/**
* Save current parameters, derivatives and hessian.
*/
void CostFuncLeastSquares::push() {
if (m_pushed) {
throw std::runtime_error("Least squares: double push.");
}
// make sure we are not dirty
m_pushedValue = valDerivHessian();
getParameters(m_pushedParams);
m_pushed = true;
}
/**
* Return cached or calculate the Hessian.
*/
const GSLMatrix &CostFuncLeastSquares::getHessian() const {
if (m_pushed) {
return m_hessian;
}
if (m_dirtyVal || m_dirtyDeriv || m_dirtyHessian) {
valDerivHessian();
}
return m_hessian;
}
/**
* Return cached or calculate the drivatives.
*/
const GSLVector &CostFuncLeastSquares::getDeriv() const {
if (m_pushed) {
return m_der;
}
if (m_dirtyVal || m_dirtyDeriv || m_dirtyHessian) {
valDerivHessian();
}
return m_der;
}
/**
* Calculates covariance matrix for fitting function's active parameters.
* @param covar :: Output cavariance matrix.
* @param epsrel :: Tolerance.
*/
void CostFuncLeastSquares::calActiveCovarianceMatrix(GSLMatrix& covar, double epsrel)
{
UNUSED_ARG(epsrel);
if (m_hessian.isEmpty())
{
valDerivHessian();
}
covar = m_hessian;
covar.invert();
}
/** Calculate the value and the derivatives of the cost function
* @param der :: Container to output the derivatives
* @return :: The value of the function
*/
double CostFuncLeastSquares::valAndDeriv(std::vector<double> &der) const {
valDerivHessian(true, false);
if (der.size() != nParams()) {
der.resize(nParams());
}
for (size_t i = 0; i < nParams(); ++i) {
der[i] = m_der.get(i);
}
return m_value;
}
/**
* Calculates covariance matrix for fitting function's active parameters.
* @param covar :: Output cavariance matrix.
* @param epsrel :: Tolerance.
*/
void CostFuncLeastSquares::calActiveCovarianceMatrix(GSLMatrix &covar,
double epsrel) {
UNUSED_ARG(epsrel);
if (m_hessian.isEmpty()) {
valDerivHessian();
}
if (g_log.is(Kernel::Logger::Priority::PRIO_DEBUG)) {
std::ostringstream osHess;
osHess << "== Hessian (H) ==\n";
osHess << std::left << std::fixed;
for (size_t i = 0; i < m_hessian.size1(); ++i) {
for (size_t j = 0; j < m_hessian.size2(); ++j) {
osHess << std::setw(10);
osHess << m_hessian.get(i, j) << " ";
}
osHess << "\n";
}
g_log.debug() << osHess.str();
}
covar = m_hessian;
covar.invert();
if (g_log.is(Kernel::Logger::Priority::PRIO_DEBUG)) {
std::ostringstream osCovar;
osCovar << "== Covariance matrix (H^-1) ==\n";
osCovar << std::left << std::fixed;
for (size_t i = 0; i < covar.size1(); ++i) {
for (size_t j = 0; j < covar.size2(); ++j) {
osCovar << std::setw(10);
osCovar << covar.get(i, j) << " ";
}
osCovar << "\n";
}
g_log.debug() << osCovar.str();
}
}
