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 ![]() ![]() | |
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... | |
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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.
hessian | hessian will be stored here |
argument | point where the hessian will be computed |
functionId | evaluated function id in the split representation |
Implements roboptim::GenericTwiceDifferentiableFunction< T >.
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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.
hessian | hessian will be stored here |
argument | point where the hessian will be computed |
functionId | evaluated function id in the split representation |
Implements roboptim::GenericTwiceDifferentiableFunction< T >.
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