| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2013 Google Inc. All rights reserved. | |
| // http://code.google.com/p/ceres-solver/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
| // and/or other materials provided with the distribution. | |
| // * Neither the name of Google Inc. nor the names of its contributors may be | |
| // used to endorse or promote products derived from this software without | |
| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE | |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR | |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS | |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) | |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| #include <algorithm> | |
| #include "ceres/compressed_col_sparse_matrix_utils.h" | |
| #include "ceres/internal/port.h" | |
| #include "ceres/suitesparse.h" | |
| #include "ceres/triplet_sparse_matrix.h" | |
| #include "glog/logging.h" | |
| #include "gtest/gtest.h" | |
| namespace ceres { | |
| namespace internal { | |
| TEST(_, BlockPermutationToScalarPermutation) { | |
| vector<int> blocks; | |
| // Block structure | |
| // 0 --1- ---2--- ---3--- 4 | |
| // [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] | |
| blocks.push_back(1); | |
| blocks.push_back(2); | |
| blocks.push_back(3); | |
| blocks.push_back(3); | |
| blocks.push_back(1); | |
| // Block ordering | |
| // [1, 0, 2, 4, 5] | |
| vector<int> block_ordering; | |
| block_ordering.push_back(1); | |
| block_ordering.push_back(0); | |
| block_ordering.push_back(2); | |
| block_ordering.push_back(4); | |
| block_ordering.push_back(3); | |
| // Expected ordering | |
| // [1, 2, 0, 3, 4, 5, 9, 6, 7, 8] | |
| vector<int> expected_scalar_ordering; | |
| expected_scalar_ordering.push_back(1); | |
| expected_scalar_ordering.push_back(2); | |
| expected_scalar_ordering.push_back(0); | |
| expected_scalar_ordering.push_back(3); | |
| expected_scalar_ordering.push_back(4); | |
| expected_scalar_ordering.push_back(5); | |
| expected_scalar_ordering.push_back(9); | |
| expected_scalar_ordering.push_back(6); | |
| expected_scalar_ordering.push_back(7); | |
| expected_scalar_ordering.push_back(8); | |
| vector<int> scalar_ordering; | |
| BlockOrderingToScalarOrdering(blocks, | |
| block_ordering, | |
| &scalar_ordering); | |
| EXPECT_EQ(scalar_ordering.size(), expected_scalar_ordering.size()); | |
| for (int i = 0; i < expected_scalar_ordering.size(); ++i) { | |
| EXPECT_EQ(scalar_ordering[i], expected_scalar_ordering[i]); | |
| } | |
| } | |
| // Helper function to fill the sparsity pattern of a TripletSparseMatrix. | |
| int FillBlock(const vector<int>& row_blocks, | |
| const vector<int>& col_blocks, | |
| const int row_block_id, | |
| const int col_block_id, | |
| int* rows, | |
| int* cols) { | |
| int row_pos = 0; | |
| for (int i = 0; i < row_block_id; ++i) { | |
| row_pos += row_blocks[i]; | |
| } | |
| int col_pos = 0; | |
| for (int i = 0; i < col_block_id; ++i) { | |
| col_pos += col_blocks[i]; | |
| } | |
| int offset = 0; | |
| for (int r = 0; r < row_blocks[row_block_id]; ++r) { | |
| for (int c = 0; c < col_blocks[col_block_id]; ++c, ++offset) { | |
| rows[offset] = row_pos + r; | |
| cols[offset] = col_pos + c; | |
| } | |
| } | |
| return offset; | |
| } | |
| TEST(_, ScalarMatrixToBlockMatrix) { | |
| // Block sparsity. | |
| // | |
| // [1 2 3 2] | |
| // [1] x x | |
| // [2] x x | |
| // [2] x x | |
| // num_nonzeros = 1 + 3 + 4 + 4 + 1 + 2 = 15 | |
| vector<int> col_blocks; | |
| col_blocks.push_back(1); | |
| col_blocks.push_back(2); | |
| col_blocks.push_back(3); | |
| col_blocks.push_back(2); | |
| vector<int> row_blocks; | |
| row_blocks.push_back(1); | |
| row_blocks.push_back(2); | |
| row_blocks.push_back(2); | |
| TripletSparseMatrix tsm(5, 8, 18); | |
| int* rows = tsm.mutable_rows(); | |
| int* cols = tsm.mutable_cols(); | |
| fill(tsm.mutable_values(), tsm.mutable_values() + 18, 1.0); | |
| int offset = 0; | |
| #define CERES_TEST_FILL_BLOCK(row_block_id, col_block_id) \ | |
| offset += FillBlock(row_blocks, col_blocks, \ | |
| row_block_id, col_block_id, \ | |
| rows + offset, cols + offset); | |
| CERES_TEST_FILL_BLOCK(0, 0); | |
| CERES_TEST_FILL_BLOCK(2, 0); | |
| CERES_TEST_FILL_BLOCK(1, 1); | |
| CERES_TEST_FILL_BLOCK(2, 1); | |
| CERES_TEST_FILL_BLOCK(0, 2); | |
| CERES_TEST_FILL_BLOCK(1, 3); | |
| #undef CERES_TEST_FILL_BLOCK | |
| tsm.set_num_nonzeros(offset); | |
| SuiteSparse ss; | |
| scoped_ptr<cholmod_sparse> ccsm(ss.CreateSparseMatrix(&tsm)); | |
| vector<int> expected_block_rows; | |
| expected_block_rows.push_back(0); | |
| expected_block_rows.push_back(2); | |
| expected_block_rows.push_back(1); | |
| expected_block_rows.push_back(2); | |
| expected_block_rows.push_back(0); | |
| expected_block_rows.push_back(1); | |
| vector<int> expected_block_cols; | |
| expected_block_cols.push_back(0); | |
| expected_block_cols.push_back(2); | |
| expected_block_cols.push_back(4); | |
| expected_block_cols.push_back(5); | |
| expected_block_cols.push_back(6); | |
| vector<int> block_rows; | |
| vector<int> block_cols; | |
| CompressedColumnScalarMatrixToBlockMatrix( | |
| reinterpret_cast<const int*>(ccsm->i), | |
| reinterpret_cast<const int*>(ccsm->p), | |
| row_blocks, | |
| col_blocks, | |
| &block_rows, | |
| &block_cols); | |
| EXPECT_EQ(block_cols.size(), expected_block_cols.size()); | |
| EXPECT_EQ(block_rows.size(), expected_block_rows.size()); | |
| for (int i = 0; i < expected_block_cols.size(); ++i) { | |
| EXPECT_EQ(block_cols[i], expected_block_cols[i]); | |
| } | |
| for (int i = 0; i < expected_block_rows.size(); ++i) { | |
| EXPECT_EQ(block_rows[i], expected_block_rows[i]); | |
| } | |
| ss.Free(ccsm.release()); | |
| } | |
| class SolveUpperTriangularTest : public ::testing::Test { | |
| protected: | |
| void SetUp() { | |
| cols.resize(5); | |
| rows.resize(7); | |
| values.resize(7); | |
| cols[0] = 0; | |
| rows[0] = 0; | |
| values[0] = 0.50754; | |
| cols[1] = 1; | |
| rows[1] = 1; | |
| values[1] = 0.80483; | |
| cols[2] = 2; | |
| rows[2] = 1; | |
| values[2] = 0.14120; | |
| rows[3] = 2; | |
| values[3] = 0.3; | |
| cols[3] = 4; | |
| rows[4] = 0; | |
| values[4] = 0.77696; | |
| rows[5] = 1; | |
| values[5] = 0.41860; | |
| rows[6] = 3; | |
| values[6] = 0.88979; | |
| cols[4] = 7; | |
| } | |
| vector<int> cols; | |
| vector<int> rows; | |
| vector<double> values; | |
| }; | |
| TEST_F(SolveUpperTriangularTest, SolveInPlace) { | |
| double rhs_and_solution[] = {1.0, 1.0, 2.0, 2.0}; | |
| const double expected[] = { -1.4706, -1.0962, 6.6667, 2.2477}; | |
| SolveUpperTriangularInPlace<int>(cols.size() - 1, | |
| &rows[0], | |
| &cols[0], | |
| &values[0], | |
| rhs_and_solution); | |
| for (int i = 0; i < 4; ++i) { | |
| EXPECT_NEAR(rhs_and_solution[i], expected[i], 1e-4) << i; | |
| } | |
| } | |
| TEST_F(SolveUpperTriangularTest, TransposeSolveInPlace) { | |
| double rhs_and_solution[] = {1.0, 1.0, 2.0, 2.0}; | |
| double expected[] = {1.970288, 1.242498, 6.081864, -0.057255}; | |
| SolveUpperTriangularTransposeInPlace<int>(cols.size() - 1, | |
| &rows[0], | |
| &cols[0], | |
| &values[0], | |
| rhs_and_solution); | |
| for (int i = 0; i < 4; ++i) { | |
| EXPECT_NEAR(rhs_and_solution[i], expected[i], 1e-4) << i; | |
| } | |
| } | |
| TEST_F(SolveUpperTriangularTest, RTRSolveWithSparseRHS) { | |
| double solution[4]; | |
| double expected[] = { 6.8420e+00, 1.0057e+00, -1.4907e-16, -1.9335e+00, | |
| 1.0057e+00, 2.2275e+00, -1.9493e+00, -6.5693e-01, | |
| -1.4907e-16, -1.9493e+00, 1.1111e+01, 9.7381e-17, | |
| -1.9335e+00, -6.5693e-01, 9.7381e-17, 1.2631e+00 }; | |
| for (int i = 0; i < 4; ++i) { | |
| SolveRTRWithSparseRHS<int>(cols.size() - 1, | |
| &rows[0], | |
| &cols[0], | |
| &values[0], | |
| i, | |
| solution); | |
| for (int j = 0; j < 4; ++j) { | |
| EXPECT_NEAR(solution[j], expected[4 * i + j], 1e-3) << i; | |
| } | |
| } | |
| } | |
| } // namespace internal | |
| } // namespace ceres |