ITK  4.8.0 Insight Segmentation and Registration Toolkit
WikiExamples/Math/AmoebaOptimization.cxx
// Include the Amoeba optimizer and a custom cost function
#include "ExampleCostFunction.h"
// Typedef the optimizer and cost function, for convenience
typedef itk::AmoebaOptimizer OptimizerType;
typedef itk::ExampleCostFunction CostType;
int main(int argc, char ** argv)
{
// Instantiate the optimizer
OptimizerType::Pointer optimizer = OptimizerType::New();
// Set properties pertinent to convergence
optimizer->SetMaximumNumberOfIterations( 100 );
optimizer->SetParametersConvergenceTolerance( 0.01 );
optimizer->SetFunctionConvergenceTolerance( 0.01 );
// Instantiate the cost function
// The cost function is a 2D paraboloid in the x-y plane
// with the equation f(x,y) = (x+5)^2+(y-7)^2 + 5
// and a global minimum at (x,y) = (-5, 7)
CostType::Pointer cost = CostType::New();
// Assign the cost function to the optimizer
optimizer->SetCostFunction( cost.GetPointer() );
// Set the initial parameters of the cost function
OptimizerType::ParametersType initial(2);
initial[0] = 123;
initial[1] = -97.4;
optimizer->SetInitialPosition( initial );
// Begin the optimization!
optimizer->StartOptimization();
// Print out some information about the optimization
std::cout << "Position: " << optimizer->GetCurrentPosition() << std::endl;
std::cout << "Value: " << optimizer->GetValue() << std::endl;
// As expected, the position is near to (-5, 7) and the value to 5
// Position: [-5.003825599641884, 6.998563761340231]
// Value: 5.00002
return EXIT_SUCCESS;
}