QuadraticCost Class Reference

Detailed Description

Implements a cost of the form

\[ .5 x'Qx + b'x + c \]

.

#include <drake/solvers/cost.h>

Public Member Functions
template<typename DerivedQ , typename Derivedb >
	QuadraticCost (const Eigen::MatrixBase< DerivedQ > &Q, const Eigen::MatrixBase< Derivedb > &b, double c=0., std::optional< bool > is_hessian_psd=std::nullopt)
	Constructs a cost of the form \[ .5 x'Qx + b'x + c \] . More...
	~QuadraticCost () override
const Eigen::MatrixXd &	Q () const
	Returns the symmetric matrix Q, as the Hessian of the cost. More...
const Eigen::VectorXd &	b () const
double	c () const
bool	is_convex () const
	Returns true if this cost is convex. More...
template<typename DerivedQ , typename DerivedB >
void	UpdateCoefficients (const Eigen::MatrixBase< DerivedQ > &new_Q, const Eigen::MatrixBase< DerivedB > &new_b, double new_c=0., std::optional< bool > is_hessian_psd=std::nullopt)
	Updates the quadratic and linear term of the constraint. More...
void	UpdateHessianEntry (int i, int j, double val, std::optional< bool > is_hessian_psd=std::nullopt)
	Updates both Q(i, j) and Q(j, i) to val. More...
void	update_linear_coefficient_entry (int i, double val)
	Updates b(i)=val. More...
void	update_constant_term (double new_c)
	Updates the constant term to new_c. More...
Does not allow copy, move, or assignment
	QuadraticCost (const QuadraticCost &)=delete
QuadraticCost &	operator= (const QuadraticCost &)=delete
	QuadraticCost (QuadraticCost &&)=delete
QuadraticCost &	operator= (QuadraticCost &&)=delete
Public Member Functions inherited from Cost
	Cost (const Cost &)=delete
Cost &	operator= (const Cost &)=delete
	Cost (Cost &&)=delete
Cost &	operator= (Cost &&)=delete
Public Member Functions inherited from EvaluatorBase
virtual	~EvaluatorBase ()
void	Eval (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::VectorXd *y) const
	Evaluates the expression. More...
void	Eval (const Eigen::Ref< const AutoDiffVecXd > &x, AutoDiffVecXd *y) const
	Evaluates the expression. More...
void	Eval (const Eigen::Ref< const VectorX< symbolic::Variable >> &x, VectorX< symbolic::Expression > *y) const
	Evaluates the expression. More...
void	set_description (const std::string &description)
	Set a human-friendly description for the evaluator. More...
const std::string &	get_description () const
	Getter for a human-friendly description for the evaluator. More...
std::ostream &	Display (std::ostream &os, const VectorX< symbolic::Variable > &vars) const
	Formats this evaluator into the given stream using vars for the bound decision variable names. More...
std::ostream &	Display (std::ostream &os) const
	Formats this evaluator into the given stream, without displaying the decision variables it is bound to. More...
std::string	ToLatex (const VectorX< symbolic::Variable > &vars, int precision=3) const
	Returns a LaTeX string describing this evaluator. More...
int	num_vars () const
	Getter for the number of variables, namely the number of rows in x, as used in Eval(x, y). More...
int	num_outputs () const
	Getter for the number of outputs, namely the number of rows in y, as used in Eval(x, y). More...
void	SetGradientSparsityPattern (const std::vector< std::pair< int, int >> &gradient_sparsity_pattern)
	Set the sparsity pattern of the gradient matrix ∂y/∂x (the gradient of y value in Eval, w.r.t x in Eval) . More...
const std::optional< std::vector< std::pair< int, int > > > &	gradient_sparsity_pattern () const
	Returns the vector of (row_index, col_index) that contains all the entries in the gradient of Eval function (∂y/∂x) whose value could be non-zero, namely if ∂yᵢ/∂xⱼ could be non-zero, then the pair (i, j) is in gradient_sparsity_pattern. More...
bool	is_thread_safe () const
	Returns whether it is safe to call Eval in parallel. More...
	EvaluatorBase (const EvaluatorBase &)=delete
EvaluatorBase &	operator= (const EvaluatorBase &)=delete
	EvaluatorBase (EvaluatorBase &&)=delete
EvaluatorBase &	operator= (EvaluatorBase &&)=delete

Additional Inherited Members
Protected Member Functions inherited from Cost
	Cost (int num_vars, const std::string &description="")
	Constructs a cost evaluator. More...
Protected Member Functions inherited from EvaluatorBase
	EvaluatorBase (int num_outputs, int num_vars, const std::string &description="")
	Constructs a evaluator. More...
void	set_num_outputs (int num_outputs)
void	set_is_thread_safe (bool is_thread_safe)

Constructor & Destructor Documentation

QuadraticCost() [1/3]

QuadraticCost ( const QuadraticCost &  )

delete

QuadraticCost() [2/3]

QuadraticCost ( QuadraticCost &&  )

delete

QuadraticCost() [3/3]

QuadraticCost	(	const Eigen::MatrixBase< DerivedQ > &	Q,
		const Eigen::MatrixBase< Derivedb > &	b,
		double	c = 0.,
		std::optional< bool >	is_hessian_psd = std::nullopt
	)

Constructs a cost of the form

\[ .5 x'Qx + b'x + c \]

.

Parameters

Q	Quadratic term.
b	Linear term.
c	(optional) Constant term.
is_hessian_psd	(optional) Indicates if the Hessian matrix Q is positive semidefinite (psd) or not. If set to true, then the user guarantees that Q is psd; if set to false, then the user guarantees that Q is not psd. If set to std::nullopt, then the constructor will check if Q is psd or not. The default is std::nullopt. To speed up the constructor, set is_hessian_psd to either true or false.

~QuadraticCost()

~QuadraticCost ( )

override

Member Function Documentation

b()

const Eigen::VectorXd& b

(

)

const

c()

double c

(

)

const

is_convex()

bool is_convex

(

)

const

Returns true if this cost is convex.

A quadratic cost if convex if and only if its Hessian matrix Q is positive semidefinite.

operator=() [1/2]

QuadraticCost& operator= ( QuadraticCost &&  )

delete

operator=() [2/2]

QuadraticCost& operator= ( const QuadraticCost &  )

delete

Q()

const Eigen::MatrixXd& Q

(

)

const

Returns the symmetric matrix Q, as the Hessian of the cost.

update_constant_term()

void update_constant_term

(

double

new_c

)

Updates the constant term to new_c.

update_linear_coefficient_entry()

void update_linear_coefficient_entry	(	int	i,
		double	val
	)

Updates b(i)=val.

UpdateCoefficients()

void UpdateCoefficients	(	const Eigen::MatrixBase< DerivedQ > &	new_Q,
		const Eigen::MatrixBase< DerivedB > &	new_b,
		double	new_c = 0.,
		std::optional< bool >	is_hessian_psd = std::nullopt
	)

Updates the quadratic and linear term of the constraint.

The new matrices need to have the same dimension as before.

Parameters

new_Q	New quadratic term.
new_b	New linear term.
new_c	(optional) New constant term.
is_hessian_psd	(optional) Indicates if the Hessian matrix Q is positive semidefinite (psd) or not. If set to true, then the user guarantees that Q is psd; if set to false, then the user guarantees that Q is not psd. If set to std::nullopt, then this function will check if Q is psd or not. The default is std::nullopt. To speed up the computation, set is_hessian_psd to either true or false.

UpdateHessianEntry()

void UpdateHessianEntry	(	int	i,
		int	j,
		double	val,
		std::optional< bool >	is_hessian_psd = std::nullopt
	)

Updates both Q(i, j) and Q(j, i) to val.

Parameters

is_hessian_psd

If this is nullopt, the new Hessian is checked (possibly expensively) for PSD-ness. If this is set true/false, the cost's convexity is updated to that value without checking (it is the user's responsibility to make sure the flag is set correctly).

Note

If you have multiple entries in the Hessian matrix to update, and you don't specify is_hessian_psd, then it is much faster to call UpdateCoefficients(new_A, new_b) where new_A contains all the updated entries.

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

• drake/solvers/cost.h