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/partitioned_matrix_view.h"
32
33#include <vector>
34#include "ceres/block_structure.h"
35#include "ceres/casts.h"
36#include "ceres/internal/eigen.h"
37#include "ceres/internal/scoped_ptr.h"
38#include "ceres/linear_least_squares_problems.h"
39#include "ceres/random.h"
40#include "ceres/sparse_matrix.h"
41#include "glog/logging.h"
42#include "gtest/gtest.h"
43
44namespace ceres {
45namespace internal {
46
47const double kEpsilon = 1e-14;
48
49class PartitionedMatrixViewTest : public ::testing::Test {
50 protected :
51  virtual void SetUp() {
52    srand(5);
53    scoped_ptr<LinearLeastSquaresProblem> problem(
54        CreateLinearLeastSquaresProblemFromId(2));
55    CHECK_NOTNULL(problem.get());
56    A_.reset(problem->A.release());
57
58    num_cols_ = A_->num_cols();
59    num_rows_ = A_->num_rows();
60    num_eliminate_blocks_ = problem->num_eliminate_blocks;
61    LinearSolver::Options options;
62    options.elimination_groups.push_back(num_eliminate_blocks_);
63    pmv_.reset(PartitionedMatrixViewBase::Create(
64                   options,
65                   *down_cast<BlockSparseMatrix*>(A_.get())));
66  }
67
68  int num_rows_;
69  int num_cols_;
70  int num_eliminate_blocks_;
71  scoped_ptr<SparseMatrix> A_;
72  scoped_ptr<PartitionedMatrixViewBase> pmv_;
73};
74
75TEST_F(PartitionedMatrixViewTest, DimensionsTest) {
76  EXPECT_EQ(pmv_->num_col_blocks_e(), num_eliminate_blocks_);
77  EXPECT_EQ(pmv_->num_col_blocks_f(), num_cols_ - num_eliminate_blocks_);
78  EXPECT_EQ(pmv_->num_cols_e(), num_eliminate_blocks_);
79  EXPECT_EQ(pmv_->num_cols_f(), num_cols_ - num_eliminate_blocks_);
80  EXPECT_EQ(pmv_->num_cols(), A_->num_cols());
81  EXPECT_EQ(pmv_->num_rows(), A_->num_rows());
82}
83
84TEST_F(PartitionedMatrixViewTest, RightMultiplyE) {
85  Vector x1(pmv_->num_cols_e());
86  Vector x2(pmv_->num_cols());
87  x2.setZero();
88
89  for (int i = 0; i < pmv_->num_cols_e(); ++i) {
90    x1(i) = x2(i) = RandDouble();
91  }
92
93  Vector y1 = Vector::Zero(pmv_->num_rows());
94  pmv_->RightMultiplyE(x1.data(), y1.data());
95
96  Vector y2 = Vector::Zero(pmv_->num_rows());
97  A_->RightMultiply(x2.data(), y2.data());
98
99  for (int i = 0; i < pmv_->num_rows(); ++i) {
100    EXPECT_NEAR(y1(i), y2(i), kEpsilon);
101  }
102}
103
104TEST_F(PartitionedMatrixViewTest, RightMultiplyF) {
105  Vector x1(pmv_->num_cols_f());
106  Vector x2 = Vector::Zero(pmv_->num_cols());
107
108  for (int i = 0; i < pmv_->num_cols_f(); ++i) {
109    x1(i) = RandDouble();
110    x2(i + pmv_->num_cols_e()) = x1(i);
111  }
112
113  Vector y1 = Vector::Zero(pmv_->num_rows());
114  pmv_->RightMultiplyF(x1.data(), y1.data());
115
116  Vector y2 = Vector::Zero(pmv_->num_rows());
117  A_->RightMultiply(x2.data(), y2.data());
118
119  for (int i = 0; i < pmv_->num_rows(); ++i) {
120    EXPECT_NEAR(y1(i), y2(i), kEpsilon);
121  }
122}
123
124TEST_F(PartitionedMatrixViewTest, LeftMultiply) {
125  Vector x = Vector::Zero(pmv_->num_rows());
126  for (int i = 0; i < pmv_->num_rows(); ++i) {
127    x(i) = RandDouble();
128  }
129
130  Vector y = Vector::Zero(pmv_->num_cols());
131  Vector y1 = Vector::Zero(pmv_->num_cols_e());
132  Vector y2 = Vector::Zero(pmv_->num_cols_f());
133
134  A_->LeftMultiply(x.data(), y.data());
135  pmv_->LeftMultiplyE(x.data(), y1.data());
136  pmv_->LeftMultiplyF(x.data(), y2.data());
137
138  for (int i = 0; i < pmv_->num_cols(); ++i) {
139    EXPECT_NEAR(y(i),
140                (i < pmv_->num_cols_e()) ? y1(i) : y2(i - pmv_->num_cols_e()),
141                kEpsilon);
142  }
143}
144
145TEST_F(PartitionedMatrixViewTest, BlockDiagonalEtE) {
146  scoped_ptr<BlockSparseMatrix>
147      block_diagonal_ee(pmv_->CreateBlockDiagonalEtE());
148  const CompressedRowBlockStructure* bs  = block_diagonal_ee->block_structure();
149
150  EXPECT_EQ(block_diagonal_ee->num_rows(), 2);
151  EXPECT_EQ(block_diagonal_ee->num_cols(), 2);
152  EXPECT_EQ(bs->cols.size(), 2);
153  EXPECT_EQ(bs->rows.size(), 2);
154
155  EXPECT_NEAR(block_diagonal_ee->values()[0], 10.0, kEpsilon);
156  EXPECT_NEAR(block_diagonal_ee->values()[1], 155.0, kEpsilon);
157}
158
159TEST_F(PartitionedMatrixViewTest, BlockDiagonalFtF) {
160  scoped_ptr<BlockSparseMatrix>
161      block_diagonal_ff(pmv_->CreateBlockDiagonalFtF());
162  const CompressedRowBlockStructure* bs  = block_diagonal_ff->block_structure();
163
164  EXPECT_EQ(block_diagonal_ff->num_rows(), 3);
165  EXPECT_EQ(block_diagonal_ff->num_cols(), 3);
166  EXPECT_EQ(bs->cols.size(), 3);
167  EXPECT_EQ(bs->rows.size(), 3);
168  EXPECT_NEAR(block_diagonal_ff->values()[0], 70.0, kEpsilon);
169  EXPECT_NEAR(block_diagonal_ff->values()[1], 17.0, kEpsilon);
170  EXPECT_NEAR(block_diagonal_ff->values()[2], 37.0, kEpsilon);
171}
172
173}  // namespace internal
174}  // namespace ceres
175