1 // Ceres Solver - A fast non-linear least squares minimizer
2 // Copyright 2013 Google Inc. All rights reserved.
3 // http://code.google.com/p/ceres-solver/
4 //
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6 // modification, are permitted provided that the following conditions are met:
7 //
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16 //
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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_sparse_matrix.h"
37 #include "ceres/block_sparse_matrix.h"
38 #include "ceres/collections_port.h"
39 #include "ceres/detect_structure.h"
40 #include "ceres/internal/scoped_ptr.h"
41 #include "ceres/linear_solver.h"
42 #include "ceres/schur_eliminator.h"
43 #include "glog/logging.h"
44
45 namespace ceres {
46 namespace internal {
47
SchurJacobiPreconditioner(const CompressedRowBlockStructure & bs,const Preconditioner::Options & options)48 SchurJacobiPreconditioner::SchurJacobiPreconditioner(
49 const CompressedRowBlockStructure& bs,
50 const Preconditioner::Options& options)
51 : options_(options) {
52 CHECK_GT(options_.elimination_groups.size(), 1);
53 CHECK_GT(options_.elimination_groups[0], 0);
54 const int num_blocks = bs.cols.size() - options_.elimination_groups[0];
55 CHECK_GT(num_blocks, 0)
56 << "Jacobian should have atleast 1 f_block for "
57 << "SCHUR_JACOBI preconditioner.";
58
59 block_size_.resize(num_blocks);
60 set<pair<int, int> > block_pairs;
61
62 int num_block_diagonal_entries = 0;
63 for (int i = 0; i < num_blocks; ++i) {
64 block_size_[i] = bs.cols[i + options_.elimination_groups[0]].size;
65 block_pairs.insert(make_pair(i, i));
66 num_block_diagonal_entries += block_size_[i] * block_size_[i];
67 }
68
69 m_.reset(new BlockRandomAccessSparseMatrix(block_size_, block_pairs));
70 InitEliminator(bs);
71 }
72
~SchurJacobiPreconditioner()73 SchurJacobiPreconditioner::~SchurJacobiPreconditioner() {
74 }
75
76 // Initialize the SchurEliminator.
InitEliminator(const CompressedRowBlockStructure & bs)77 void SchurJacobiPreconditioner::InitEliminator(
78 const CompressedRowBlockStructure& bs) {
79 LinearSolver::Options eliminator_options;
80
81 eliminator_options.elimination_groups = options_.elimination_groups;
82 eliminator_options.num_threads = options_.num_threads;
83
84 DetectStructure(bs, options_.elimination_groups[0],
85 &eliminator_options.row_block_size,
86 &eliminator_options.e_block_size,
87 &eliminator_options.f_block_size);
88
89 eliminator_.reset(SchurEliminatorBase::Create(eliminator_options));
90 eliminator_->Init(options_.elimination_groups[0], &bs);
91 }
92
93 // Update the values of the preconditioner matrix and factorize it.
UpdateImpl(const BlockSparseMatrix & A,const double * D)94 bool SchurJacobiPreconditioner::UpdateImpl(const BlockSparseMatrix& A,
95 const double* D) {
96 const int num_rows = m_->num_rows();
97 CHECK_GT(num_rows, 0);
98
99 // We need a dummy rhs vector and a dummy b vector since the Schur
100 // eliminator combines the computation of the reduced camera matrix
101 // with the computation of the right hand side of that linear
102 // system.
103 //
104 // TODO(sameeragarwal): Perhaps its worth refactoring the
105 // SchurEliminator::Eliminate function to allow NULL for the rhs. As
106 // of now it does not seem to be worth the effort.
107 Vector rhs = Vector::Zero(m_->num_rows());
108 Vector b = Vector::Zero(A.num_rows());
109
110 // Compute a subset of the entries of the Schur complement.
111 eliminator_->Eliminate(&A, b.data(), D, m_.get(), rhs.data());
112 return true;
113 }
114
RightMultiply(const double * x,double * y) const115 void SchurJacobiPreconditioner::RightMultiply(const double* x,
116 double* y) const {
117 CHECK_NOTNULL(x);
118 CHECK_NOTNULL(y);
119
120 const double* lhs_values =
121 down_cast<BlockRandomAccessSparseMatrix*>(m_.get())->matrix()->values();
122
123 // This loop can be easily multi-threaded with OpenMP if need be.
124 for (int i = 0; i < block_size_.size(); ++i) {
125 const int block_size = block_size_[i];
126 ConstMatrixRef block(lhs_values, block_size, block_size);
127
128 VectorRef(y, block_size) =
129 block
130 .selfadjointView<Eigen::Upper>()
131 .llt()
132 .solve(ConstVectorRef(x, block_size));
133
134 x += block_size;
135 y += block_size;
136 lhs_values += block_size * block_size;
137 }
138 }
139
num_rows() const140 int SchurJacobiPreconditioner::num_rows() const {
141 return m_->num_rows();
142 }
143
144 } // namespace internal
145 } // namespace ceres
146