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
|
/*=========================================================================
*
* 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 "itkOnePlusOneEvolutionaryOptimizer.h"
#include "itkNormalVariateGenerator.h"
#include "itkCommand.h"
#include "itkMath.h"
namespace itk
{
/**
* \class OnePlusOneCostFunction
*
* 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 OnePlusOneCostFunction : public itk::SingleValuedCostFunction
{
public:
typedef OnePlusOneCostFunction Self;
typedef itk::SingleValuedCostFunction Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
itkNewMacro( Self );
itkTypeMacro( OnePlusOneCostFunction, SingleValuedCostFunction );
enum { SpaceDimension=2 };
typedef Superclass::ParametersType ParametersType;
typedef Superclass::MeasureType MeasureType;
OnePlusOneCostFunction()
{
}
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 & itkNotUsed( parameters ),
DerivativeType & itkNotUsed( derivative ) ) const ITK_OVERRIDE
{
itkGenericExceptionMacro("OnePlusOneEvolutionaryOptimizer is not supposed to call GetDerivative()");
}
virtual unsigned int GetNumberOfParameters(void) const ITK_OVERRIDE
{
return SpaceDimension;
}
private:
};
class OnePlusOneCommandIterationUpdate : public itk::Command
{
public:
typedef OnePlusOneCommandIterationUpdate Self;
typedef itk::Command Superclass;
typedef itk::SmartPointer<Self> Pointer;
itkNewMacro( Self );
protected:
OnePlusOneCommandIterationUpdate() { m_LastMetricValue = 0.0; };
public:
typedef itk::OnePlusOneEvolutionaryOptimizer OptimizerType;
typedef const OptimizerType * OptimizerPointer;
virtual void Execute(itk::Object *caller, const itk::EventObject & event) ITK_OVERRIDE
{
Execute( (const itk::Object *)caller, event);
}
virtual void Execute(const itk::Object * object, const itk::EventObject & event) ITK_OVERRIDE
{
OptimizerPointer optimizer = static_cast< OptimizerPointer >( object );
if( ! itk::IterationEvent().CheckEvent( &event ) )
{
return;
}
double currentValue = optimizer->GetValue();
// Only print out when the Metric value changes
if( std::fabs( m_LastMetricValue - currentValue ) > 1e-7 )
{
std::cout << optimizer->GetCurrentIteration() << " ";
std::cout << currentValue << " ";
std::cout << optimizer->GetCurrentPosition() << std::endl;
m_LastMetricValue = currentValue;
}
}
private:
double m_LastMetricValue;
};
}
int itkOnePlusOneEvolutionaryOptimizerTest(int, char* [] )
{
std::cout << "Gradient Descent Optimizer Test ";
std::cout << std::endl << std::endl;
typedef itk::OnePlusOneEvolutionaryOptimizer OptimizerType;
// Declaration of a itkOptimizer
OptimizerType::Pointer itkOptimizer = OptimizerType::New();
itk::OnePlusOneCommandIterationUpdate::Pointer observer = itk::OnePlusOneCommandIterationUpdate::New();
itkOptimizer->AddObserver( itk::IterationEvent(), observer );
// Declaration of the CostFunction
itk::OnePlusOneCostFunction::Pointer costFunction = itk::OnePlusOneCostFunction::New();
itkOptimizer->SetCostFunction( costFunction.GetPointer() );
typedef itk::OnePlusOneCostFunction::ParametersType ParametersType;
const unsigned int spaceDimension = costFunction->GetNumberOfParameters();
// We start not so far from | 2 -2 |
ParametersType initialPosition( spaceDimension );
initialPosition[0] = 100;
initialPosition[1] = -100;
itkOptimizer->MinimizeOn();
itkOptimizer->Initialize( 10 );
itkOptimizer->SetEpsilon( 0.1 );
itkOptimizer->SetMaximumIteration( 8000 );
typedef itk::Statistics::NormalVariateGenerator GeneratorType;
GeneratorType::Pointer generator = GeneratorType::New();
itkOptimizer->SetNormalVariateGenerator( generator );
itkOptimizer->SetInitialPosition( initialPosition );
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;
//
// 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;
}
}
// Exercise various member functions.
std::cout << "Maximize: " << itkOptimizer->GetMaximize() << std::endl;
std::cout << "Epsilon: " << itkOptimizer->GetEpsilon() << std::endl;
std::cout << "NumberOfIterations: " << itkOptimizer->GetMaximumIteration() << std::endl;
itkOptimizer->Print( std::cout );
std::cout << "Stop description = " << itkOptimizer->GetStopConditionDescription() << std::endl;
if( !pass )
{
std::cout << "Test failed." << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
|