2)
      {
        std::cout << " @ index = " << currentIndex << std::endl;
        // Casting is safe here since the indices are always integer values (but there are stored in doubles):
        auto idx = static_cast<unsigned long>(currentIndex[0] + 21 * currentIndex[1]);
        m_VisitedIndices.push_back(idx);
      }
    }
  }

  void
  Execute(itk::Object * caller, const itk::EventObject & event) override
  {
    Execute(static_cast<const itk::Object *>(caller), event);
  }

  std::vector<unsigned long> m_VisitedIndices;
};

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

  using OptimizerType = itk::ExhaustiveOptimizer;

  using ScalesType = OptimizerType::ScalesType;


  // Declaration of an itkOptimizer
  auto itkOptimizer = OptimizerType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(itkOptimizer, ExhaustiveOptimizer, SingleValuedNonLinearOptimizer);


  // Index observer (enables us to check if all positions were indeed visisted):
  auto idxObserver = IndexObserver::New();
  itkOptimizer->AddObserver(itk::IterationEvent(), idxObserver);

  // Declaration of the CostFunction
  auto costFunction = RSGCostFunction::New();
  itkOptimizer->SetCostFunction(costFunction);


  using ParametersType = RSGCostFunction::ParametersType;


  const unsigned int spaceDimension = costFunction->GetNumberOfParameters();

  // We start not so far from  | 2 -2 |
  ParametersType initialPosition(spaceDimension);
  initialPosition[0] = 0.0;
  initialPosition[1] = -4.0;

  itkOptimizer->SetInitialPosition(initialPosition);


  ScalesType parametersScale(spaceDimension);
  parametersScale[0] = 1.0;
  parametersScale[1] = 1.0;

  itkOptimizer->SetScales(parametersScale);


  auto stepLength = 1.0;
  itkOptimizer->SetStepLength(stepLength);
  ITK_TEST_SET_GET_VALUE(stepLength, itkOptimizer->GetStepLength());


  using StepsType = OptimizerType::StepsType;
  StepsType steps(2);
  steps[0] = 10;
  steps[1] = 10;

  itkOptimizer->SetNumberOfSteps(steps);
  ITK_TEST_SET_GET_VALUE(steps, itkOptimizer->GetNumberOfSteps());


  std::cout << "MaximumNumberOfIterations: " << itkOptimizer->GetMaximumNumberOfIterations() << std::endl;

  try
  {
    itkOptimizer->StartOptimization();
  }
  catch (const 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;
  }


  bool minimumValuePass = itk::Math::abs(itkOptimizer->GetMinimumMetricValue() - -10) < 1E-3;

  std::cout << "MinimumMetricValue = " << itkOptimizer->GetMinimumMetricValue() << std::endl;
  std::cout << "Minimum Position = " << itkOptimizer->GetMinimumMetricValuePosition() << std::endl;

  bool maximumValuePass = itk::Math::abs(itkOptimizer->GetMaximumMetricValue() - 926) < 1E-3;
  std::cout << "MaximumMetricValue = " << itkOptimizer->GetMaximumMetricValue() << std::endl;
  std::cout << "Maximum Position = " << itkOptimizer->GetMaximumMetricValuePosition() << std::endl;

  ParametersType finalPosition = itkOptimizer->GetMinimumMetricValuePosition();
  std::cout << "Solution        = (";
  std::cout << finalPosition[0] << ',';
  std::cout << finalPosition[1] << ')' << std::endl;

  bool                       visitedIndicesPass = true;
  std::vector<unsigned long> visitedIndices = idxObserver->m_VisitedIndices;

  size_t requiredNumberOfSteps = (2 * steps[0] + 1) * (2 * steps[1] + 1);
  if (visitedIndices.size() != requiredNumberOfSteps)
  {
    visitedIndicesPass = false;
  }

  std::sort(visitedIndices.begin(), visitedIndices.end());

  for (size_t i = 0; i < visitedIndices.size(); ++i)
  {
    if (visitedIndices[i] != i)
    {
      visitedIndicesPass = false;
      std::cout << "Mismatch in visited index " << visitedIndices[i] << " @ " << i << std::endl;
      break;
    }
  }

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

  if (!minimumValuePass || !maximumValuePass || !trueParamsPass || !visitedIndicesPass)
  {
    std::cout << "minimumValuePass   = " << minimumValuePass << std::endl;
    std::cout << "maximumValuePass   = " << maximumValuePass << std::endl;
    std::cout << "trueParamsPass     = " << trueParamsPass << std::endl;
    std::cout << "visitedIndicesPass = " << visitedIndicesPass << std::endl;
    std::cout << "Test failed." << std::endl;
    return EXIT_FAILURE;
  }


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