void calculateJacobian(const arma::Mat<std::complex<double> >& myOffsets,
arma::Mat<double>& myJacobian,
arma::Col<std::complex<double> >& myTargetsCalculated,
arma::Col<std::complex<double> >& myCurrentGuess,
void myCalculateDependentVariables(const arma::Mat<std::complex<double> >&, const arma::Col<std::complex<double> >&, arma::Col<std::complex<double> >&))
{
//Calculate a temporary, unperturbed target evaluation, such as is needed for solving for the updated guess
//formula
arma::Col<std::complex<double> > unperturbedTargetsCalculated(NUMDIMENSIONS);
unperturbedTargetsCalculated.fill(0.0);
myCalculateDependentVariables(myOffsets, myCurrentGuess, unperturbedTargetsCalculated);
std::complex<double> oldGuessValue(0.0, 0.0);
//Each iteration fills a column in the Jacobian
//The Jacobian takes this form:
//
// dF0/dx0 dF0/dx1
// dF1/dx0 dF1/dx1
//
for(int j = 0; j< NUMDIMENSIONS; j++)
{
//Store old element value, perturb the current value
oldGuessValue = myCurrentGuess[j];
myCurrentGuess[j] += std::complex<double>(0.0, PROBEDISTANCE);
//Evaluate functions for perturbed guess
myCalculateDependentVariables(myOffsets, myCurrentGuess, myTargetsCalculated);
//The column of the Jacobian that goes with the independent variable we perturbed
//can be determined using the finite-difference formula
//The arma::Col allows this to be expressed as a single vector operation
//note slice works as: std::slice(start_index, number_of_elements_to_access, index_interval_between_selections)
//std::cout << "Jacobian column " << j << " with:" << std::endl;
//std::cout << "myTargetsCalculated" << std::endl;
//std::cout << myTargetsCalculated << std::endl;
//std::cout << "unperturbedTargetsCalculated" << std::endl;
//std::cout << unperturbedTargetsCalculated << std::endl;
myJacobian.col(j) = arma::imag(myTargetsCalculated);
myJacobian.col(j) *= pow(PROBEDISTANCE, -1.0);
//std::cout << "The jacobian: " << std::endl;
//std::cout << myJacobian << std::endl;
myCurrentGuess[j] = oldGuessValue;
}
//Reset to unperturbed, so we dont waste a function evaluation
myTargetsCalculated = unperturbedTargetsCalculated;
}
void calculateJacobian(const Teuchos::SerialDenseMatrix<int, std::complex<double> >& myOffsets,
Teuchos::SerialDenseMatrix<int, std::complex<double> >& myJacobian,
Teuchos::SerialDenseVector<int, std::complex<double> >& myTargetsCalculated,
Teuchos::SerialDenseVector<int, std::complex<double> >& myUnperturbedTargetsCalculated,
Teuchos::SerialDenseVector<int, std::complex<double> >& myCurrentGuess,
void myCalculateDependentVariables(const Teuchos::SerialDenseMatrix<int, std::complex<double> >&, const Teuchos::SerialDenseVector<int, std::complex<double> >&, Teuchos::SerialDenseVector<int, std::complex<double> >&)
)
{
//Calculate a temporary, unperturbed target evaluation, such as is needed for the finite-difference
//formula
myCalculateDependentVariables(myOffsets, myCurrentGuess, myUnperturbedTargetsCalculated);
std::complex<double> oldGuessValue;
//Each iteration fills a column in the Jacobian
//The Jacobian takes this form:
//
// dF0/dx0 dF0/dx1
// dF1/dx0 dF1/dx1
//
//
for(int column = 0; column< NUMDIMENSIONS; column++)
{
//Store old element value, perturb the current value
oldGuessValue = myCurrentGuess[column];
myCurrentGuess[column] += std::complex<double>(0.0, PROBEDISTANCE);
//Evaluate functions for perturbed guess
myCalculateDependentVariables(myOffsets, myCurrentGuess, myTargetsCalculated);
myTargetsCalculated *= pow(PROBEDISTANCE, -1.0);
for(int row = 0; row < NUMDIMENSIONS; row ++)
{
myJacobian(row, column) = std::imag(myTargetsCalculated[row]);
}
myCurrentGuess[column] = oldGuessValue;
}
//Reset to unperturbed, so we dont waste a function evaluation
myTargetsCalculated = myUnperturbedTargetsCalculated;
}
