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SapModel caches the Hessian factorization.
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| Original file line number | Diff line number | Diff line change |
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| #include "drake/multibody/contact_solvers/sap/dense_supernodal_solver.h" | ||
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| #include <vector> | ||
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| namespace drake { | ||
| namespace multibody { | ||
| namespace contact_solvers { | ||
| namespace internal { | ||
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| DenseSuperNodalSolver::DenseSuperNodalSolver( | ||
| const std::vector<MatrixX<double>>* A, const BlockSparseMatrix<double>* J) | ||
| : A_(A), J_(J) { | ||
| DRAKE_THROW_UNLESS(A != nullptr); | ||
| DRAKE_THROW_UNLESS(J != nullptr); | ||
| const int nv = [A]() { | ||
| int size = 0; | ||
| for (const auto& Ai : *A) { | ||
| DRAKE_THROW_UNLESS(Ai.rows() == Ai.cols()); | ||
| size += Ai.rows(); | ||
| } | ||
| return size; | ||
| }(); | ||
| H_.resize(nv, nv); | ||
| } | ||
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| bool DenseSuperNodalSolver::DoSetWeightMatrix( | ||
| const std::vector<Eigen::MatrixXd>& G) { | ||
| const int nv = size(); | ||
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| // Make dense dynamics matrix. | ||
| MatrixX<double> Adense = MatrixX<double>::Zero(nv, nv); | ||
| int offset = 0; | ||
| for (const auto& Ac : *A_) { | ||
| const int nv_clique = Ac.rows(); | ||
| Adense.block(offset, offset, nv_clique, nv_clique) = Ac; | ||
| offset += nv_clique; | ||
| } | ||
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| // Make dense Jacobian matrix. | ||
| const MatrixX<double> Jdense = J_->MakeDenseMatrix(); | ||
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| // Make dense Hessian matrix G. | ||
| const int nk = Jdense.rows(); | ||
| MatrixX<double> Gdense = MatrixX<double>::Zero(nk, nk); | ||
| offset = 0; | ||
| for (const auto& Gi : G) { | ||
| const int ni = Gi.rows(); | ||
| if (offset + ni > nk) { | ||
| // Weight matrix G is incompatible with the Jacobian matrix J. | ||
| return false; | ||
| } | ||
| Gdense.block(offset, offset, ni, ni) = Gi; | ||
| offset += ni; | ||
| } | ||
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| H_ = Adense + Jdense.transpose() * Gdense * Jdense; | ||
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| return true; | ||
| } | ||
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| bool DenseSuperNodalSolver::DoFactor() { | ||
| Hldlt_.compute(H_); | ||
| return Hldlt_.info() == Eigen::Success; | ||
| } | ||
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| void DenseSuperNodalSolver::DoSolveInPlace(Eigen::VectorXd* b) const { | ||
| *b = Hldlt_.solve(*b); | ||
| } | ||
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| } // namespace internal | ||
| } // namespace contact_solvers | ||
| } // namespace multibody | ||
| } // namespace drake |
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| #pragma once | ||
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| #include <vector> | ||
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| #include "drake/multibody/contact_solvers/supernodal_solver.h" | ||
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| namespace drake { | ||
| namespace multibody { | ||
| namespace contact_solvers { | ||
| namespace internal { | ||
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| // A class that implements the SuperNodalSolver interface using dense algebra. | ||
| // As with every other SuperNodalSolver, this class implements a Cholesky | ||
| // factorization of a Hessian matrix H of the form H = A + Jᵀ⋅G⋅J, where A is | ||
| // referred to as the dynamics matrix and J is the Jacobian matrix. | ||
| class DenseSuperNodalSolver final : public SuperNodalSolver { | ||
| public: | ||
| DRAKE_NO_COPY_NO_MOVE_NO_ASSIGN(DenseSuperNodalSolver) | ||
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| // Constructs a dense solver for dynamics matrix A and Jacobian matrix J. | ||
| // This class holds references to matrices A and J, and therefore they must | ||
| // outlive this object. | ||
| // @throws std::runtime_error if A or J is nullptr. | ||
| // @throws std::runtime_error if a block in A is not square. | ||
| // @pre each block in A is SPD. | ||
| // @pre The number of columns of J equals the size of A. | ||
| // @note The sizes in J are not checked here, but during SetWeightMatrix(). | ||
| DenseSuperNodalSolver(const std::vector<MatrixX<double>>* A, | ||
| const BlockSparseMatrix<double>* J); | ||
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| // @returns the size of the system. | ||
| int size() const { return H_.rows(); } | ||
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| private: | ||
| // Implementations of SuperNodalSolver NVIs. | ||
| bool DoSetWeightMatrix( | ||
| const std::vector<Eigen::MatrixXd>& block_diagonal_G) final; | ||
| Eigen::MatrixXd DoMakeFullMatrix() const final { return H_; } | ||
| bool DoFactor() final; | ||
| void DoSolveInPlace(Eigen::VectorXd* b) const final; | ||
| int DoGetSize() const final { return size(); } | ||
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| const std::vector<MatrixX<double>>* A_{nullptr}; | ||
| const BlockSparseMatrix<double>* J_{nullptr}; | ||
| // The support for dense algebra is mostly for testing purposes, even | ||
| // though the computation of the dense H (and in particular of the Jᵀ⋅G⋅J | ||
| // term) is very costly. Therefore below we decided to trade off speed for | ||
| // stability when choosing to use an LDLT decomposition instead of a slightly | ||
| // faster, though less stable, LLT decomposition. | ||
| MatrixX<double> H_; | ||
| // N.B. This instantiates an in-place LDLT solver that uses the memory in H_. | ||
| Eigen::LDLT<MatrixX<double>> Hldlt_{H_}; | ||
| }; | ||
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| } // namespace internal | ||
| } // namespace contact_solvers | ||
| } // namespace multibody | ||
| } // namespace drake |
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