Impose the matrix inequality constraint on variable x
\[ F_0 + x_1 F_1 + ... + x_n F_n \text{ is p.s.d} \]
where p.s.d stands for positive semidefinite.
\( F_0, F_1, ..., F_n \) are all given symmetric matrices of the same size.
- Note
- if the matrices Fᵢ all have 1 row, then it is better to impose a linear inequality constraints; if they all have 2 rows, then it is better to impose a rotated Lorentz cone constraint, since a 2 x 2 matrix X being p.s.d is equivalent to the constraint [X(0, 0), X(1, 1), X(0, 1)] in the rotated Lorentz cone.
|
| LinearMatrixInequalityConstraint (std::vector< Eigen::MatrixXd > F, double symmetry_tolerance=1E-10) |
|
| ~LinearMatrixInequalityConstraint () override |
|
const std::vector< Eigen::MatrixXd > & | F () const |
|
int | matrix_rows () const |
| Gets the number of rows in the matrix inequality constraint. More...
|
|
|
| LinearMatrixInequalityConstraint (const LinearMatrixInequalityConstraint &)=delete |
|
LinearMatrixInequalityConstraint & | operator= (const LinearMatrixInequalityConstraint &)=delete |
|
| LinearMatrixInequalityConstraint (LinearMatrixInequalityConstraint &&)=delete |
|
LinearMatrixInequalityConstraint & | operator= (LinearMatrixInequalityConstraint &&)=delete |
|
template<typename DerivedLB , typename DerivedUB > |
| Constraint (int num_constraints, int num_vars, const Eigen::MatrixBase< DerivedLB > &lb, const Eigen::MatrixBase< DerivedUB > &ub, const std::string &description="") |
| Constructs a constraint which has num_constraints rows, with an input num_vars x 1 vector. More...
|
|
| Constraint (int num_constraints, int num_vars) |
| Constructs a constraint which has num_constraints rows, with an input num_vars x 1 vector, with no bounds. More...
|
|
bool | CheckSatisfied (const Eigen::Ref< const Eigen::VectorXd > &x, double tol=1E-6) const |
| Return whether this constraint is satisfied by the given value, x . More...
|
|
bool | CheckSatisfied (const Eigen::Ref< const AutoDiffVecXd > &x, double tol=1E-6) const |
|
symbolic::Formula | CheckSatisfied (const Eigen::Ref< const VectorX< symbolic::Variable >> &x) const |
|
const Eigen::VectorXd & | lower_bound () const |
|
const Eigen::VectorXd & | upper_bound () const |
|
int | num_constraints () const |
| Number of rows in the output constraint. More...
|
|
| Constraint (const Constraint &)=delete |
|
Constraint & | operator= (const Constraint &)=delete |
|
| Constraint (Constraint &&)=delete |
|
Constraint & | operator= (Constraint &&)=delete |
|
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 |
|
|
void | DoEval (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::VectorXd *y) const override |
| Evaluate the eigen values of the linear matrix. More...
|
|
void | DoEval (const Eigen::Ref< const AutoDiffVecXd > &x, AutoDiffVecXd *y) const override |
| This function is not supported, since Eigen's eigen value solver does not accept AutoDiffXd. More...
|
|
void | DoEval (const Eigen::Ref< const VectorX< symbolic::Variable >> &x, VectorX< symbolic::Expression > *y) const override |
| This function is not supported, since Eigen's eigen value solver does not accept symbolic::Expression type. More...
|
|
std::string | DoToLatex (const VectorX< symbolic::Variable > &, int) const override |
|
void | UpdateLowerBound (const Eigen::Ref< const Eigen::VectorXd > &new_lb) |
| Updates the lower bound. More...
|
|
void | UpdateUpperBound (const Eigen::Ref< const Eigen::VectorXd > &new_ub) |
| Updates the upper bound. More...
|
|
void | set_bounds (const Eigen::Ref< const Eigen::VectorXd > &new_lb, const Eigen::Ref< const Eigen::VectorXd > &new_ub) |
| Set the upper and lower bounds of the constraint. More...
|
|
virtual bool | DoCheckSatisfied (const Eigen::Ref< const Eigen::VectorXd > &x, const double tol) const |
|
virtual bool | DoCheckSatisfied (const Eigen::Ref< const AutoDiffVecXd > &x, const double tol) const |
|
virtual symbolic::Formula | DoCheckSatisfied (const Eigen::Ref< const VectorX< symbolic::Variable >> &x) const |
|
| EvaluatorBase (int num_outputs, int num_vars, const std::string &description="") |
| Constructs a evaluator. More...
|
|
virtual std::ostream & | DoDisplay (std::ostream &os, const VectorX< symbolic::Variable > &vars) const |
| NVI implementation of Display. More...
|
|
void | set_num_outputs (int num_outputs) |
|
void | set_is_thread_safe (bool is_thread_safe) |
|