1// Ceres Solver - A fast non-linear least squares minimizer
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3// http://code.google.com/p/ceres-solver/
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29// Author: sameeragarwal@google.com (Sameer Agarwal)
30
31#include "ceres/schur_jacobi_preconditioner.h"
32
33#include <utility>
34#include <vector>
35#include "Eigen/Dense"
36#include "ceres/block_random_access_diagonal_matrix.h"
37#include "ceres/block_sparse_matrix.h"
38#include "ceres/collections_port.h"
39#include "ceres/internal/scoped_ptr.h"
40#include "ceres/linear_solver.h"
41#include "ceres/schur_eliminator.h"
42#include "glog/logging.h"
43
44namespace ceres {
45namespace internal {
46
47SchurJacobiPreconditioner::SchurJacobiPreconditioner(
48    const CompressedRowBlockStructure& bs,
49    const Preconditioner::Options& options)
50    : options_(options) {
51  CHECK_GT(options_.elimination_groups.size(), 1);
52  CHECK_GT(options_.elimination_groups[0], 0);
53  const int num_blocks = bs.cols.size() - options_.elimination_groups[0];
54  CHECK_GT(num_blocks, 0)
55      << "Jacobian should have atleast 1 f_block for "
56      << "SCHUR_JACOBI preconditioner.";
57
58  block_size_.resize(num_blocks);
59  for (int i = 0; i < num_blocks; ++i) {
60    block_size_[i] = bs.cols[i + options_.elimination_groups[0]].size;
61  }
62
63  m_.reset(new BlockRandomAccessDiagonalMatrix(block_size_));
64  InitEliminator(bs);
65}
66
67SchurJacobiPreconditioner::~SchurJacobiPreconditioner() {
68}
69
70// Initialize the SchurEliminator.
71void SchurJacobiPreconditioner::InitEliminator(
72    const CompressedRowBlockStructure& bs) {
73  LinearSolver::Options eliminator_options;
74  eliminator_options.elimination_groups = options_.elimination_groups;
75  eliminator_options.num_threads = options_.num_threads;
76  eliminator_options.e_block_size = options_.e_block_size;
77  eliminator_options.f_block_size = options_.f_block_size;
78  eliminator_options.row_block_size = options_.row_block_size;
79  eliminator_.reset(SchurEliminatorBase::Create(eliminator_options));
80  eliminator_->Init(eliminator_options.elimination_groups[0], &bs);
81}
82
83// Update the values of the preconditioner matrix and factorize it.
84bool SchurJacobiPreconditioner::UpdateImpl(const BlockSparseMatrix& A,
85                                           const double* D) {
86  const int num_rows = m_->num_rows();
87  CHECK_GT(num_rows, 0);
88
89  // We need a dummy rhs vector and a dummy b vector since the Schur
90  // eliminator combines the computation of the reduced camera matrix
91  // with the computation of the right hand side of that linear
92  // system.
93  //
94  // TODO(sameeragarwal): Perhaps its worth refactoring the
95  // SchurEliminator::Eliminate function to allow NULL for the rhs. As
96  // of now it does not seem to be worth the effort.
97  Vector rhs = Vector::Zero(m_->num_rows());
98  Vector b = Vector::Zero(A.num_rows());
99
100  // Compute a subset of the entries of the Schur complement.
101  eliminator_->Eliminate(&A, b.data(), D, m_.get(), rhs.data());
102  return true;
103}
104
105void SchurJacobiPreconditioner::RightMultiply(const double* x,
106                                              double* y) const {
107  CHECK_NOTNULL(x);
108  CHECK_NOTNULL(y);
109
110  const double* lhs_values =
111      down_cast<BlockRandomAccessDiagonalMatrix*>(m_.get())->matrix()->values();
112
113  // This loop can be easily multi-threaded with OpenMP if need be.
114  for (int i = 0; i < block_size_.size(); ++i) {
115    const int block_size = block_size_[i];
116    ConstMatrixRef block(lhs_values, block_size, block_size);
117
118    VectorRef(y, block_size) =
119        block
120        .selfadjointView<Eigen::Upper>()
121        .llt()
122        .solve(ConstVectorRef(x, block_size));
123
124    x += block_size;
125    y += block_size;
126    lhs_values += block_size * block_size;
127  }
128}
129
130int SchurJacobiPreconditioner::num_rows() const {
131  return m_->num_rows();
132}
133
134}  // namespace internal
135}  // namespace ceres
136