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 $\mathbb{R} \rightarrow \mathbb{R}^m$ function, derivable n times ( $n \geq 2$). 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
 
void roboptim::Cos< T >::impl_hessian (hessian_ref hessian, const_argument_ref x, size_type) const
 Hessian evaluation. More...
 
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
 
void roboptim::Sin< T >::impl_hessian (hessian_ref hessian, const_argument_ref x, size_type) const
 Hessian evaluation. More...
 

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

◆ impl_gradient() [2/3]

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

◆ impl_gradient() [3/3]

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

◆ impl_hessian() [1/2]

template<typename T >
void roboptim::Sin< T >::impl_hessian ( hessian_ref  hessian,
const_argument_ref  argument,
size_type  functionId 
) const
protectedvirtual

Hessian evaluation.

Compute the hessian, has to be implemented in concrete classes. The hessian is computed for a specific sub-function which id is passed through the functionId argument.

Warning
Do not call this function directly, call hessian instead.
Parameters
hessianhessian will be stored here
argumentpoint where the hessian will be computed
functionIdevaluated function id in the split representation

Implements roboptim::GenericTwiceDifferentiableFunction< T >.

◆ impl_hessian() [2/2]

template<typename T >
void roboptim::Cos< T >::impl_hessian ( hessian_ref  hessian,
const_argument_ref  argument,
size_type  functionId 
) const
protectedvirtual

Hessian evaluation.

Compute the hessian, has to be implemented in concrete classes. The hessian is computed for a specific sub-function which id is passed through the functionId argument.

Warning
Do not call this function directly, call hessian instead.
Parameters
hessianhessian will be stored here
argumentpoint where the hessian will be computed
functionIdevaluated function id in the split representation

Implements roboptim::GenericTwiceDifferentiableFunction< T >.

◆ impl_jacobian() [1/2]

template<typename T >
void roboptim::Cos< T >::impl_jacobian ( jacobian_ref  jacobian,
const_argument_ref  x 
) const
protected

◆ impl_jacobian() [2/2]

template<typename T >
void roboptim::Sin< T >::impl_jacobian ( jacobian_ref  jacobian,
const_argument_ref  x 
) const
protected