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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkFRPROptimizerTest.cxx,v $
Language: C++
Date: $Date: 2006-05-25 13:42:34 $
Version: $Revision: 1.2 $
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.
=========================================================================*/
#include <vnl/vnl_math.h>
#include "itkFRPROptimizer.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 FRPRGradientCostFunction : public itk::SingleValuedCostFunction
{
public:
typedef FRPRGradientCostFunction Self;
typedef itk::SingleValuedCostFunction Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
itkNewMacro( Self );
itkTypeMacro( FRPRGradientCostFunction, SingleValuedCostFunction );
enum { SpaceDimension=2 };
typedef Superclass::ParametersType ParametersType;
typedef Superclass::DerivativeType DerivativeType;
typedef Superclass::MeasureType MeasureType ;
FRPRGradientCostFunction()
{
}
MeasureType GetValue( const ParametersType & parameters ) const
{
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
{
double x = parameters[0];
double y = parameters[1];
std::cout << "GetDerivative( " ;
std::cout << x << " ";
std::cout << y << ") = ";
DerivativeType temp(SpaceDimension);
temp.Fill( 0 );
derivative = temp;
derivative[0] = 3 * x + 2 * y -2;
derivative[1] = 2 * x + 6 * y +8;
std::cout << derivative << std::endl;
}
unsigned int GetNumberOfParameters(void) const
{
return SpaceDimension;
}
private:
};
int itkFRPROptimizerTest(int, char* [] )
{
std::cout << "FRPR Optimizer Test ";
std::cout << std::endl << std::endl;
typedef itk::FRPROptimizer OptimizerType;
typedef OptimizerType::ScalesType ScalesType;
// Declaration of a itkOptimizer
OptimizerType::Pointer itkOptimizer = OptimizerType::New();
// Declaration of the CostFunction
FRPRGradientCostFunction::Pointer costFunction = FRPRGradientCostFunction::New();
itkOptimizer->SetCostFunction( costFunction.GetPointer() );
typedef FRPRGradientCostFunction::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->SetStepLength(0.01);
itkOptimizer->SetMaximize(false);
itkOptimizer->SetMaximumIteration( 50 );
{
// Exercise the methods that set the optimization mode
std::cout << "Testing Fletch Reeves Mode" << std::endl;
itkOptimizer->SetToFletchReeves();
itkOptimizer->SetInitialPosition( initialPosition );
try
{
itkOptimizer->StartOptimization();
}
catch( itk::ExceptionObject & e )
{
std::cout << "Exception thrown ! " << std::endl;
std::cout << "An error ocurred 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( vnl_math_abs( finalPosition[j] - trueParameters[j] ) > 0.01 )
pass = false;
}
// Exercise various member functions.
std::cout << "Maximize: " << itkOptimizer->GetMaximize() << std::endl;
std::cout << std::endl;
std::cout << "MaximumIteration: " << itkOptimizer->GetMaximumIteration();
std::cout << std::endl;
itkOptimizer->Print( std::cout );
if( !pass )
{
std::cout << "Test failed." << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
{
// Exercise the methods that set the optimization mode
std::cout << "Testing Polak Ribiere Mode" << std::endl;
itkOptimizer->SetToPolakRibiere();
itkOptimizer->SetInitialPosition( initialPosition );
try
{
itkOptimizer->StartOptimization();
}
catch( itk::ExceptionObject & e )
{
std::cout << "Exception thrown ! " << std::endl;
std::cout << "An error ocurred 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( vnl_math_abs( finalPosition[j] - trueParameters[j] ) > 0.01 )
pass = false;
}
// Exercise various member functions.
std::cout << "Maximize: " << itkOptimizer->GetMaximize() << std::endl;
std::cout << std::endl;
std::cout << "MaximumIteration: " << itkOptimizer->GetMaximumIteration();
std::cout << std::endl;
itkOptimizer->Print( std::cout );
if( !pass )
{
std::cout << "Test failed." << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
}
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