Abstracted Objective Functional class. More...

#include <op.hpp>

Public Types
using	ResultType = double

using	SensitivityType = std::vector< double >

using	EvalObjectiveFn = std::function< ResultType(const std::vector< double > &)>

using	EvalObjectiveGradFn = std::function< SensitivityType(const std::vector< double > &)>

Public Member Functions
	Functional (EvalObjectiveFn obj, EvalObjectiveGradFn grad, double lb=default_min, double ub=default_max)
	Objective container class. More...

ResultType	Eval (const std::vector< double > &v)
	Return the objective evaluation. More...

SensitivityType	EvalGradient (const std::vector< double > &v)
	return the objective gradient evaluation More...

Public Attributes
double	lower_bound
	Lower bounds for this optimization functional.

double	upper_bound
	Upper bounds for this optimization functional.

Static Public Attributes
static constexpr double	default_min = -std::numeric_limits<double>::max()

static constexpr double	default_max = std::numeric_limits<double>::max()

Detailed Description

Abstracted Objective Functional class.

Definition at line 118 of file op.hpp.

Constructor & Destructor Documentation

inline

Objective container class.

Parameters

obj	A simple function that calculates the objective
grad	A simple function that calculates the sensitivity

Definition at line 134 of file op.hpp.

ResultType op::Functional::Eval ( const std::vector< double > & v )

inline

Return the objective evaluation.

Parameters

[in] v input optimization vector to evaluate

Definition at line 144 of file op.hpp.

SensitivityType op::Functional::EvalGradient ( const std::vector< double > & v )

inline

return the objective gradient evaluation

Parameters

[in] v input optimization vector to evaluate

Definition at line 151 of file op.hpp.

The documentation for this class was generated from the following file: