1 // Ceres Solver - A fast non-linear least squares minimizer
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29 // Author: sameeragarwal@google.com (Sameer Agarwal)
30 
31 #include "ceres/implicit_schur_complement.h"
32 
33 #include "Eigen/Dense"
34 #include "ceres/block_sparse_matrix.h"
35 #include "ceres/block_structure.h"
36 #include "ceres/internal/eigen.h"
37 #include "ceres/internal/scoped_ptr.h"
38 #include "ceres/linear_solver.h"
39 #include "ceres/types.h"
40 #include "glog/logging.h"
41 
42 namespace ceres {
43 namespace internal {
44 
ImplicitSchurComplement(const LinearSolver::Options & options)45 ImplicitSchurComplement::ImplicitSchurComplement(
46     const LinearSolver::Options& options)
47     : options_(options),
48       D_(NULL),
49       b_(NULL) {
50 }
51 
~ImplicitSchurComplement()52 ImplicitSchurComplement::~ImplicitSchurComplement() {
53 }
54 
Init(const BlockSparseMatrix & A,const double * D,const double * b)55 void ImplicitSchurComplement::Init(const BlockSparseMatrix& A,
56                                    const double* D,
57                                    const double* b) {
58   // Since initialization is reasonably heavy, perhaps we can save on
59   // constructing a new object everytime.
60   if (A_ == NULL) {
61     A_.reset(PartitionedMatrixViewBase::Create(options_, A));
62   }
63 
64   D_ = D;
65   b_ = b;
66 
67   // Initialize temporary storage and compute the block diagonals of
68   // E'E and F'E.
69   if (block_diagonal_EtE_inverse_ == NULL) {
70     block_diagonal_EtE_inverse_.reset(A_->CreateBlockDiagonalEtE());
71     if (options_.preconditioner_type == JACOBI) {
72       block_diagonal_FtF_inverse_.reset(A_->CreateBlockDiagonalFtF());
73     }
74     rhs_.resize(A_->num_cols_f());
75     rhs_.setZero();
76     tmp_rows_.resize(A_->num_rows());
77     tmp_e_cols_.resize(A_->num_cols_e());
78     tmp_e_cols_2_.resize(A_->num_cols_e());
79     tmp_f_cols_.resize(A_->num_cols_f());
80   } else {
81     A_->UpdateBlockDiagonalEtE(block_diagonal_EtE_inverse_.get());
82     if (options_.preconditioner_type == JACOBI) {
83       A_->UpdateBlockDiagonalFtF(block_diagonal_FtF_inverse_.get());
84     }
85   }
86 
87   // The block diagonals of the augmented linear system contain
88   // contributions from the diagonal D if it is non-null. Add that to
89   // the block diagonals and invert them.
90   AddDiagonalAndInvert(D_, block_diagonal_EtE_inverse_.get());
91   if (options_.preconditioner_type == JACOBI) {
92     AddDiagonalAndInvert((D_ ==  NULL) ? NULL : D_ + A_->num_cols_e(),
93                          block_diagonal_FtF_inverse_.get());
94   }
95 
96   // Compute the RHS of the Schur complement system.
97   UpdateRhs();
98 }
99 
100 // Evaluate the product
101 //
102 //   Sx = [F'F - F'E (E'E)^-1 E'F]x
103 //
104 // By breaking it down into individual matrix vector products
105 // involving the matrices E and F. This is implemented using a
106 // PartitionedMatrixView of the input matrix A.
RightMultiply(const double * x,double * y) const107 void ImplicitSchurComplement::RightMultiply(const double* x, double* y) const {
108   // y1 = F x
109   tmp_rows_.setZero();
110   A_->RightMultiplyF(x, tmp_rows_.data());
111 
112   // y2 = E' y1
113   tmp_e_cols_.setZero();
114   A_->LeftMultiplyE(tmp_rows_.data(), tmp_e_cols_.data());
115 
116   // y3 = -(E'E)^-1 y2
117   tmp_e_cols_2_.setZero();
118   block_diagonal_EtE_inverse_->RightMultiply(tmp_e_cols_.data(),
119                                              tmp_e_cols_2_.data());
120   tmp_e_cols_2_ *= -1.0;
121 
122   // y1 = y1 + E y3
123   A_->RightMultiplyE(tmp_e_cols_2_.data(), tmp_rows_.data());
124 
125   // y5 = D * x
126   if (D_ != NULL) {
127     ConstVectorRef Dref(D_ + A_->num_cols_e(), num_cols());
128     VectorRef(y, num_cols()) =
129         (Dref.array().square() *
130          ConstVectorRef(x, num_cols()).array()).matrix();
131   } else {
132     VectorRef(y, num_cols()).setZero();
133   }
134 
135   // y = y5 + F' y1
136   A_->LeftMultiplyF(tmp_rows_.data(), y);
137 }
138 
139 // Given a block diagonal matrix and an optional array of diagonal
140 // entries D, add them to the diagonal of the matrix and compute the
141 // inverse of each diagonal block.
AddDiagonalAndInvert(const double * D,BlockSparseMatrix * block_diagonal)142 void ImplicitSchurComplement::AddDiagonalAndInvert(
143     const double* D,
144     BlockSparseMatrix* block_diagonal) {
145   const CompressedRowBlockStructure* block_diagonal_structure =
146       block_diagonal->block_structure();
147   for (int r = 0; r < block_diagonal_structure->rows.size(); ++r) {
148     const int row_block_pos = block_diagonal_structure->rows[r].block.position;
149     const int row_block_size = block_diagonal_structure->rows[r].block.size;
150     const Cell& cell = block_diagonal_structure->rows[r].cells[0];
151     MatrixRef m(block_diagonal->mutable_values() + cell.position,
152                 row_block_size, row_block_size);
153 
154     if (D != NULL) {
155       ConstVectorRef d(D + row_block_pos, row_block_size);
156       m += d.array().square().matrix().asDiagonal();
157     }
158 
159     m = m
160         .selfadjointView<Eigen::Upper>()
161         .llt()
162         .solve(Matrix::Identity(row_block_size, row_block_size));
163   }
164 }
165 
166 // Similar to RightMultiply, use the block structure of the matrix A
167 // to compute y = (E'E)^-1 (E'b - E'F x).
BackSubstitute(const double * x,double * y)168 void ImplicitSchurComplement::BackSubstitute(const double* x, double* y) {
169   const int num_cols_e = A_->num_cols_e();
170   const int num_cols_f = A_->num_cols_f();
171   const int num_cols =  A_->num_cols();
172   const int num_rows = A_->num_rows();
173 
174   // y1 = F x
175   tmp_rows_.setZero();
176   A_->RightMultiplyF(x, tmp_rows_.data());
177 
178   // y2 = b - y1
179   tmp_rows_ = ConstVectorRef(b_, num_rows) - tmp_rows_;
180 
181   // y3 = E' y2
182   tmp_e_cols_.setZero();
183   A_->LeftMultiplyE(tmp_rows_.data(), tmp_e_cols_.data());
184 
185   // y = (E'E)^-1 y3
186   VectorRef(y, num_cols).setZero();
187   block_diagonal_EtE_inverse_->RightMultiply(tmp_e_cols_.data(), y);
188 
189   // The full solution vector y has two blocks. The first block of
190   // variables corresponds to the eliminated variables, which we just
191   // computed via back substitution. The second block of variables
192   // corresponds to the Schur complement system, so we just copy those
193   // values from the solution to the Schur complement.
194   VectorRef(y + num_cols_e, num_cols_f) =  ConstVectorRef(x, num_cols_f);
195 }
196 
197 // Compute the RHS of the Schur complement system.
198 //
199 // rhs = F'b - F'E (E'E)^-1 E'b
200 //
201 // Like BackSubstitute, we use the block structure of A to implement
202 // this using a series of matrix vector products.
UpdateRhs()203 void ImplicitSchurComplement::UpdateRhs() {
204   // y1 = E'b
205   tmp_e_cols_.setZero();
206   A_->LeftMultiplyE(b_, tmp_e_cols_.data());
207 
208   // y2 = (E'E)^-1 y1
209   Vector y2 = Vector::Zero(A_->num_cols_e());
210   block_diagonal_EtE_inverse_->RightMultiply(tmp_e_cols_.data(), y2.data());
211 
212   // y3 = E y2
213   tmp_rows_.setZero();
214   A_->RightMultiplyE(y2.data(), tmp_rows_.data());
215 
216   // y3 = b - y3
217   tmp_rows_ = ConstVectorRef(b_, A_->num_rows()) - tmp_rows_;
218 
219   // rhs = F' y3
220   rhs_.setZero();
221   A_->LeftMultiplyF(tmp_rows_.data(), rhs_.data());
222 }
223 
224 }  // namespace internal
225 }  // namespace ceres
226