1// Ceres Solver - A fast non-linear least squares minimizer
2// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
3// http://code.google.com/p/ceres-solver/
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29// Author: sameeragarwal@google.com (Sameer Agarwal)
30
31#include "ceres/block_sparse_matrix.h"
32
33#include <string>
34#include "ceres/casts.h"
35#include "ceres/internal/eigen.h"
36#include "ceres/internal/scoped_ptr.h"
37#include "ceres/linear_least_squares_problems.h"
38#include "ceres/triplet_sparse_matrix.h"
39#include "glog/logging.h"
40#include "gtest/gtest.h"
41
42namespace ceres {
43namespace internal {
44
45class BlockSparseMatrixTest : public ::testing::Test {
46 protected :
47  virtual void SetUp() {
48    scoped_ptr<LinearLeastSquaresProblem> problem(
49        CreateLinearLeastSquaresProblemFromId(2));
50    CHECK_NOTNULL(problem.get());
51    A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
52
53    problem.reset(CreateLinearLeastSquaresProblemFromId(1));
54    CHECK_NOTNULL(problem.get());
55    B_.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
56
57    CHECK_EQ(A_->num_rows(), B_->num_rows());
58    CHECK_EQ(A_->num_cols(), B_->num_cols());
59    CHECK_EQ(A_->num_nonzeros(), B_->num_nonzeros());
60  }
61
62  scoped_ptr<BlockSparseMatrix> A_;
63  scoped_ptr<TripletSparseMatrix> B_;
64};
65
66TEST_F(BlockSparseMatrixTest, SetZeroTest) {
67  A_->SetZero();
68  EXPECT_EQ(13, A_->num_nonzeros());
69}
70
71TEST_F(BlockSparseMatrixTest, RightMultiplyTest) {
72  Vector y_a = Vector::Zero(A_->num_rows());
73  Vector y_b = Vector::Zero(A_->num_rows());
74  for (int i = 0; i < A_->num_cols(); ++i) {
75    Vector x = Vector::Zero(A_->num_cols());
76    x[i] = 1.0;
77    A_->RightMultiply(x.data(), y_a.data());
78    B_->RightMultiply(x.data(), y_b.data());
79    EXPECT_LT((y_a - y_b).norm(), 1e-12);
80  }
81}
82
83TEST_F(BlockSparseMatrixTest, LeftMultiplyTest) {
84  Vector y_a = Vector::Zero(A_->num_cols());
85  Vector y_b = Vector::Zero(A_->num_cols());
86  for (int i = 0; i < A_->num_rows(); ++i) {
87    Vector x = Vector::Zero(A_->num_rows());
88    x[i] = 1.0;
89    A_->LeftMultiply(x.data(), y_a.data());
90    B_->LeftMultiply(x.data(), y_b.data());
91    EXPECT_LT((y_a - y_b).norm(), 1e-12);
92  }
93}
94
95TEST_F(BlockSparseMatrixTest, SquaredColumnNormTest) {
96  Vector y_a = Vector::Zero(A_->num_cols());
97  Vector y_b = Vector::Zero(A_->num_cols());
98  A_->SquaredColumnNorm(y_a.data());
99  B_->SquaredColumnNorm(y_b.data());
100  EXPECT_LT((y_a - y_b).norm(), 1e-12);
101}
102
103TEST_F(BlockSparseMatrixTest, ToDenseMatrixTest) {
104  Matrix m_a;
105  Matrix m_b;
106  A_->ToDenseMatrix(&m_a);
107  B_->ToDenseMatrix(&m_b);
108  EXPECT_LT((m_a - m_b).norm(), 1e-12);
109}
110
111}  // namespace internal
112}  // namespace ceres
113