#include <test_04.hpp>

Inheritance diagram for EqualityConstraint_BurgersControl< Real >:

Public Member Functions
	EqualityConstraint_BurgersControl (const Teuchos::RCP< BurgersFEM< Real > > &fem, const bool useHessian=true)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (int nx=128, Real nu=1.e-2, Real u0=1.0, Real u1=0.0, Real f=0.0)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (int nx=128, int nt=100, Real T=1, Real nu=1.e-2, Real u0=0.0, Real u1=0.0, Real f=0.0)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	solve (ROL::Vector< Real > &c, ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Given $z$, solve $c(u,z)=0$ for $u$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &hwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (Teuchos::RCP< BurgersFEM< Real > > &fem, bool useHessian=true)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (int nx=128)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	solve (ROL::Vector< Real > &c, ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Given $z$, solve $c(u,z)=0$ for $u$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (Teuchos::RCP< BurgersFEM< Real > > &fem, bool useHessian=true)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (Teuchos::RCP< BurgersFEM< Real > > &fem, bool useHessian=true)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

	EqualityConstraint_BurgersControl (Teuchos::RCP< BurgersFEM< Real > > &fem, bool useHessian=true)

void	value (ROL::Vector< Real > &c, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$. More...

void	applyJacobian_1 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$. More...

void	applyJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$. More...

void	applyInverseJacobian_1 (ROL::Vector< Real > &ijv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$. More...

void	applyAdjointJacobian_1 (ROL::Vector< Real > &ajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the primary interface. More...

void	applyAdjointJacobian_2 (ROL::Vector< Real > &jv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the primary interface. More...

void	applyInverseAdjointJacobian_1 (ROL::Vector< Real > &iajv, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-} \in L(\mathcal{U}^, \mathcal{C}^*)$, to the vector $v$. More...

void	applyAdjointHessian_11 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_12 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_21 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$. More...

void	applyAdjointHessian_22 (ROL::Vector< Real > &ahwv, const ROL::Vector< Real > &w, const ROL::Vector< Real > &v, const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, Real &tol)
	Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$. More...

Public Member Functions inherited from ROL::EqualityConstraint_SimOpt< Real >
	EqualityConstraint_SimOpt ()

virtual void	update (const Vector< Real > &u, const Vector< Real > &z, bool flag=true, int iter=-1)
	Update constraint functions. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count. More...

virtual void	update_1 (const Vector< Real > &u, bool flag=true, int iter=-1)
	Update constraint functions with respect to Sim variable. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count. More...

virtual void	update_2 (const Vector< Real > &z, bool flag=true, int iter=-1)
	Update constraint functions with respect to Opt variable. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count. More...

virtual void	setSolveParameters (Teuchos::ParameterList &parlist)
	Set solve parameters. More...

virtual void	applyAdjointJacobian_1 (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &dualv, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^, \mathcal{U}^)$, to the vector $v$. This is the secondary interface, for use with dual spaces where the user does not define the dual() operation. More...

virtual void	applyAdjointJacobian_2 (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &dualv, Real &tol)
	Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^, \mathcal{Z}^)$, to vector $v$. This is the secondary interface, for use with dual spaces where the user does not define the dual() operation. More...

virtual std::vector< Real >	solveAugmentedSystem (Vector< Real > &v1, Vector< Real > &v2, const Vector< Real > &b1, const Vector< Real > &b2, const Vector< Real > &x, Real &tol)
	Approximately solves the augmented system \[ \begin{pmatrix} I & c'(x)^* \\ c'(x) & 0 \end{pmatrix} \begin{pmatrix} v_{1} \\ v_{2} \end{pmatrix} = \begin{pmatrix} b_{1} \\ b_{2} \end{pmatrix} \] where $v_{1} \in \mathcal{X}$, $v_{2} \in \mathcal{C}^$, $b_{1} \in \mathcal{X}^$, $b_{2} \in \mathcal{C}$, $I : \mathcal{X} \rightarrow \mathcal{X}^$ is an identity operator, and $0 : \mathcal{C}^ \rightarrow \mathcal{C}$ is a zero operator. More...

virtual void	applyPreconditioner (Vector< Real > &pv, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &g, Real &tol)
	Apply a constraint preconditioner at $x$, $P(x) \in L(\mathcal{C}, \mathcal{C})$, to vector $v$. In general, this preconditioner satisfies the following relationship: \[ c'(x) c'(x)^* P(x) v \approx v \,. \] It is used by the solveAugmentedSystem method. More...

virtual void	update (const Vector< Real > &x, bool flag=true, int iter=-1)
	Update constraint functions. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count. More...

virtual bool	isFeasible (const Vector< Real > &v)
	Check if the vector, v, is feasible. More...

virtual void	value (Vector< Real > &c, const Vector< Real > &x, Real &tol)
	Evaluate the constraint operator $c:\mathcal{X} \rightarrow \mathcal{C}$ at $x$. More...

virtual void	applyJacobian (Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply the constraint Jacobian at $x$, $c'(x) \in L(\mathcal{X}, \mathcal{C})$, to vector $v$. More...

virtual void	applyAdjointJacobian (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply the adjoint of the the constraint Jacobian at $x$, $c'(x)^* \in L(\mathcal{C}^, \mathcal{X}^)$, to vector $v$. More...

virtual void	applyAdjointHessian (Vector< Real > &ahwv, const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
	Apply the derivative of the adjoint of the constraint Jacobian at $x$ to vector $u$ in direction $v$, according to $ v \mapsto c''(x)(v,\cdot)^*u $. More...

virtual Real	checkSolve (const ROL::Vector< Real > &u, const ROL::Vector< Real > &z, const ROL::Vector< Real > &c, const bool printToStream=true, std::ostream &outStream=std::cout)

virtual Real	checkAdjointConsistencyJacobian_1 (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const bool printToStream=true, std::ostream &outStream=std::cout)
	Check the consistency of the Jacobian and its adjoint. This is the primary interface. More...

virtual Real	checkAdjointConsistencyJacobian_1 (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &dualw, const Vector< Real > &dualv, const bool printToStream=true, std::ostream &outStream=std::cout)
	Check the consistency of the Jacobian and its adjoint. This is the secondary interface, for use with dual spaces where the user does not define the dual() operation. More...

virtual Real	checkAdjointConsistencyJacobian_2 (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const bool printToStream=true, std::ostream &outStream=std::cout)
	Check the consistency of the Jacobian and its adjoint. This is the primary interface. More...

virtual Real	checkAdjointConsistencyJacobian_2 (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &dualw, const Vector< Real > &dualv, const bool printToStream=true, std::ostream &outStream=std::cout)
	Check the consistency of the Jacobian and its adjoint. This is the secondary interface, for use with dual spaces where the user does not define the dual() operation. More...

virtual Real	checkInverseJacobian_1 (const Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const bool printToStream=true, std::ostream &outStream=std::cout)

virtual Real	checkInverseAdjointJacobian_1 (const Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, const bool printToStream=true, std::ostream &outStream=std::cout)

std::vector< std::vector< Real > >	checkApplyJacobian_1 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &v, const Vector< Real > &jv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)

std::vector< std::vector< Real > >	checkApplyJacobian_1 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &v, const Vector< Real > &jv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)

std::vector< std::vector< Real > >	checkApplyJacobian_2 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &v, const Vector< Real > &jv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)

std::vector< std::vector< Real > >	checkApplyJacobian_2 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &v, const Vector< Real > &jv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_11 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_11 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_21 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_21 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_12 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_12 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_22 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)

std::vector< std::vector< Real > >	checkApplyAdjointHessian_22 (const Vector< Real > &u, const Vector< Real > &z, const Vector< Real > &p, const Vector< Real > &v, const Vector< Real > &hv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)

Public Member Functions inherited from ROL::EqualityConstraint< Real >
virtual	~EqualityConstraint ()

virtual void	applyAdjointJacobian (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &dualv, Real &tol)
	Apply the adjoint of the the constraint Jacobian at $x$, $c'(x)^* \in L(\mathcal{C}^, \mathcal{X}^)$, to vector $v$. More...

	EqualityConstraint (void)

void	activate (void)
	Turn on constraints. More...

void	deactivate (void)
	Turn off constraints. More...

bool	isActivated (void)
	Check if constraints are on. More...

virtual std::vector < std::vector< Real > >	checkApplyJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &jv, const std::vector< Real > &steps, const bool printToStream=true, std::ostream &outStream=std::cout, const int order=1)
	Finite-difference check for the constraint Jacobian application. More...

virtual std::vector < std::vector< Real > >	checkApplyJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &jv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
	Finite-difference check for the constraint Jacobian application. More...

virtual std::vector < std::vector< Real > >	checkApplyAdjointJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &c, const Vector< Real > &ajv, const bool printToStream=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS)
	Finite-difference check for the application of the adjoint of constraint Jacobian. More...

virtual Real	checkAdjointConsistencyJacobian (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &x, const bool printToStream=true, std::ostream &outStream=std::cout)

virtual Real	checkAdjointConsistencyJacobian (const Vector< Real > &w, const Vector< Real > &v, const Vector< Real > &x, const Vector< Real > &dualw, const Vector< Real > &dualv, const bool printToStream=true, std::ostream &outStream=std::cout)

virtual std::vector < std::vector< Real > >	checkApplyAdjointHessian (const Vector< Real > &x, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &hv, const std::vector< Real > &step, const bool printToScreen=true, std::ostream &outStream=std::cout, const int order=1)
	Finite-difference check for the application of the adjoint of constraint Hessian. More...

virtual std::vector < std::vector< Real > >	checkApplyAdjointHessian (const Vector< Real > &x, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &hv, const bool printToScreen=true, std::ostream &outStream=std::cout, const int numSteps=ROL_NUM_CHECKDERIV_STEPS, const int order=1)
	Finite-difference check for the application of the adjoint of constraint Hessian. More...

virtual void	setParameter (const std::vector< Real > &param)

Private Types
typedef H1VectorPrimal< Real >	PrimalStateVector

typedef H1VectorDual< Real >	DualStateVector

typedef L2VectorPrimal< Real >	PrimalControlVector

typedef L2VectorDual< Real >	DualControlVector

typedef H1VectorDual< Real >	PrimalConstraintVector

typedef H1VectorPrimal< Real >	DualConstraintVector

typedef H1VectorPrimal< Real >	PrimalStateVector

typedef H1VectorDual< Real >	DualStateVector

typedef L2VectorPrimal< Real >	PrimalControlVector

typedef L2VectorDual< Real >	DualControlVector

typedef H1VectorDual< Real >	PrimalConstraintVector

typedef H1VectorPrimal< Real >	DualConstraintVector

typedef H1VectorPrimal< Real >	PrimalStateVector

typedef H1VectorDual< Real >	DualStateVector

typedef L2VectorPrimal< Real >	PrimalControlVector

typedef L2VectorDual< Real >	DualControlVector

typedef H1VectorDual< Real >	PrimalConstraintVector

typedef H1VectorPrimal< Real >	DualConstraintVector

typedef H1VectorPrimal< Real >	PrimalStateVector

typedef H1VectorDual< Real >	DualStateVector

typedef L2VectorPrimal< Real >	PrimalControlVector

typedef L2VectorDual< Real >	DualControlVector

typedef H1VectorDual< Real >	PrimalConstraintVector

typedef H1VectorPrimal< Real >	DualConstraintVector

typedef std::vector< Real > ::size_type	uint

typedef H1VectorPrimal< Real >	PrimalStateVector

typedef H1VectorDual< Real >	DualStateVector

typedef L2VectorPrimal< Real >	PrimalControlVector

typedef L2VectorDual< Real >	DualControlVector

typedef H1VectorDual< Real >	PrimalConstraintVector

typedef H1VectorPrimal< Real >	DualConstraintVector

Private Member Functions
Real	compute_norm (const std::vector< Real > &r)

Real	dot (const std::vector< Real > &x, const std::vector< Real > &y)

void	update (std::vector< Real > &u, const std::vector< Real > &s, const Real alpha=1.0)

void	scale (std::vector< Real > &u, const Real alpha=0.0)

void	compute_residual (std::vector< Real > &r, const std::vector< Real > &u, const std::vector< Real > &z)

void	compute_pde_jacobian (std::vector< Real > &dl, std::vector< Real > &d, std::vector< Real > &du, const std::vector< Real > &u)

void	linear_solve (std::vector< Real > &u, std::vector< Real > &dl, std::vector< Real > &d, std::vector< Real > &du, const std::vector< Real > &r, const bool transpose=false)

Real	compute_norm (const std::vector< Real > &r)

Real	dot (const std::vector< Real > &x, const std::vector< Real > &y)

void	update (std::vector< Real > &u, const std::vector< Real > &s, const Real alpha=1.0)

void	scale (std::vector< Real > &u, const Real alpha=0.0)

void	compute_residual (std::vector< Real > &r, const std::vector< Real > &uold, const std::vector< Real > &zold, const std::vector< Real > &unew, const std::vector< Real > &znew)

void	compute_pde_jacobian (std::vector< Real > &dl, std::vector< Real > &d, std::vector< Real > &du, const std::vector< Real > &u)

void	apply_pde_jacobian_new (std::vector< Real > &jv, const std::vector< Real > &v, const std::vector< Real > &u, bool adjoint=false)

void	apply_pde_jacobian_old (std::vector< Real > &jv, const std::vector< Real > &v, const std::vector< Real > &u, bool adjoint=false)

void	apply_pde_jacobian (std::vector< Real > &jv, const std::vector< Real > &vold, const std::vector< Real > &uold, const std::vector< Real > &vnew, const std::vector< Real > unew, bool adjoint=false)

void	apply_pde_hessian (std::vector< Real > &hv, const std::vector< Real > &wold, const std::vector< Real > &vold, const std::vector< Real > &wnew, const std::vector< Real > &vnew)

void	apply_control_jacobian (std::vector< Real > &jv, const std::vector< Real > &v, bool adjoint=false)

void	run_newton (std::vector< Real > &u, const std::vector< Real > &znew, const std::vector< Real > &uold, const std::vector< Real > &zold)

void	linear_solve (std::vector< Real > &u, const std::vector< Real > &dl, const std::vector< Real > &d, const std::vector< Real > &du, const std::vector< Real > &r, const bool transpose=false)

Real	compute_norm (const std::vector< Real > &r)

Real	dot (const std::vector< Real > &x, const std::vector< Real > &y)

void	update (std::vector< Real > &u, const std::vector< Real > &s, const Real alpha=1.0)

void	scale (std::vector< Real > &u, const Real alpha=0.0)

void	compute_residual (std::vector< Real > &r, const std::vector< Real > &u, const std::vector< Real > &z)

void	compute_pde_jacobian (std::vector< Real > &dl, std::vector< Real > &d, std::vector< Real > &du, const std::vector< Real > &u)

void	linear_solve (std::vector< Real > &u, std::vector< Real > &dl, std::vector< Real > &d, std::vector< Real > &du, const std::vector< Real > &r, const bool transpose=false)

Private Attributes
Teuchos::RCP< BurgersFEM< Real > >	fem_

bool	useHessian_

int	nx_

Real	dx_

Real	nu_

Real	u0_

Real	u1_

Real	f_

unsigned	nx_

unsigned	nt_

Real	T_

Real	dt_

std::vector< Real >	u_init_

Additional Inherited Members
Protected Member Functions inherited from ROL::EqualityConstraint< Real >
const std::vector< Real >	getParameter (void) const

Detailed Description

template<class Real>
class EqualityConstraint_BurgersControl< Real >

Definition at line 869 of file test_04.hpp.

Member Typedef Documentation

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalStateVector

private

Definition at line 872 of file test_04.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualStateVector

private

Definition at line 873 of file test_04.hpp.

template<class Real>

typedef L2VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalControlVector

private

Definition at line 875 of file test_04.hpp.

template<class Real>

typedef L2VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualControlVector

private

Definition at line 876 of file test_04.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::PrimalConstraintVector

private

Definition at line 878 of file test_04.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::DualConstraintVector

private

Definition at line 879 of file test_04.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalStateVector

private

Definition at line 864 of file example_04.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualStateVector

private

Definition at line 865 of file example_04.hpp.

template<class Real>

typedef L2VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalControlVector

private

Definition at line 867 of file example_04.hpp.

template<class Real>

typedef L2VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualControlVector

private

Definition at line 868 of file example_04.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::PrimalConstraintVector

private

Definition at line 870 of file example_04.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::DualConstraintVector

private

Definition at line 871 of file example_04.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalStateVector

private

Definition at line 868 of file example_06.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualStateVector

private

Definition at line 869 of file example_06.hpp.

template<class Real>

typedef L2VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalControlVector

private

Definition at line 871 of file example_06.hpp.

template<class Real>

typedef L2VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualControlVector

private

Definition at line 872 of file example_06.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::PrimalConstraintVector

private

Definition at line 874 of file example_06.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::DualConstraintVector

private

Definition at line 875 of file example_06.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalStateVector

private

Definition at line 872 of file example_07.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualStateVector

private

Definition at line 873 of file example_07.hpp.

template<class Real>

typedef L2VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalControlVector

private

Definition at line 875 of file example_07.hpp.

template<class Real>

typedef L2VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualControlVector

private

Definition at line 876 of file example_07.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::PrimalConstraintVector

private

Definition at line 878 of file example_07.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::DualConstraintVector

private

Definition at line 879 of file example_07.hpp.

template<class Real>

typedef std::vector<Real>::size_type EqualityConstraint_BurgersControl< Real >::uint

private

Definition at line 881 of file example_07.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalStateVector

private

Definition at line 868 of file example_08.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualStateVector

private

Definition at line 869 of file example_08.hpp.

template<class Real>

typedef L2VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::PrimalControlVector

private

Definition at line 871 of file example_08.hpp.

template<class Real>

typedef L2VectorDual<Real> EqualityConstraint_BurgersControl< Real >::DualControlVector

private

Definition at line 872 of file example_08.hpp.

template<class Real>

typedef H1VectorDual<Real> EqualityConstraint_BurgersControl< Real >::PrimalConstraintVector

private

Definition at line 874 of file example_08.hpp.

template<class Real>

typedef H1VectorPrimal<Real> EqualityConstraint_BurgersControl< Real >::DualConstraintVector

private

Definition at line 875 of file example_08.hpp.

Constructor & Destructor Documentation

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	const Teuchos::RCP< BurgersFEM< Real > > &	fem,
		const bool	useHessian = `true`
	)

inline

Definition at line 885 of file test_04.hpp.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	int	nx = `128`,
		Real	nu = `1.e-2`,
		Real	u0 = `1.0`,
		Real	u1 = `0.0`,
		Real	f = `0.0`
	)

inline

Definition at line 188 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	int	nx = `128`,
		int	nt = `100`,
		Real	T = `1`,
		Real	nu = `1.e-2`,
		Real	u0 = `0.0`,
		Real	u1 = `0.0`,
		Real	f = `0.0`
	)

inline

Definition at line 431 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nx_, and EqualityConstraint_BurgersControl< Real >::u_init_.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	Teuchos::RCP< BurgersFEM< Real > > &	fem,
		bool	useHessian = `true`
	)

inline

Definition at line 877 of file example_04.hpp.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl ( int nx = 128 )

inline

Definition at line 193 of file example_05.hpp.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	Teuchos::RCP< BurgersFEM< Real > > &	fem,
		bool	useHessian = `true`
	)

inline

Definition at line 881 of file example_06.hpp.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	Teuchos::RCP< BurgersFEM< Real > > &	fem,
		bool	useHessian = `true`
	)

inline

Definition at line 887 of file example_07.hpp.

template<class Real>

EqualityConstraint_BurgersControl< Real >::EqualityConstraint_BurgersControl	(	Teuchos::RCP< BurgersFEM< Real > > &	fem,
		bool	useHessian = `true`
	)

inline

Definition at line 881 of file example_08.hpp.

Member Function Documentation

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 889 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

Referenced by EqualityConstraint_BurgersControl< Real >::solve().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 901 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 915 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 929 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 943 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 957 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 971 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

Referenced by main().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 985 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1006 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1026 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1046 of file test_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

Real EqualityConstraint_BurgersControl< Real >::compute_norm ( const std::vector< Real > & r )

inlineprivate

Definition at line 76 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dot().

Referenced by EqualityConstraint_BurgersControl< Real >::run_newton().

template<class Real>

Real EqualityConstraint_BurgersControl< Real >::dot	(	const std::vector< Real > &	x,
		const std::vector< Real > &	y
	)

inlineprivate

Definition at line 80 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

Referenced by EqualityConstraint_BurgersControl< Real >::compute_norm(), and EqualityConstraint_BurgersControl< Real >::linear_solve().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::update	(	std::vector< Real > &	u,
		const std::vector< Real > &	s,
		const Real	alpha = `1.0`
	)

inlineprivate

Definition at line 99 of file burgers-control/example_02.hpp.

Referenced by EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1(), EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1(), and EqualityConstraint_BurgersControl< Real >::run_newton().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::scale	(	std::vector< Real > &	u,
		const Real	alpha = `0.0`
	)

inlineprivate

Definition at line 105 of file burgers-control/example_02.hpp.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::compute_residual	(	std::vector< Real > &	r,
		const std::vector< Real > &	u,
		const std::vector< Real > &	z
	)

inlineprivate

Definition at line 111 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::f_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

Referenced by EqualityConstraint_BurgersControl< Real >::run_newton(), and EqualityConstraint_BurgersControl< Real >::value().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian	(	std::vector< Real > &	dl,
		std::vector< Real > &	d,
		std::vector< Real > &	du,
		const std::vector< Real > &	u
	)

inlineprivate

Definition at line 143 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

Referenced by EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1(), EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1(), and EqualityConstraint_BurgersControl< Real >::run_newton().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::linear_solve	(	std::vector< Real > &	u,
		std::vector< Real > &	dl,
		std::vector< Real > &	d,
		std::vector< Real > &	du,
		const std::vector< Real > &	r,
		const bool	transpose = `false`
	)

inlineprivate

Definition at line 168 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::nx_.

Referenced by EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1(), EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1(), and EqualityConstraint_BurgersControl< Real >::run_newton().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 193 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_residual().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 204 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 232 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 248 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::linear_solve(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 267 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 295 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 324 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::linear_solve(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 341 of file burgers-control/example_02.hpp.

References EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 365 of file burgers-control/example_02.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 369 of file burgers-control/example_02.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 373 of file burgers-control/example_02.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

Real EqualityConstraint_BurgersControl< Real >::compute_norm ( const std::vector< Real > & r )

inlineprivate

Definition at line 84 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dot().

template<class Real>

Real EqualityConstraint_BurgersControl< Real >::dot	(	const std::vector< Real > &	x,
		const std::vector< Real > &	y
	)

inlineprivate

Definition at line 88 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::update	(	std::vector< Real > &	u,
		const std::vector< Real > &	s,
		const Real	alpha = `1.0`
	)

inlineprivate

Definition at line 107 of file example_03.hpp.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::scale	(	std::vector< Real > &	u,
		const Real	alpha = `0.0`
	)

inlineprivate

Definition at line 113 of file example_03.hpp.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::compute_residual	(	std::vector< Real > &	r,
		const std::vector< Real > &	uold,
		const std::vector< Real > &	zold,
		const std::vector< Real > &	unew,
		const std::vector< Real > &	znew
	)

inlineprivate

Definition at line 119 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::f_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian	(	std::vector< Real > &	dl,
		std::vector< Real > &	d,
		std::vector< Real > &	du,
		const std::vector< Real > &	u
	)

inlineprivate

Definition at line 155 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian_new	(	std::vector< Real > &	jv,
		const std::vector< Real > &	v,
		const std::vector< Real > &	u,
		bool	adjoint = `false`
	)

inlineprivate

Definition at line 180 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian_old	(	std::vector< Real > &	jv,
		const std::vector< Real > &	v,
		const std::vector< Real > &	u,
		bool	adjoint = `false`
	)

inlineprivate

Definition at line 210 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

Referenced by EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1(), and EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian	(	std::vector< Real > &	jv,
		const std::vector< Real > &	vold,
		const std::vector< Real > &	uold,
		const std::vector< Real > &	vnew,
		const std::vector< Real >	unew,
		bool	adjoint = `false`
	)

inlineprivate

Definition at line 240 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, EqualityConstraint_BurgersControl< Real >::nu_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::u0_, and EqualityConstraint_BurgersControl< Real >::u1_.

Referenced by EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1(), and EqualityConstraint_BurgersControl< Real >::applyJacobian_1().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::apply_pde_hessian	(	std::vector< Real > &	hv,
		const std::vector< Real > &	wold,
		const std::vector< Real > &	vold,
		const std::vector< Real > &	wnew,
		const std::vector< Real > &	vnew
	)

inlineprivate

Definition at line 279 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, and EqualityConstraint_BurgersControl< Real >::nx_.

Referenced by EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::apply_control_jacobian	(	std::vector< Real > &	jv,
		const std::vector< Real > &	v,
		bool	adjoint = `false`
	)

inlineprivate

Definition at line 295 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dt_, EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

Referenced by EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2(), and EqualityConstraint_BurgersControl< Real >::applyJacobian_2().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::run_newton	(	std::vector< Real > &	u,
		const std::vector< Real > &	znew,
		const std::vector< Real > &	uold,
		const std::vector< Real > &	zold
	)

inlineprivate

Definition at line 323 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_norm(), EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::compute_residual(), EqualityConstraint_BurgersControl< Real >::linear_solve(), EqualityConstraint_BurgersControl< Real >::nx_, and EqualityConstraint_BurgersControl< Real >::update().

Referenced by EqualityConstraint_BurgersControl< Real >::solve().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::linear_solve	(	std::vector< Real > &	u,
		const std::vector< Real > &	dl,
		const std::vector< Real > &	d,
		const std::vector< Real > &	du,
		const std::vector< Real > &	r,
		const bool	transpose = `false`
	)

inlineprivate

Definition at line 370 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::dot(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 445 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_residual(), EqualityConstraint_BurgersControl< Real >::nt_, EqualityConstraint_BurgersControl< Real >::nx_, and EqualityConstraint_BurgersControl< Real >::u_init_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::solve	(	ROL::Vector< Real > &	c,
		ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Given $z$, solve $c(u,z)=0$ for $u$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in,out]	u	is the solution vector; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

The defualt implementation is Newton's method globalized with a backtracking line search.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 484 of file example_03.hpp.

References ROL::Vector< Real >::norm(), EqualityConstraint_BurgersControl< Real >::nt_, EqualityConstraint_BurgersControl< Real >::nx_, EqualityConstraint_BurgersControl< Real >::run_newton(), EqualityConstraint_BurgersControl< Real >::u_init_, and EqualityConstraint_BurgersControl< Real >::value().

Referenced by main().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 518 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::nt_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 545 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_control_jacobian(), EqualityConstraint_BurgersControl< Real >::nt_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 574 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian_old(), EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::linear_solve(), EqualityConstraint_BurgersControl< Real >::nt_, EqualityConstraint_BurgersControl< Real >::nx_, and EqualityConstraint_BurgersControl< Real >::update().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 610 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::nt_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 635 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_control_jacobian(), EqualityConstraint_BurgersControl< Real >::nt_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 665 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_pde_jacobian_old(), EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::linear_solve(), EqualityConstraint_BurgersControl< Real >::nt_, EqualityConstraint_BurgersControl< Real >::nx_, and EqualityConstraint_BurgersControl< Real >::update().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 699 of file example_03.hpp.

References EqualityConstraint_BurgersControl< Real >::apply_pde_hessian(), EqualityConstraint_BurgersControl< Real >::nt_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 724 of file example_03.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 728 of file example_03.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 732 of file example_03.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 880 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 893 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 906 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 919 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 932 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 945 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 958 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 971 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 991 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1010 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1029 of file example_04.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

Real EqualityConstraint_BurgersControl< Real >::compute_norm ( const std::vector< Real > & r )

inlineprivate

Definition at line 74 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dot().

template<class Real>

Real EqualityConstraint_BurgersControl< Real >::dot	(	const std::vector< Real > &	x,
		const std::vector< Real > &	y
	)

inlineprivate

Definition at line 78 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::update	(	std::vector< Real > &	u,
		const std::vector< Real > &	s,
		const Real	alpha = `1.0`
	)

inlineprivate

Definition at line 97 of file example_05.hpp.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::scale	(	std::vector< Real > &	u,
		const Real	alpha = `0.0`
	)

inlineprivate

Definition at line 103 of file example_05.hpp.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::compute_residual	(	std::vector< Real > &	r,
		const std::vector< Real > &	u,
		const std::vector< Real > &	z
	)

inlineprivate

Definition at line 109 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, ROL::EqualityConstraint< Real >::getParameter(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian	(	std::vector< Real > &	dl,
		std::vector< Real > &	d,
		std::vector< Real > &	du,
		const std::vector< Real > &	u
	)

inlineprivate

Definition at line 146 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, ROL::EqualityConstraint< Real >::getParameter(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::linear_solve	(	std::vector< Real > &	u,
		std::vector< Real > &	dl,
		std::vector< Real > &	d,
		std::vector< Real > &	du,
		const std::vector< Real > &	r,
		const bool	transpose = `false`
	)

inlineprivate

Definition at line 173 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 195 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_residual().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::solve	(	ROL::Vector< Real > &	c,
		ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Given $z$, solve $c(u,z)=0$ for $u$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in,out]	u	is the solution vector; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

The defualt implementation is Newton's method globalized with a backtracking line search.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 206 of file example_05.hpp.

References ROL::EqualityConstraint_SimOpt< Real >::solve().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 213 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, ROL::EqualityConstraint< Real >::getParameter(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 246 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 262 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::linear_solve(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 281 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, ROL::EqualityConstraint< Real >::getParameter(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 314 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::dx_, and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 343 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::compute_pde_jacobian(), EqualityConstraint_BurgersControl< Real >::linear_solve(), and EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 360 of file example_05.hpp.

References EqualityConstraint_BurgersControl< Real >::nx_.

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 384 of file example_05.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 388 of file example_05.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 392 of file example_05.hpp.

References ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 884 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 900 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 918 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 936 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 954 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 972 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 990 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1008 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1033 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1057 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1081 of file example_06.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 890 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 906 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 924 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 942 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 960 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 978 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 996 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1014 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1039 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1063 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1087 of file example_07.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::value	(	ROL::Vector< Real > &	c,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Evaluate the constraint operator $c:\mathcal{U}\times\mathcal{Z} \rightarrow \mathcal{C}$ at $(u,z)$.

Parameters

[out]	c	is the result of evaluating the constraint operator at $(u,z)$; a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{c} = c(u,z)$, where $\mathsf{c} \in \mathcal{C}$, $\mathsf{u} \in \mathcal{U}$, and $ $\mathsf{z} \in\mathcal{Z}$.

Implements ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 884 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_1	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_u(u,z) \in L(\mathcal{U}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; an simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_u(u,z)v$, where $v \in \mathcal{U}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 900 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyJacobian_2	(	ROL::Vector< Real > &	jv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the partial constraint Jacobian at $(u,z)$, $c_z(u,z) \in L(\mathcal{Z}, \mathcal{C})$, to the vector $v$.

Parameters

[out]	jv	is the result of applying the constraint Jacobian to v at $(u,z)$; a constraint-space vector
[in]	v	is an optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{jv} = c_z(u,z)v$, where $v \in \mathcal{Z}$, $\mathsf{jv} \in \mathcal{C}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 918 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseJacobian_1	(	ROL::Vector< Real > &	ijv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-1} \in L(\mathcal{C}, \mathcal{U})$, to the vector $v$.

Parameters

[out]	ijv	is the result of applying the inverse constraint Jacobian to v at $(u,z)$; a simulation-space vector
[in]	v	is a constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ijv} = c_u(u,z)^{-1}v$, where $v \in \mathcal{C}$, $\mathsf{ijv} \in \mathcal{U}$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 936 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_1	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^* \in L(\mathcal{C}^*, \mathcal{U}^*)$, to the vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at (u,z); a dual simulation-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_u(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 954 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointJacobian_2	(	ROL::Vector< Real > &	ajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the adjoint of the partial constraint Jacobian at $(u,z)$, $c_z(u,z)^* \in L(\mathcal{C}^*, \mathcal{Z}^*)$, to vector $v$. This is the primary interface.

Parameters

[out]	ajv	is the result of applying the adjoint of the constraint Jacobian to v at $(u,z)$; a dual optimization-space vector
[in]	v	is a dual constraint-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ajv} = c_z(u,z)^*v$, where $v \in \mathcal{C}^*$, $\mathsf{ajv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 972 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyInverseAdjointJacobian_1	(	ROL::Vector< Real > &	iajv,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the inverse of the adjoint of the partial constraint Jacobian at $(u,z)$, $c_u(u,z)^{-*} \in L(\mathcal{U}^*, \mathcal{C}^*)$, to the vector $v$.

Parameters

[out]	iajv	is the result of applying the inverse adjoint of the constraint Jacobian to v at (u,z); a dual constraint-space vector
[in]	v	is a dual simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{iajv} = c_u(u,z)^{-*}v$, where $v \in \mathcal{U}^*$, $\mathsf{iajv} \in \mathcal{C}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 990 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, and ROL::EqualityConstraint< Real >::getParameter().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_11	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1008 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_12	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{uz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint simulation-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a simulation-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{uz}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{U}$, and $\mathsf{ahwv} \in \mathcal{Z}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1033 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_21	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zu}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the simulation-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual simulation-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused

On return, $\mathsf{ahwv} = c_{zu}(u,z)(v,\cdot)^*w$, where $w \in \mathcal{C}^*$, $v \in \mathcal{Z}$, and $\mathsf{ahwv} \in \mathcal{U}^*$.

Reimplemented from ROL::EqualityConstraint_SimOpt< Real >.

Definition at line 1057 of file example_08.hpp.

References EqualityConstraint_BurgersControl< Real >::fem_, ROL::EqualityConstraint< Real >::getParameter(), EqualityConstraint_BurgersControl< Real >::useHessian_, and ROL::Vector< Real >::zero().

template<class Real>

void EqualityConstraint_BurgersControl< Real >::applyAdjointHessian_22	(	ROL::Vector< Real > &	ahwv,
		const ROL::Vector< Real > &	w,
		const ROL::Vector< Real > &	v,
		const ROL::Vector< Real > &	u,
		const ROL::Vector< Real > &	z,
		Real &	tol
	)

inlinevirtual

Apply the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in the direction $v$, according to $v\mapsto c_{zz}(u,z)(v,\cdot)^*w$.

Parameters

[out]	ahwv	is the result of applying the optimization-space derivative of the adjoint of the constraint optimization-space Jacobian at $(u,z)$ to the vector $w$ in direction $w$; a dual optimization-space vector
[in]	w	is the direction vector; a dual constraint-space vector
[in]	v	is a optimization-space vector
[in]	u	is the constraint argument; a simulation-space vector
[in]	z	is the constraint argument; an optimization-space vector
[in,out]	tol	is a tolerance for inexact evaluations; currently unused