Solver for C1 function with gradient computation, no constraint. More...
#include <roboptim/core/plugin/nag/nag-differentiable.hh>
Public Types | |
typedef Solver< EigenMatrixDense > | parent_t |
typedef Function::argument_t | argument_t |
typedef Function::result_t | result_t |
typedef DifferentiableFunction::gradient_t | gradient_t |
Public Member Functions | |
NagSolverDifferentiable (const problem_t &pb) | |
virtual | ~NagSolverDifferentiable () |
void | solve () |
Solve the problem. | |
void | setIterationCallback (callback_t callback) |
const callback_t & | callback () const |
solverState_t & | solverState () |
Solver for C1 function with gradient computation, no constraint.
Search for a minimum, in a given finite interval, of a continuous function of a single variable, using function and first derivative values. The method (based on cubic interpolation) is intended for functions which have a continuous first derivative (although it will usually work if the derivative has occasional discontinuities).
typedef Function::argument_t roboptim::NagSolverDifferentiable::argument_t |
typedef DifferentiableFunction::gradient_t roboptim::NagSolverDifferentiable::gradient_t |
typedef Solver<EigenMatrixDense> roboptim::NagSolverDifferentiable::parent_t |
typedef Function::result_t roboptim::NagSolverDifferentiable::result_t |
roboptim::NagSolverDifferentiable::NagSolverDifferentiable | ( | const problem_t & | pb | ) | [explicit] |
References DEFINE_PARAMETER.
const callback_t& roboptim::NagSolverDifferentiable::callback | ( | ) | const [inline] |
Referenced by roboptim::detail::nagSolverCallbackDifferentiable().
void roboptim::NagSolverDifferentiable::setIterationCallback | ( | callback_t | callback | ) | [inline] |
Solve the problem.
References roboptim::detail::nagSolverCallbackDifferentiable().
solverState_t& roboptim::NagSolverDifferentiable::solverState | ( | ) | [inline] |
Referenced by roboptim::detail::nagSolverCallbackDifferentiable().