1// Ceres Solver - A fast non-linear least squares minimizer
2// Copyright 2010, 2011, 2012, 2013 Google Inc. All rights reserved.
3// http://code.google.com/p/ceres-solver/
4//
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28//
29// Author: keir@google.com (Keir Mierle)
30//
31// TODO(keir): Implement a generic "compare sparse matrix implementations" test
32// suite that can compare all the implementations. Then this file would shrink
33// in size.
34
35#include "ceres/dense_sparse_matrix.h"
36
37#include "ceres/casts.h"
38#include "ceres/linear_least_squares_problems.h"
39#include "ceres/triplet_sparse_matrix.h"
40#include "ceres/internal/eigen.h"
41#include "ceres/internal/scoped_ptr.h"
42#include "glog/logging.h"
43#include "gtest/gtest.h"
44
45namespace ceres {
46namespace internal {
47
48void CompareMatrices(const SparseMatrix* a, const SparseMatrix* b) {
49  EXPECT_EQ(a->num_rows(), b->num_rows());
50  EXPECT_EQ(a->num_cols(), b->num_cols());
51
52  int num_rows = a->num_rows();
53  int num_cols = a->num_cols();
54
55  for (int i = 0; i < num_cols; ++i) {
56    Vector x = Vector::Zero(num_cols);
57    x(i) = 1.0;
58
59    Vector y_a = Vector::Zero(num_rows);
60    Vector y_b = Vector::Zero(num_rows);
61
62    a->RightMultiply(x.data(), y_a.data());
63    b->RightMultiply(x.data(), y_b.data());
64
65    EXPECT_EQ((y_a - y_b).norm(), 0);
66  }
67}
68
69class DenseSparseMatrixTest : public ::testing::Test {
70 protected :
71  virtual void SetUp() {
72    scoped_ptr<LinearLeastSquaresProblem> problem(
73        CreateLinearLeastSquaresProblemFromId(1));
74
75    CHECK_NOTNULL(problem.get());
76
77    tsm.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
78    dsm.reset(new DenseSparseMatrix(*tsm));
79
80    num_rows = tsm->num_rows();
81    num_cols = tsm->num_cols();
82  }
83
84  int num_rows;
85  int num_cols;
86
87  scoped_ptr<TripletSparseMatrix> tsm;
88  scoped_ptr<DenseSparseMatrix> dsm;
89};
90
91TEST_F(DenseSparseMatrixTest, RightMultiply) {
92  CompareMatrices(tsm.get(), dsm.get());
93
94  // Try with a not entirely zero vector to verify column interactions, which
95  // could be masked by a subtle bug when using the elementary vectors.
96  Vector a(num_cols);
97  for (int i = 0; i < num_cols; i++) {
98    a(i) = i;
99  }
100  Vector b1 = Vector::Zero(num_rows);
101  Vector b2 = Vector::Zero(num_rows);
102
103  tsm->RightMultiply(a.data(), b1.data());
104  dsm->RightMultiply(a.data(), b2.data());
105
106  EXPECT_EQ((b1 - b2).norm(), 0);
107}
108
109TEST_F(DenseSparseMatrixTest, LeftMultiply) {
110  for (int i = 0; i < num_rows; ++i) {
111    Vector a = Vector::Zero(num_rows);
112    a(i) = 1.0;
113
114    Vector b1 = Vector::Zero(num_cols);
115    Vector b2 = Vector::Zero(num_cols);
116
117    tsm->LeftMultiply(a.data(), b1.data());
118    dsm->LeftMultiply(a.data(), b2.data());
119
120    EXPECT_EQ((b1 - b2).norm(), 0);
121  }
122
123  // Try with a not entirely zero vector to verify column interactions, which
124  // could be masked by a subtle bug when using the elementary vectors.
125  Vector a(num_rows);
126  for (int i = 0; i < num_rows; i++) {
127    a(i) = i;
128  }
129  Vector b1 = Vector::Zero(num_cols);
130  Vector b2 = Vector::Zero(num_cols);
131
132  tsm->LeftMultiply(a.data(), b1.data());
133  dsm->LeftMultiply(a.data(), b2.data());
134
135  EXPECT_EQ((b1 - b2).norm(), 0);
136}
137
138TEST_F(DenseSparseMatrixTest, ColumnNorm) {
139  Vector b1 = Vector::Zero(num_cols);
140  Vector b2 = Vector::Zero(num_cols);
141
142  tsm->SquaredColumnNorm(b1.data());
143  dsm->SquaredColumnNorm(b2.data());
144
145  EXPECT_EQ((b1 - b2).norm(), 0);
146}
147
148TEST_F(DenseSparseMatrixTest, Scale) {
149  Vector scale(num_cols);
150  for (int i = 0; i < num_cols; ++i) {
151    scale(i) = i + 1;
152  }
153  tsm->ScaleColumns(scale.data());
154  dsm->ScaleColumns(scale.data());
155  CompareMatrices(tsm.get(), dsm.get());
156}
157
158TEST_F(DenseSparseMatrixTest, ToDenseMatrix) {
159  Matrix tsm_dense;
160  Matrix dsm_dense;
161
162  tsm->ToDenseMatrix(&tsm_dense);
163  dsm->ToDenseMatrix(&dsm_dense);
164
165  EXPECT_EQ((tsm_dense - dsm_dense).norm(), 0.0);
166}
167
168}  // namespace internal
169}  // namespace ceres
170