hpp::core::pathOptimization::LinearConstraint Struct Reference

A linear constraint \( J \times x = b \). More...

#include <hpp/core/path-optimization/linear-constraint.hh>

Public Member Functions
	LinearConstraint (size_type inputSize, size_type outputSize)
	~LinearConstraint ()
void	concatenate (const LinearConstraint &oc)
bool	decompose (bool check=false, bool throwIfNotValid=false)
void	computeRank ()
	Compute rank of the constraint using a LU decomposition. More...
bool	reduceConstraint (const LinearConstraint &lc, LinearConstraint &lcr, bool computeRank=true) const
void	computeSolution (const vector_t &v)
bool	isSatisfied (const vector_t &x, const value_type &threshold=Eigen::NumTraits< value_type >::dummy_precision())
	Returns \( ( J \times x - b ).isZero (threshold) \). More...
void	addRows (const std::size_t &nbRows)

Public Attributes
Model
matrix_t	J
vector_t	b
Data
Solutions are \( \left\{ x^* + PK \times v, v \in \mathbb{R}^{nCols(J) - rank} \right\} \)
size_type	rank
	Rank of J. More...
matrix_t	PK
	Projector onto \( kernel(J) \). More...
vector_t	xStar
	\( x^* \) is a particular solution. More...
vector_t	xSol

Detailed Description

A linear constraint \( J \times x = b \).

Constructor & Destructor Documentation

LinearConstraint()

hpp::core::pathOptimization::LinearConstraint::LinearConstraint ( size_type  inputSize, size_type  outputSize  )

inline

~LinearConstraint()

hpp::core::pathOptimization::LinearConstraint::~LinearConstraint

(

)

Member Function Documentation

addRows()

void hpp::core::pathOptimization::LinearConstraint::addRows ( const std::size_t &  nbRows )

inline

computeRank()

void hpp::core::pathOptimization::LinearConstraint::computeRank ( )

inline

Compute rank of the constraint using a LU decomposition.

computeSolution()

void hpp::core::pathOptimization::LinearConstraint::computeSolution ( const vector_t &  v )

inline

Compute the unique solution derived from v into xSol. \( xSol \gets x^* + PK \times v \)

Parameters

v	an element of the kernel of matrix J.

Return values

this->xSol

concatenate()

void hpp::core::pathOptimization::LinearConstraint::concatenate ( const LinearConstraint &  oc )

inline

decompose()

bool hpp::core::pathOptimization::LinearConstraint::decompose	(	bool	check = false,
		bool	throwIfNotValid = false
	)

Compute one solution and a base of the kernel of matrix J. rank is also updated.

Parameters

check

If true, checks whether the constraint is feasible.

Returns

whether the constraint is feasible (alwys true when check is false)

isSatisfied()

bool hpp::core::pathOptimization::LinearConstraint::isSatisfied ( const vector_t &  x, const value_type &  threshold = Eigen::NumTraits<value_type>::dummy_precision()  )

inline

Returns \( ( J \times x - b ).isZero (threshold) \).

reduceConstraint()

bool hpp::core::pathOptimization::LinearConstraint::reduceConstraint ( const LinearConstraint &  lc, LinearConstraint &  lcr, bool  computeRank = true  ) const

inline

Reduced constraint into the set of solutions of this constraint.

Parameters

[in]	lc	the full constraint
[out]	lcr	the reduced constraint

Returns

if computeRank, returns true if the reduced constraint is full rank. if not computeRank, returns true.

Note

rank is computed using computeRank method.

Member Data Documentation

b

vector_t hpp::core::pathOptimization::LinearConstraint::b

J

matrix_t hpp::core::pathOptimization::LinearConstraint::J

PK

matrix_t hpp::core::pathOptimization::LinearConstraint::PK

Projector onto \( kernel(J) \).

rank

size_type hpp::core::pathOptimization::LinearConstraint::rank

Rank of J.

xSol

vector_t hpp::core::pathOptimization::LinearConstraint::xSol

xStar

vector_t hpp::core::pathOptimization::LinearConstraint::xStar

\( x^* \) is a particular solution.

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

• include/hpp/core/path-optimization/linear-constraint.hh