Implements a constraint of the form \( lb <= x <= ub \).
Note: the base Constraint class (as implemented at the moment) could play this role. But this class enforces that it is ONLY a bounding box constraint, and not something more general. Some solvers use this information to handle bounding box constraints differently than general constraints, so use of this form is encouraged.
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| | BoundingBoxConstraint (const Eigen::Ref< const Eigen::VectorXd > &lb, const Eigen::Ref< const Eigen::VectorXd > &ub) |
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| | ~BoundingBoxConstraint () override |
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| | BoundingBoxConstraint (const BoundingBoxConstraint &)=delete |
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| BoundingBoxConstraint & | operator= (const BoundingBoxConstraint &)=delete |
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| | BoundingBoxConstraint (BoundingBoxConstraint &&)=delete |
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| BoundingBoxConstraint & | operator= (BoundingBoxConstraint &&)=delete |
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| | LinearConstraint (const Eigen::Ref< const Eigen::MatrixXd > &A, const Eigen::Ref< const Eigen::VectorXd > &lb, const Eigen::Ref< const Eigen::VectorXd > &ub) |
| | Construct the linear constraint lb <= A*x <= ub. More...
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| | LinearConstraint (const Eigen::SparseMatrix< double > &A, const Eigen::Ref< const Eigen::VectorXd > &lb, const Eigen::Ref< const Eigen::VectorXd > &ub) |
| | Overloads constructor with a sparse A matrix. More...
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| | ~LinearConstraint () override |
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| const Eigen::SparseMatrix< double > & | get_sparse_A () const |
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| const Eigen::MatrixXd & | GetDenseA () const |
| | Get the matrix A as a dense matrix. More...
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| void | UpdateCoefficients (const Eigen::Ref< const Eigen::MatrixXd > &new_A, const Eigen::Ref< const Eigen::VectorXd > &new_lb, const Eigen::Ref< const Eigen::VectorXd > &new_ub) |
| | Updates the linear term, upper and lower bounds in the linear constraint. More...
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| void | UpdateCoefficients (const Eigen::SparseMatrix< double > &new_A, const Eigen::Ref< const Eigen::VectorXd > &new_lb, const Eigen::Ref< const Eigen::VectorXd > &new_ub) |
| | Overloads UpdateCoefficients but with a sparse A matrix. More...
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| void | RemoveTinyCoefficient (double tol) |
| | Sets A(i, j) to zero if abs(A(i, j)) <= tol. More...
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| bool | is_dense_A_constructed () const |
| | Returns true iff this constraint already has a dense representation, i.e, if GetDenseA() will be cheap. 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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| 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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| | LinearConstraint (const LinearConstraint &)=delete |
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| LinearConstraint & | operator= (const LinearConstraint &)=delete |
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| | LinearConstraint (LinearConstraint &&)=delete |
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| LinearConstraint & | operator= (LinearConstraint &&)=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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| | 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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Public Member Functions inherited from LinearConstraint