Mathematical functions

Classes
class	roboptim::GenericConstantFunction< T >
	Constant function. More...
class	roboptim::Cos< T >
	Cos function. More...
class	roboptim::GenericIdentityFunction< T >
	Identity function. More...
class	roboptim::Polynomial< T >
	Polynomial function. More...
class	roboptim::Sin< T >
	Sin function. More...
class	roboptim::NTimesDerivableFunction< DerivabilityOrder >
	Define a function, derivable n times ( ). More...
class	roboptim::NTimesDerivableFunction< 2 >
	Explicit specialization for the stop case of NTimesDerivable class. More...
class	roboptim::GenericNumericLinearFunction< T >
	Build a linear function from a vector and a matrix. More...
class	roboptim::GenericNumericQuadraticFunction< T >
	Build a quadratic function from a matrix and a vector. More...

Functions
void	roboptim::Cos< T >::impl_gradient (gradient_ref gradient, const_argument_ref x, size_type) const
void	roboptim::Cos< T >::impl_jacobian (jacobian_ref jacobian, const_argument_ref x) const
	Jacobian evaluation.
void	roboptim::Cos< T >::impl_hessian (hessian_ref hessian, const_argument_ref x, size_type) const
void	roboptim::GenericIdentityFunction< T >::impl_gradient (gradient_ref gradient, const_argument_ref, size_type idFunction) const
void	roboptim::Sin< T >::impl_gradient (gradient_ref gradient, const_argument_ref x, size_type) const
void	roboptim::Sin< T >::impl_jacobian (jacobian_ref jacobian, const_argument_ref x) const
	Jacobian evaluation.
void	roboptim::Sin< T >::impl_hessian (hessian_ref hessian, const_argument_ref x, size_type) const

Detailed Description

Function Documentation

impl_gradient() [1/3]

template<typename T>

void roboptim::Cos< T >::impl_gradient ( gradient_ref gradient, const_argument_ref x, size_type  ) const

protected

References roboptim::GenericDifferentiableFunction< T >::gradient().

impl_gradient() [2/3]

template<typename T>

void roboptim::GenericIdentityFunction< T >::impl_gradient ( gradient_ref gradient, const_argument_ref , size_type idFunction ) const

protected

References roboptim::GenericDifferentiableFunction< T >::gradient().

impl_gradient() [3/3]

template<typename T>

void roboptim::Sin< T >::impl_gradient ( gradient_ref gradient, const_argument_ref x, size_type  ) const

protected

References roboptim::GenericDifferentiableFunction< T >::gradient().

impl_hessian() [1/2]

template<typename T>

void roboptim::Cos< T >::impl_hessian ( hessian_ref hessian, const_argument_ref x, size_type  ) const

protected

References roboptim::GenericTwiceDifferentiableFunction< T >::hessian().

impl_hessian() [2/2]

template<typename T>

void roboptim::Sin< T >::impl_hessian ( hessian_ref hessian, const_argument_ref x, size_type  ) const

protected

References roboptim::GenericTwiceDifferentiableFunction< T >::hessian().

impl_jacobian() [1/2]

template<typename T>

void roboptim::Cos< T >::impl_jacobian ( jacobian_ref jacobian, const_argument_ref arg ) const

protectedvirtual

Jacobian evaluation.

Computes the jacobian, can be overridden by concrete classes. The default behavior is to compute the jacobian from the gradient.

Warning

Do not call this function directly, call jacobian instead.

Parameters

jacobian	jacobian will be store in this argument
arg	point where the jacobian will be computed

Reimplemented from roboptim::GenericDifferentiableFunction< T >.

References roboptim::GenericDifferentiableFunction< T >::jacobian().

impl_jacobian() [2/2]

template<typename T>

void roboptim::Sin< T >::impl_jacobian ( jacobian_ref jacobian, const_argument_ref arg ) const

protectedvirtual

Jacobian evaluation.

Computes the jacobian, can be overridden by concrete classes. The default behavior is to compute the jacobian from the gradient.

Warning

Do not call this function directly, call jacobian instead.

Parameters

jacobian	jacobian will be store in this argument
arg	point where the jacobian will be computed

Reimplemented from roboptim::GenericDifferentiableFunction< T >.

References roboptim::GenericDifferentiableFunction< T >::jacobian().