Implements a positive semidefinite constraint on a symmetric matrix S
\[\text{ S is p.s.d }\]
namely, all eigen values of S are non-negative.
- Note
- if the matix S has 1 row, then it is better to impose a linear inequality constraints; if it has 2 rows, then it is better to impose a rotated Lorentz cone constraint, since a 2 x 2 matrix S being p.s.d is equivalent to the constraint [S(0, 0), S(1, 1), S(0, 1)] in the rotated Lorentz cone.
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| PositiveSemidefiniteConstraint (int rows) |
| Impose the constraint that a symmetric matrix with size rows x rows is positive semidefinite. More...
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| ~PositiveSemidefiniteConstraint () override |
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int | matrix_rows () const |
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| PositiveSemidefiniteConstraint (const PositiveSemidefiniteConstraint &)=delete |
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PositiveSemidefiniteConstraint & | operator= (const PositiveSemidefiniteConstraint &)=delete |
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| PositiveSemidefiniteConstraint (PositiveSemidefiniteConstraint &&)=delete |
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PositiveSemidefiniteConstraint & | operator= (PositiveSemidefiniteConstraint &&)=delete |
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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...
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| 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...
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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...
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bool | CheckSatisfied (const Eigen::Ref< const AutoDiffVecXd > &x, double tol=1E-6) const |
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symbolic::Formula | CheckSatisfied (const Eigen::Ref< const VectorX< symbolic::Variable >> &x) const |
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const Eigen::VectorXd & | lower_bound () const |
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const Eigen::VectorXd & | upper_bound () const |
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int | num_constraints () const |
| Number of rows in the output constraint. More...
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| Constraint (const Constraint &)=delete |
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Constraint & | operator= (const Constraint &)=delete |
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| Constraint (Constraint &&)=delete |
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Constraint & | operator= (Constraint &&)=delete |
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virtual | ~EvaluatorBase () |
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void | Eval (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::VectorXd *y) const |
| Evaluates the expression. More...
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void | Eval (const Eigen::Ref< const AutoDiffVecXd > &x, AutoDiffVecXd *y) const |
| Evaluates the expression. More...
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void | Eval (const Eigen::Ref< const VectorX< symbolic::Variable >> &x, VectorX< symbolic::Expression > *y) const |
| Evaluates the expression. More...
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void | set_description (const std::string &description) |
| Set a human-friendly description for the evaluator. More...
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const std::string & | get_description () const |
| Getter for a human-friendly description for the evaluator. More...
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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...
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std::ostream & | Display (std::ostream &os) const |
| Formats this evaluator into the given stream, without displaying the decision variables it is bound to. More...
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std::string | ToLatex (const VectorX< symbolic::Variable > &vars, int precision=3) const |
| Returns a LaTeX string describing this evaluator. More...
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int | num_vars () const |
| Getter for the number of variables, namely the number of rows in x, as used in Eval(x, y). More...
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int | num_outputs () const |
| Getter for the number of outputs, namely the number of rows in y, as used in Eval(x, y). More...
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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...
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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...
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bool | is_thread_safe () const |
| Returns whether it is safe to call Eval in parallel. More...
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| EvaluatorBase (const EvaluatorBase &)=delete |
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EvaluatorBase & | operator= (const EvaluatorBase &)=delete |
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| EvaluatorBase (EvaluatorBase &&)=delete |
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EvaluatorBase & | operator= (EvaluatorBase &&)=delete |
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void | DoEval (const Eigen::Ref< const Eigen::VectorXd > &x, Eigen::VectorXd *y) const override |
| Evaluate the eigen values of the symmetric matrix. More...
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void | DoEval (const Eigen::Ref< const AutoDiffVecXd > &x, AutoDiffVecXd *y) const override |
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void | DoEval (const Eigen::Ref< const VectorX< symbolic::Variable >> &x, VectorX< symbolic::Expression > *y) const override |
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std::string | DoToLatex (const VectorX< symbolic::Variable > &, int) const override |
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void | UpdateLowerBound (const Eigen::Ref< const Eigen::VectorXd > &new_lb) |
| Updates the lower bound. More...
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void | UpdateUpperBound (const Eigen::Ref< const Eigen::VectorXd > &new_ub) |
| Updates the upper bound. More...
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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...
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virtual bool | DoCheckSatisfied (const Eigen::Ref< const Eigen::VectorXd > &x, const double tol) const |
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virtual bool | DoCheckSatisfied (const Eigen::Ref< const AutoDiffVecXd > &x, const double tol) const |
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virtual symbolic::Formula | DoCheckSatisfied (const Eigen::Ref< const VectorX< symbolic::Variable >> &x) const |
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| EvaluatorBase (int num_outputs, int num_vars, const std::string &description="") |
| Constructs a evaluator. More...
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virtual std::ostream & | DoDisplay (std::ostream &os, const VectorX< symbolic::Variable > &vars) const |
| NVI implementation of Display. More...
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void | set_num_outputs (int num_outputs) |
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void | set_is_thread_safe (bool is_thread_safe) |
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