Optimist
0.0.0
A C++ library for optimization
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Class container for the Schaffer2 function. More...
#include <Schaffer2.hh>
Inherits Optimist::CostFunction< Real, 2, Schaffer2< Real > >.
Public Types | |
using | Vector = typename CostFunction<Real, 2, Schaffer2<Real>>::Vector |
using | RowVector = typename CostFunction<Real, 2, Schaffer2<Real>>::RowVector |
using | Matrix = typename CostFunction<Real, 2, Schaffer2<Real>>::Matrix |
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using | Vector |
using | RowVector |
using | Matrix |
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using | InputType |
using | OutputType |
using | FirstDerivativeType |
using | SecondDerivativeType |
Public Member Functions | |
Schaffer2 () | |
std::string | name_impl () const |
void | evaluate_impl (const Vector &x, Real &out) const |
void | first_derivative_impl (const Vector &x, RowVector &out) const |
void | second_derivative_impl (const Vector &x, Matrix &out) const |
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CostFunction () | |
std::string | name () const |
void | evaluate (const Vector &x, Vector &out) const |
void | gradient (const Vector &x, RowVector &out) const |
void | hessian (const Vector &x, Matrix &out) const |
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Function () | |
std::string | name () const |
void | evaluate (const InputType &x, OutputType &out) const |
void | first_derivative (const InputType &x, FirstDerivativeType &out) const |
void | 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 (const Integer i) const |
const InputType & | guess (const Integer i) const |
bool | is_solution (const InputType &x, const Real tol=EPSILON_LOW) const |
Additional Inherited Members | |
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friend | Function< Real, N, 1, CostFunction< Real, N, DerivedFunction > > |
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std::vector< InputType > | m_solutions |
std::vector< InputType > | m_guesses |
Class container for the Schaffer2 function, which is defined as:
\[f(\mathbf{x}) = 0.5 + \displaystyle\frac{\sin^{2}(x_1^2 - x_2^2) - 0.5}{(1 + 0.001(x_1^2 + x_2^2))^2} \text{.} \]
The function has global minima at \(\mathbf{x} = (0, 0)\), with \(f(\mathbf{x}) = 0\). The initial guesses are generated on the square \(x_i \in \left[-100, 100\right]\).
Real | Scalar number type. |
using Optimist::TestSet::Schaffer2< Real >::Matrix = typename CostFunction<Real, 2, Schaffer2<Real>>::Matrix |
Basic constants.
using Optimist::TestSet::Schaffer2< Real >::RowVector = typename CostFunction<Real, 2, Schaffer2<Real>>::RowVector |
using Optimist::TestSet::Schaffer2< Real >::Vector = typename CostFunction<Real, 2, Schaffer2<Real>>::Vector |
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Class constructor for the Schaffer2 function.
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Compute the function value at the input point.
[in] | x | Input point. |
[out] | out | The function value. |
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Compute the first derivative value at the input point.
[in] | x | Input point. |
[out] | out | The first derivative value. |
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Get the function name.
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Compute the second derivative value at the input point.
[in] | x | Input point. |
[out] | out | The second derivative value. |