Maps one friction coefficient to the whole state. More...

#include <FrictionVariableToSimulation.hpp>

Inheritance diagram for polyfem::solver::FrictionVariableToSimulation:

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Public Types
using	StatePtrs = std::vector< std::shared_ptr< legacy::State > >

using	DiffCachePtrs = std::vector< std::shared_ptr< DiffCache > >

Public Member Functions
	FrictionVariableToSimulation (StatePtrs states, DiffCachePtrs diff_caches, CompositeParametrization parametrizations)
	Construct FrictionVariableToSimulation.

std::string	name () const override

ParameterType	parameter_type () const override

bool	affect_state (const legacy::State &target) const override
	Return true if current var2sim maps to target state.

void	update (const Eigen::VectorXd &x) override
	Update forward simulation states from optimization variables.

void	update_state_variables (const Eigen::VectorXd &x, Eigen::VectorXd &state_variables) const override
	Update state variables from optimization variables.

Eigen::VectorXd	compute_adjoint_term (const Eigen::VectorXd &x) const override
	Compute adjoint contribution of objective gradient.

int	inverse_dof () const override
	Compute optimization variables dof.

Eigen::VectorXd	inverse_eval () const override
	Compute optimization variables from forward simulation legacy::State.

Eigen::VectorXd	apply_parametrization_jacobian (const Eigen::VectorXd &term, const Eigen::VectorXd &x) const override
	Apply parametrization jacobian to compute the gradient w.r.t.

Public Member Functions inherited from polyfem::solver::VariableToSimulation
virtual	~VariableToSimulation ()=default

Private Member Functions
int	para_out_dof () const

Private Attributes
StatePtrs	states_

DiffCachePtrs	diff_caches_

CompositeParametrization	parametrization_

Detailed Description

Maps one friction coefficient to the whole state.

Definition at line 14 of file FrictionVariableToSimulation.hpp.

Member Typedef Documentation

◆ DiffCachePtrs

using polyfem::solver::FrictionVariableToSimulation::DiffCachePtrs = std::vector<std::shared_ptr<DiffCache> >

Definition at line 18 of file FrictionVariableToSimulation.hpp.

◆ StatePtrs

using polyfem::solver::FrictionVariableToSimulation::StatePtrs = std::vector<std::shared_ptr<legacy::State> >

Definition at line 17 of file FrictionVariableToSimulation.hpp.

Constructor & Destructor Documentation

◆ FrictionVariableToSimulation()

polyfem::solver::FrictionVariableToSimulation::FrictionVariableToSimulation	(	StatePtrs	states,
		DiffCachePtrs	diff_caches,
		CompositeParametrization	parametrizations
	)

Construct FrictionVariableToSimulation.

Parameters

[in]	states	Shared ptr to all forward sim states.
[in]	diff_caches	Shared ptr to all diff caches.
[in]	parametrizations	Parametrizations.

Exceptions

std::runtime_error Throw if input is invalid.

Definition at line 16 of file FrictionVariableToSimulation.cpp.

References diff_caches_, polyfem::log_and_throw_adjoint_error(), and states_.

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Member Function Documentation

◆ affect_state()

bool polyfem::solver::FrictionVariableToSimulation::affect_state ( const legacy::State & target ) const

overridevirtual

Return true if current var2sim maps to target state.

Implements polyfem::solver::VariableToSimulation.

Definition at line 45 of file FrictionVariableToSimulation.cpp.

References states_.

◆ apply_parametrization_jacobian()

Eigen::VectorXd polyfem::solver::FrictionVariableToSimulation::apply_parametrization_jacobian	(	const Eigen::VectorXd &	term,
		const Eigen::VectorXd &	x
	)		const

overridevirtual

Apply parametrization jacobian to compute the gradient w.r.t.

to optimization variables.

Parameters

term	Gradient w.r.t. to full inherent dof (Ex. all vertices for shape var2sim)
x	Optimization variables.

Implements polyfem::solver::VariableToSimulation.

Definition at line 113 of file FrictionVariableToSimulation.cpp.

References polyfem::log_and_throw_adjoint_error(), and name().

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◆ compute_adjoint_term()

Eigen::VectorXd polyfem::solver::FrictionVariableToSimulation::compute_adjoint_term ( const Eigen::VectorXd & x ) const

overridevirtual

Compute adjoint contribution of objective gradient.

See arXiv:2205.13643.

Let objective function be J and optimization variable be x. This method computes all adjoint related terms in dJ/dx. For static case (E.q. 11), it's the second term. For dynamic case (E.q. 15), it's everything except ∂qJ.

Parameters

x[in] Optimization variables.