Derived approximation class for first- or second-order Taylor series (a local approximation). More...
Public Member Functions | |
TaylorApproximation () | |
default constructor | |
TaylorApproximation (ProblemDescDB &problem_db, size_t num_vars) | |
standard constructor | |
TaylorApproximation (size_t num_vars, unsigned short data_order) | |
alternate constructor | |
~TaylorApproximation () | |
destructor | |
Protected Member Functions | |
int | min_coefficients () const |
return the minimum number of samples (unknowns) required to build the derived class approximation type in numVars dimensions | |
void | build () |
builds the approximation from scratch | |
const Real & | get_value (const RealVector &x) |
retrieve the approximate function value for a given parameter vector | |
const RealVector & | get_gradient (const RealVector &x) |
retrieve the approximate function gradient for a given parameter vector | |
const RealSymMatrix & | get_hessian (const RealVector &x) |
retrieve the approximate function Hessian for a given parameter vector |
Derived approximation class for first- or second-order Taylor series (a local approximation).
The TaylorApproximation class provides a local approximation based on data from a single point in parameter space. It uses a first- or second-order Taylor series expansion: f(x) = f(x_c) + grad(x_c)' (x - x_c) + (x - x_c)' Hess(x_c) (x - x_c) / 2.