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 <cstddef>
34 #include <memory>
35 
36 #include "Eigen/Dense"
37 #include "ceres/block_random_access_dense_matrix.h"
38 #include "ceres/block_sparse_matrix.h"
39 #include "ceres/casts.h"
40 #include "ceres/context_impl.h"
41 #include "ceres/internal/eigen.h"
42 #include "ceres/linear_least_squares_problems.h"
43 #include "ceres/linear_solver.h"
44 #include "ceres/schur_eliminator.h"
45 #include "ceres/triplet_sparse_matrix.h"
46 #include "ceres/types.h"
47 #include "glog/logging.h"
48 #include "gtest/gtest.h"
49 
50 namespace ceres {
51 namespace internal {
52 
53 using testing::AssertionResult;
54 
55 const double kEpsilon = 1e-14;
56 
57 class ImplicitSchurComplementTest : public ::testing::Test {
58  protected:
SetUp()59   void SetUp() final {
60     std::unique_ptr<LinearLeastSquaresProblem> problem(
61         CreateLinearLeastSquaresProblemFromId(2));
62 
63     CHECK(problem != nullptr);
64     A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
65     b_.reset(problem->b.release());
66     D_.reset(problem->D.release());
67 
68     num_cols_ = A_->num_cols();
69     num_rows_ = A_->num_rows();
70     num_eliminate_blocks_ = problem->num_eliminate_blocks;
71   }
72 
ReducedLinearSystemAndSolution(double * D,Matrix * lhs,Vector * rhs,Vector * solution)73   void ReducedLinearSystemAndSolution(double* D,
74                                       Matrix* lhs,
75                                       Vector* rhs,
76                                       Vector* solution) {
77     const CompressedRowBlockStructure* bs = A_->block_structure();
78     const int num_col_blocks = bs->cols.size();
79     std::vector<int> blocks(num_col_blocks - num_eliminate_blocks_, 0);
80     for (int i = num_eliminate_blocks_; i < num_col_blocks; ++i) {
81       blocks[i - num_eliminate_blocks_] = bs->cols[i].size;
82     }
83 
84     BlockRandomAccessDenseMatrix blhs(blocks);
85     const int num_schur_rows = blhs.num_rows();
86 
87     LinearSolver::Options options;
88     options.elimination_groups.push_back(num_eliminate_blocks_);
89     options.type = DENSE_SCHUR;
90     ContextImpl context;
91     options.context = &context;
92 
93     std::unique_ptr<SchurEliminatorBase> eliminator(
94         SchurEliminatorBase::Create(options));
95     CHECK(eliminator != nullptr);
96     const bool kFullRankETE = true;
97     eliminator->Init(num_eliminate_blocks_, kFullRankETE, bs);
98 
99     lhs->resize(num_schur_rows, num_schur_rows);
100     rhs->resize(num_schur_rows);
101 
102     eliminator->Eliminate(
103         BlockSparseMatrixData(*A_), b_.get(), D, &blhs, rhs->data());
104 
105     MatrixRef lhs_ref(blhs.mutable_values(), num_schur_rows, num_schur_rows);
106 
107     // lhs_ref is an upper triangular matrix. Construct a full version
108     // of lhs_ref in lhs by transposing lhs_ref, choosing the strictly
109     // lower triangular part of the matrix and adding it to lhs_ref.
110     *lhs = lhs_ref;
111     lhs->triangularView<Eigen::StrictlyLower>() =
112         lhs_ref.triangularView<Eigen::StrictlyUpper>().transpose();
113 
114     solution->resize(num_cols_);
115     solution->setZero();
116     VectorRef schur_solution(solution->data() + num_cols_ - num_schur_rows,
117                              num_schur_rows);
118     schur_solution = lhs->selfadjointView<Eigen::Upper>().llt().solve(*rhs);
119     eliminator->BackSubstitute(BlockSparseMatrixData(*A_),
120                                b_.get(),
121                                D,
122                                schur_solution.data(),
123                                solution->data());
124   }
125 
TestImplicitSchurComplement(double * D)126   AssertionResult TestImplicitSchurComplement(double* D) {
127     Matrix lhs;
128     Vector rhs;
129     Vector reference_solution;
130     ReducedLinearSystemAndSolution(D, &lhs, &rhs, &reference_solution);
131 
132     LinearSolver::Options options;
133     options.elimination_groups.push_back(num_eliminate_blocks_);
134     options.preconditioner_type = JACOBI;
135     ContextImpl context;
136     options.context = &context;
137     ImplicitSchurComplement isc(options);
138     isc.Init(*A_, D, b_.get());
139 
140     int num_sc_cols = lhs.cols();
141 
142     for (int i = 0; i < num_sc_cols; ++i) {
143       Vector x(num_sc_cols);
144       x.setZero();
145       x(i) = 1.0;
146 
147       Vector y(num_sc_cols);
148       y = lhs * x;
149 
150       Vector z(num_sc_cols);
151       isc.RightMultiply(x.data(), z.data());
152 
153       // The i^th column of the implicit schur complement is the same as
154       // the explicit schur complement.
155       if ((y - z).norm() > kEpsilon) {
156         return testing::AssertionFailure()
157                << "Explicit and Implicit SchurComplements differ in "
158                << "column " << i << ". explicit: " << y.transpose()
159                << " implicit: " << z.transpose();
160       }
161     }
162 
163     // Compare the rhs of the reduced linear system
164     if ((isc.rhs() - rhs).norm() > kEpsilon) {
165       return testing::AssertionFailure()
166              << "Explicit and Implicit SchurComplements differ in "
167              << "rhs. explicit: " << rhs.transpose()
168              << " implicit: " << isc.rhs().transpose();
169     }
170 
171     // Reference solution to the f_block.
172     const Vector reference_f_sol =
173         lhs.selfadjointView<Eigen::Upper>().llt().solve(rhs);
174 
175     // Backsubstituted solution from the implicit schur solver using the
176     // reference solution to the f_block.
177     Vector sol(num_cols_);
178     isc.BackSubstitute(reference_f_sol.data(), sol.data());
179     if ((sol - reference_solution).norm() > kEpsilon) {
180       return testing::AssertionFailure()
181              << "Explicit and Implicit SchurComplements solutions differ. "
182              << "explicit: " << reference_solution.transpose()
183              << " implicit: " << sol.transpose();
184     }
185 
186     return testing::AssertionSuccess();
187   }
188 
189   int num_rows_;
190   int num_cols_;
191   int num_eliminate_blocks_;
192 
193   std::unique_ptr<BlockSparseMatrix> A_;
194   std::unique_ptr<double[]> b_;
195   std::unique_ptr<double[]> D_;
196 };
197 
198 // Verify that the Schur Complement matrix implied by the
199 // ImplicitSchurComplement class matches the one explicitly computed
200 // by the SchurComplement solver.
201 //
202 // We do this with and without regularization to check that the
203 // support for the LM diagonal is correct.
TEST_F(ImplicitSchurComplementTest,SchurMatrixValuesTest)204 TEST_F(ImplicitSchurComplementTest, SchurMatrixValuesTest) {
205   EXPECT_TRUE(TestImplicitSchurComplement(NULL));
206   EXPECT_TRUE(TestImplicitSchurComplement(D_.get()));
207 }
208 
209 }  // namespace internal
210 }  // namespace ceres
211