proxsuite-nlp
0.10.0
A primal-dual augmented Lagrangian-type solver for nonlinear programming on manifolds.
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Linear function of difference vector on a manifold, of the form \( r(x) = A(x \ominus \bar{x}) + b \). More...
#include <proxsuite-nlp/modelling/residuals/linear.hpp>
Public Types | |
using | Scalar = _Scalar |
using | Base = ComposeFunctionTpl<Scalar> |
using | Manifold = ManifoldAbstractTpl<Scalar> |
Public Types inherited from proxsuite::nlp::ComposeFunctionTpl< _Scalar > | |
using | Scalar |
using | Base |
Public Types inherited from proxsuite::nlp::C2FunctionTpl< _Scalar > | |
using | Scalar |
using | Base |
Public Types inherited from proxsuite::nlp::C1FunctionTpl< _Scalar > | |
using | Scalar |
using | Base |
Public Types inherited from proxsuite::nlp::BaseFunctionTpl< _Scalar > | |
using | Scalar |
Public Types inherited from proxsuite::nlp::math_types< _Scalar > | |
using | Scalar = _Scalar |
Public Member Functions | |
LinearFunctionDifferenceToPoint (const polymorphic< Manifold > &space, const ConstVectorRef &target, const ConstMatrixRef &A, const ConstVectorRef &b) | |
Public Member Functions inherited from proxsuite::nlp::ComposeFunctionTpl< _Scalar > | |
ComposeFunctionTpl (const shared_ptr< Base > &left, const shared_ptr< Base > &right) | |
VectorXs | operator() (const ConstVectorRef &x) const |
Evaluate the residual at a given point x. | |
void | computeJacobian (const ConstVectorRef &x, MatrixRef Jout) const |
Jacobian matrix of the constraint function. | |
const Base & | left () const |
const Base & | right () const |
virtual void | vectorHessianProduct (const ConstVectorRef &, const ConstVectorRef &, MatrixRef Hout) const |
Vector-hessian product. | |
Public Member Functions inherited from proxsuite::nlp::C2FunctionTpl< _Scalar > | |
C2FunctionTpl (const int nx, const int ndx, const int nr) | |
C2FunctionTpl (const ManifoldAbstractTpl< _Scalar > &manifold, const int nr) | |
Public Member Functions inherited from proxsuite::nlp::C1FunctionTpl< _Scalar > | |
C1FunctionTpl (const int nx, const int ndx, const int nr) | |
C1FunctionTpl (const ManifoldAbstractTpl< _Scalar > &manifold, const int nr) | |
MatrixXs | computeJacobian (const ConstVectorRef &x) const |
Jacobian matrix of the constraint function. | |
Public Member Functions inherited from proxsuite::nlp::BaseFunctionTpl< _Scalar > | |
BaseFunctionTpl (const int nx, const int ndx, const int nr) | |
BaseFunctionTpl (const ManifoldAbstractTpl< _Scalar > &manifold, const int nr) | |
virtual | ~BaseFunctionTpl ()=default |
int | nx () const |
Get function input vector size (representation of manifold). | |
int | ndx () const |
Get input manifold's tangent space dimension. | |
int | nr () const |
Get function codimension. | |
Public Attributes | |
Scalar | |
Public Attributes inherited from proxsuite::nlp::ComposeFunctionTpl< _Scalar > | |
Scalar | |
Public Attributes inherited from proxsuite::nlp::C2FunctionTpl< _Scalar > | |
Scalar | |
Public Attributes inherited from proxsuite::nlp::C1FunctionTpl< _Scalar > | |
Scalar | |
Public Attributes inherited from proxsuite::nlp::BaseFunctionTpl< _Scalar > | |
Scalar | |
Public Attributes inherited from proxsuite::nlp::math_types< _Scalar > | |
_Scalar | |
Additional Inherited Members | |
Protected Attributes inherited from proxsuite::nlp::BaseFunctionTpl< _Scalar > | |
int | nx_ |
int | ndx_ |
int | nr_ |
Linear function of difference vector on a manifold, of the form \( r(x) = A(x \ominus \bar{x}) + b \).
Definition at line 41 of file linear.hpp.
using proxsuite::nlp::LinearFunctionDifferenceToPoint< _Scalar >::Scalar = _Scalar |
Definition at line 42 of file linear.hpp.
using proxsuite::nlp::LinearFunctionDifferenceToPoint< _Scalar >::Base = ComposeFunctionTpl<Scalar> |
Definition at line 43 of file linear.hpp.
using proxsuite::nlp::LinearFunctionDifferenceToPoint< _Scalar >::Manifold = ManifoldAbstractTpl<Scalar> |
Definition at line 46 of file linear.hpp.
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inline |
Definition at line 48 of file linear.hpp.
proxsuite::nlp::LinearFunctionDifferenceToPoint< _Scalar >::Scalar |
Definition at line 44 of file linear.hpp.