Carlos Hernandez | 79397c2 | 2014-08-07 17:51:38 -0700 | [diff] [blame] | 1 | // Ceres Solver - A fast non-linear least squares minimizer |
| 2 | // Copyright 2014 Google Inc. All rights reserved. |
| 3 | // http://code.google.com/p/ceres-solver/ |
| 4 | // |
| 5 | // Redistribution and use in source and binary forms, with or without |
| 6 | // modification, are permitted provided that the following conditions are met: |
| 7 | // |
| 8 | // * Redistributions of source code must retain the above copyright notice, |
| 9 | // this list of conditions and the following disclaimer. |
| 10 | // * Redistributions in binary form must reproduce the above copyright notice, |
| 11 | // this list of conditions and the following disclaimer in the documentation |
| 12 | // and/or other materials provided with the distribution. |
| 13 | // * Neither the name of Google Inc. nor the names of its contributors may be |
| 14 | // used to endorse or promote products derived from this software without |
| 15 | // specific prior written permission. |
| 16 | // |
| 17 | // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| 18 | // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| 19 | // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| 20 | // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| 21 | // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| 22 | // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| 23 | // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| 24 | // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| 25 | // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| 26 | // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| 27 | // POSSIBILITY OF SUCH DAMAGE. |
| 28 | // |
| 29 | // Author: richie.stebbing@gmail.com (Richard Stebbing) |
| 30 | |
| 31 | #include "ceres/dynamic_compressed_row_sparse_matrix.h" |
| 32 | |
| 33 | #include "ceres/casts.h" |
| 34 | #include "ceres/compressed_row_sparse_matrix.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/triplet_sparse_matrix.h" |
| 40 | #include "gtest/gtest.h" |
| 41 | |
| 42 | namespace ceres { |
| 43 | namespace internal { |
| 44 | |
| 45 | class DynamicCompressedRowSparseMatrixTest : public ::testing::Test { |
| 46 | protected: |
| 47 | virtual void SetUp() { |
| 48 | num_rows = 7; |
| 49 | num_cols = 4; |
| 50 | |
| 51 | // The number of additional elements reserved when `Finalize` is called |
| 52 | // should have no effect on the number of rows, columns or nonzeros. |
| 53 | // Set this to some nonzero value to be sure. |
| 54 | num_additional_elements = 13; |
| 55 | |
| 56 | expected_num_nonzeros = num_rows * num_cols - min(num_rows, num_cols); |
| 57 | |
| 58 | InitialiseDenseReference(); |
| 59 | InitialiseSparseMatrixReferences(); |
| 60 | |
| 61 | dcrsm.reset(new DynamicCompressedRowSparseMatrix(num_rows, |
| 62 | num_cols, |
| 63 | 0)); |
| 64 | } |
| 65 | |
| 66 | void Finalize() { |
| 67 | dcrsm->Finalize(num_additional_elements); |
| 68 | } |
| 69 | |
| 70 | void InitialiseDenseReference() { |
| 71 | dense.resize(num_rows, num_cols); |
| 72 | dense.setZero(); |
| 73 | int num_nonzeros = 0; |
| 74 | for (int i = 0; i < (num_rows * num_cols); ++i) { |
| 75 | const int r = i / num_cols, c = i % num_cols; |
| 76 | if (r != c) { |
| 77 | dense(r, c) = i + 1; |
| 78 | ++num_nonzeros; |
| 79 | } |
| 80 | } |
| 81 | ASSERT_EQ(num_nonzeros, expected_num_nonzeros); |
| 82 | } |
| 83 | |
| 84 | void InitialiseSparseMatrixReferences() { |
| 85 | std::vector<int> rows, cols; |
| 86 | std::vector<double> values; |
| 87 | for (int i = 0; i < (num_rows * num_cols); ++i) { |
| 88 | const int r = i / num_cols, c = i % num_cols; |
| 89 | if (r != c) { |
| 90 | rows.push_back(r); |
| 91 | cols.push_back(c); |
| 92 | values.push_back(i + 1); |
| 93 | } |
| 94 | } |
| 95 | ASSERT_EQ(values.size(), expected_num_nonzeros); |
| 96 | |
| 97 | tsm.reset(new TripletSparseMatrix(num_rows, |
| 98 | num_cols, |
| 99 | expected_num_nonzeros)); |
| 100 | std::copy(rows.begin(), rows.end(), tsm->mutable_rows()); |
| 101 | std::copy(cols.begin(), cols.end(), tsm->mutable_cols()); |
| 102 | std::copy(values.begin(), values.end(), tsm->mutable_values()); |
| 103 | tsm->set_num_nonzeros(values.size()); |
| 104 | |
| 105 | Matrix dense_from_tsm; |
| 106 | tsm->ToDenseMatrix(&dense_from_tsm); |
| 107 | ASSERT_TRUE((dense.array() == dense_from_tsm.array()).all()); |
| 108 | |
| 109 | crsm.reset(new CompressedRowSparseMatrix(*tsm)); |
| 110 | Matrix dense_from_crsm; |
| 111 | crsm->ToDenseMatrix(&dense_from_crsm); |
| 112 | ASSERT_TRUE((dense.array() == dense_from_crsm.array()).all()); |
| 113 | } |
| 114 | |
| 115 | void InsertNonZeroEntriesFromDenseReference() { |
| 116 | for (int r = 0; r < num_rows; ++r) { |
| 117 | for (int c = 0; c < num_cols; ++c) { |
| 118 | const double& v = dense(r, c); |
| 119 | if (v != 0.0) { |
| 120 | dcrsm->InsertEntry(r, c, v); |
| 121 | } |
| 122 | } |
| 123 | } |
| 124 | } |
| 125 | |
| 126 | void ExpectEmpty() { |
| 127 | EXPECT_EQ(dcrsm->num_rows(), num_rows); |
| 128 | EXPECT_EQ(dcrsm->num_cols(), num_cols); |
| 129 | EXPECT_EQ(dcrsm->num_nonzeros(), 0); |
| 130 | |
| 131 | Matrix dense_from_dcrsm; |
| 132 | dcrsm->ToDenseMatrix(&dense_from_dcrsm); |
| 133 | EXPECT_EQ(dense_from_dcrsm.rows(), num_rows); |
| 134 | EXPECT_EQ(dense_from_dcrsm.cols(), num_cols); |
| 135 | EXPECT_TRUE((dense_from_dcrsm.array() == 0.0).all()); |
| 136 | } |
| 137 | |
| 138 | void ExpectEqualToDenseReference() { |
| 139 | Matrix dense_from_dcrsm; |
| 140 | dcrsm->ToDenseMatrix(&dense_from_dcrsm); |
| 141 | EXPECT_TRUE((dense.array() == dense_from_dcrsm.array()).all()); |
| 142 | } |
| 143 | |
| 144 | void ExpectEqualToCompressedRowSparseMatrixReference() { |
| 145 | typedef Eigen::Map<const Eigen::VectorXi> ConstIntVectorRef; |
| 146 | |
| 147 | ConstIntVectorRef crsm_rows(crsm->rows(), crsm->num_rows() + 1); |
| 148 | ConstIntVectorRef dcrsm_rows(dcrsm->rows(), dcrsm->num_rows() + 1); |
| 149 | EXPECT_TRUE((crsm_rows.array() == dcrsm_rows.array()).all()); |
| 150 | |
| 151 | ConstIntVectorRef crsm_cols(crsm->cols(), crsm->num_nonzeros()); |
| 152 | ConstIntVectorRef dcrsm_cols(dcrsm->cols(), dcrsm->num_nonzeros()); |
| 153 | EXPECT_TRUE((crsm_cols.array() == dcrsm_cols.array()).all()); |
| 154 | |
| 155 | ConstVectorRef crsm_values(crsm->values(), crsm->num_nonzeros()); |
| 156 | ConstVectorRef dcrsm_values(dcrsm->values(), dcrsm->num_nonzeros()); |
| 157 | EXPECT_TRUE((crsm_values.array() == dcrsm_values.array()).all()); |
| 158 | } |
| 159 | |
| 160 | int num_rows; |
| 161 | int num_cols; |
| 162 | |
| 163 | int num_additional_elements; |
| 164 | |
| 165 | int expected_num_nonzeros; |
| 166 | |
| 167 | Matrix dense; |
| 168 | scoped_ptr<TripletSparseMatrix> tsm; |
| 169 | scoped_ptr<CompressedRowSparseMatrix> crsm; |
| 170 | |
| 171 | scoped_ptr<DynamicCompressedRowSparseMatrix> dcrsm; |
| 172 | }; |
| 173 | |
| 174 | TEST_F(DynamicCompressedRowSparseMatrixTest, Initialization) { |
| 175 | ExpectEmpty(); |
| 176 | |
| 177 | Finalize(); |
| 178 | ExpectEmpty(); |
| 179 | } |
| 180 | |
| 181 | TEST_F(DynamicCompressedRowSparseMatrixTest, InsertEntryAndFinalize) { |
| 182 | InsertNonZeroEntriesFromDenseReference(); |
| 183 | ExpectEmpty(); |
| 184 | |
| 185 | Finalize(); |
| 186 | ExpectEqualToDenseReference(); |
| 187 | ExpectEqualToCompressedRowSparseMatrixReference(); |
| 188 | } |
| 189 | |
| 190 | TEST_F(DynamicCompressedRowSparseMatrixTest, ClearRows) { |
| 191 | InsertNonZeroEntriesFromDenseReference(); |
| 192 | Finalize(); |
| 193 | ExpectEqualToDenseReference(); |
| 194 | ExpectEqualToCompressedRowSparseMatrixReference(); |
| 195 | |
| 196 | dcrsm->ClearRows(0, 0); |
| 197 | Finalize(); |
| 198 | ExpectEqualToDenseReference(); |
| 199 | ExpectEqualToCompressedRowSparseMatrixReference(); |
| 200 | |
| 201 | dcrsm->ClearRows(0, num_rows); |
| 202 | ExpectEqualToCompressedRowSparseMatrixReference(); |
| 203 | |
| 204 | Finalize(); |
| 205 | ExpectEmpty(); |
| 206 | |
| 207 | InsertNonZeroEntriesFromDenseReference(); |
| 208 | dcrsm->ClearRows(1, 2); |
| 209 | Finalize(); |
| 210 | dense.block(1, 0, 2, num_cols).setZero(); |
| 211 | ExpectEqualToDenseReference(); |
| 212 | |
| 213 | InitialiseDenseReference(); |
| 214 | } |
| 215 | |
| 216 | } // namespace internal |
| 217 | } // namespace ceres |