|
| | Brown () |
| std::string | name_impl () const |
| bool | evaluate_impl (const InputVector &x, OutputVector &out) const |
| bool | first_derivative_impl (const InputVector &x, Matrix &out) const |
| bool | second_derivative_impl (const InputVector &, Tensor &out) const |
| | Function () |
| std::string | name () const |
| bool | evaluate (const InputVector &x, OutputVector &out) const |
| bool | jacobian (const InputVector &x, Matrix &out) const |
| bool | hessian (const InputVector &x, Tensor &out) const |
| | FunctionBase () |
| std::string | name () const |
| bool | evaluate (const InputType &x, OutputType &out) const |
| bool | first_derivative (const InputType &x, FirstDerivativeType &out) const |
| bool | second_derivative (const InputType &x, SecondDerivativeType &out) const |
| constexpr Integer | input_dimension () const |
| constexpr Integer | output_dimension () const |
| const std::vector< InputType > & | solutions () const |
| const std::vector< InputType > & | guesses () const |
| const InputType & | solution (Integer const i) const |
| const InputType & | guess (Integer const i) const |
| bool | is_solution (const InputType &x, Real const tol=EPSILON_LOW) const |
template<typename Real>
class Optimist::TestSet::Brown< Real >
Class container for the Brown badly scaled function, which is defined as:
\[\mathbf{f}(\mathbf{x}) = \begin{bmatrix} x_1 - a \\ x_2 - 2a \\ x_1x_2 - 2 \end{bmatrix} \text{,}
\]
where \(a = 10^{-6}\). The function has one solution at \(\mathbf{x} = [a, 2a]^\top\), with \(f(\mathbf{x}) = 0\). The initial guess is generated at \(\mathbf{x} = [1, 1]^\top\).
- Template Parameters
-