Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 1 | // Ceres Solver - A fast non-linear least squares minimizer |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 2 | // Copyright 2023 Google Inc. All rights reserved. |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 3 | // http://ceres-solver.org/ |
| 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: sameeragarwal@google.com (Sameer Agarwal) |
| 30 | |
| 31 | #include "ceres/program.h" |
| 32 | |
| 33 | #include <cmath> |
| 34 | #include <limits> |
| 35 | #include <memory> |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 36 | #include <string> |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 37 | #include <utility> |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 38 | #include <vector> |
| 39 | |
| 40 | #include "ceres/internal/integer_sequence_algorithm.h" |
| 41 | #include "ceres/problem_impl.h" |
| 42 | #include "ceres/residual_block.h" |
| 43 | #include "ceres/sized_cost_function.h" |
| 44 | #include "ceres/triplet_sparse_matrix.h" |
| 45 | #include "gtest/gtest.h" |
| 46 | |
| 47 | namespace ceres { |
| 48 | namespace internal { |
| 49 | |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 50 | // A cost function that simply returns its argument. |
| 51 | class UnaryIdentityCostFunction : public SizedCostFunction<1, 1> { |
| 52 | public: |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 53 | bool Evaluate(double const* const* parameters, |
| 54 | double* residuals, |
| 55 | double** jacobians) const final { |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 56 | residuals[0] = parameters[0][0]; |
| 57 | if (jacobians != nullptr && jacobians[0] != nullptr) { |
| 58 | jacobians[0][0] = 1.0; |
| 59 | } |
| 60 | return true; |
| 61 | } |
| 62 | }; |
| 63 | |
| 64 | // Templated base class for the CostFunction signatures. |
| 65 | template <int kNumResiduals, int... Ns> |
| 66 | class MockCostFunctionBase : public SizedCostFunction<kNumResiduals, Ns...> { |
| 67 | public: |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 68 | bool Evaluate(double const* const* parameters, |
| 69 | double* residuals, |
| 70 | double** jacobians) const final { |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 71 | constexpr int kNumParameters = (Ns + ... + 0); |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 72 | |
| 73 | for (int i = 0; i < kNumResiduals; ++i) { |
| 74 | residuals[i] = kNumResiduals + kNumParameters; |
| 75 | } |
| 76 | return true; |
| 77 | } |
| 78 | }; |
| 79 | |
| 80 | class UnaryCostFunction : public MockCostFunctionBase<2, 1> {}; |
| 81 | class BinaryCostFunction : public MockCostFunctionBase<2, 1, 1> {}; |
| 82 | class TernaryCostFunction : public MockCostFunctionBase<2, 1, 1, 1> {}; |
| 83 | |
| 84 | TEST(Program, RemoveFixedBlocksNothingConstant) { |
| 85 | ProblemImpl problem; |
| 86 | double x; |
| 87 | double y; |
| 88 | double z; |
| 89 | |
| 90 | problem.AddParameterBlock(&x, 1); |
| 91 | problem.AddParameterBlock(&y, 1); |
| 92 | problem.AddParameterBlock(&z, 1); |
| 93 | problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &x); |
| 94 | problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &x, &y); |
| 95 | problem.AddResidualBlock(new TernaryCostFunction(), nullptr, &x, &y, &z); |
| 96 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 97 | std::vector<double*> removed_parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 98 | double fixed_cost = 0.0; |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 99 | std::string message; |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 100 | std::unique_ptr<Program> reduced_program( |
| 101 | problem.program().CreateReducedProgram( |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 102 | &removed_parameter_blocks, &fixed_cost, &message)); |
| 103 | |
| 104 | EXPECT_EQ(reduced_program->NumParameterBlocks(), 3); |
| 105 | EXPECT_EQ(reduced_program->NumResidualBlocks(), 3); |
| 106 | EXPECT_EQ(removed_parameter_blocks.size(), 0); |
| 107 | EXPECT_EQ(fixed_cost, 0.0); |
| 108 | } |
| 109 | |
| 110 | TEST(Program, RemoveFixedBlocksAllParameterBlocksConstant) { |
| 111 | ProblemImpl problem; |
| 112 | double x = 1.0; |
| 113 | |
| 114 | problem.AddParameterBlock(&x, 1); |
| 115 | problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &x); |
| 116 | problem.SetParameterBlockConstant(&x); |
| 117 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 118 | std::vector<double*> removed_parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 119 | double fixed_cost = 0.0; |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 120 | std::string message; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 121 | std::unique_ptr<Program> reduced_program( |
| 122 | problem.program().CreateReducedProgram( |
| 123 | &removed_parameter_blocks, &fixed_cost, &message)); |
| 124 | |
| 125 | EXPECT_EQ(reduced_program->NumParameterBlocks(), 0); |
| 126 | EXPECT_EQ(reduced_program->NumResidualBlocks(), 0); |
| 127 | EXPECT_EQ(removed_parameter_blocks.size(), 1); |
| 128 | EXPECT_EQ(removed_parameter_blocks[0], &x); |
| 129 | EXPECT_EQ(fixed_cost, 9.0); |
| 130 | } |
| 131 | |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 132 | TEST(Program, RemoveFixedBlocksNoResidualBlocks) { |
| 133 | ProblemImpl problem; |
| 134 | double x; |
| 135 | double y; |
| 136 | double z; |
| 137 | |
| 138 | problem.AddParameterBlock(&x, 1); |
| 139 | problem.AddParameterBlock(&y, 1); |
| 140 | problem.AddParameterBlock(&z, 1); |
| 141 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 142 | std::vector<double*> removed_parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 143 | double fixed_cost = 0.0; |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 144 | std::string message; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 145 | std::unique_ptr<Program> reduced_program( |
| 146 | problem.program().CreateReducedProgram( |
| 147 | &removed_parameter_blocks, &fixed_cost, &message)); |
| 148 | EXPECT_EQ(reduced_program->NumParameterBlocks(), 0); |
| 149 | EXPECT_EQ(reduced_program->NumResidualBlocks(), 0); |
| 150 | EXPECT_EQ(removed_parameter_blocks.size(), 3); |
| 151 | EXPECT_EQ(fixed_cost, 0.0); |
| 152 | } |
| 153 | |
| 154 | TEST(Program, RemoveFixedBlocksOneParameterBlockConstant) { |
| 155 | ProblemImpl problem; |
| 156 | double x; |
| 157 | double y; |
| 158 | double z; |
| 159 | |
| 160 | problem.AddParameterBlock(&x, 1); |
| 161 | problem.AddParameterBlock(&y, 1); |
| 162 | problem.AddParameterBlock(&z, 1); |
| 163 | |
| 164 | problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &x); |
| 165 | problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &x, &y); |
| 166 | problem.SetParameterBlockConstant(&x); |
| 167 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 168 | std::vector<double*> removed_parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 169 | double fixed_cost = 0.0; |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 170 | std::string message; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 171 | std::unique_ptr<Program> reduced_program( |
| 172 | problem.program().CreateReducedProgram( |
| 173 | &removed_parameter_blocks, &fixed_cost, &message)); |
| 174 | EXPECT_EQ(reduced_program->NumParameterBlocks(), 1); |
| 175 | EXPECT_EQ(reduced_program->NumResidualBlocks(), 1); |
| 176 | } |
| 177 | |
| 178 | TEST(Program, RemoveFixedBlocksNumEliminateBlocks) { |
| 179 | ProblemImpl problem; |
| 180 | double x; |
| 181 | double y; |
| 182 | double z; |
| 183 | |
| 184 | problem.AddParameterBlock(&x, 1); |
| 185 | problem.AddParameterBlock(&y, 1); |
| 186 | problem.AddParameterBlock(&z, 1); |
| 187 | problem.AddResidualBlock(new UnaryCostFunction(), nullptr, &x); |
| 188 | problem.AddResidualBlock(new TernaryCostFunction(), nullptr, &x, &y, &z); |
| 189 | problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &x, &y); |
| 190 | problem.SetParameterBlockConstant(&x); |
| 191 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 192 | std::vector<double*> removed_parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 193 | double fixed_cost = 0.0; |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 194 | std::string message; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 195 | std::unique_ptr<Program> reduced_program( |
| 196 | problem.program().CreateReducedProgram( |
| 197 | &removed_parameter_blocks, &fixed_cost, &message)); |
| 198 | EXPECT_EQ(reduced_program->NumParameterBlocks(), 2); |
| 199 | EXPECT_EQ(reduced_program->NumResidualBlocks(), 2); |
| 200 | } |
| 201 | |
| 202 | TEST(Program, RemoveFixedBlocksFixedCost) { |
| 203 | ProblemImpl problem; |
| 204 | double x = 1.23; |
| 205 | double y = 4.56; |
| 206 | double z = 7.89; |
| 207 | |
| 208 | problem.AddParameterBlock(&x, 1); |
| 209 | problem.AddParameterBlock(&y, 1); |
| 210 | problem.AddParameterBlock(&z, 1); |
| 211 | problem.AddResidualBlock(new UnaryIdentityCostFunction(), nullptr, &x); |
| 212 | problem.AddResidualBlock(new TernaryCostFunction(), nullptr, &x, &y, &z); |
| 213 | problem.AddResidualBlock(new BinaryCostFunction(), nullptr, &x, &y); |
| 214 | problem.SetParameterBlockConstant(&x); |
| 215 | |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 216 | ResidualBlock* expected_removed_block = |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 217 | problem.program().residual_blocks()[0]; |
| 218 | std::unique_ptr<double[]> scratch( |
| 219 | new double[expected_removed_block->NumScratchDoublesForEvaluate()]); |
| 220 | double expected_fixed_cost; |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 221 | expected_removed_block->Evaluate( |
| 222 | true, &expected_fixed_cost, nullptr, nullptr, scratch.get()); |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 223 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 224 | std::vector<double*> removed_parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 225 | double fixed_cost = 0.0; |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 226 | std::string message; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 227 | std::unique_ptr<Program> reduced_program( |
| 228 | problem.program().CreateReducedProgram( |
| 229 | &removed_parameter_blocks, &fixed_cost, &message)); |
| 230 | |
| 231 | EXPECT_EQ(reduced_program->NumParameterBlocks(), 2); |
| 232 | EXPECT_EQ(reduced_program->NumResidualBlocks(), 2); |
| 233 | EXPECT_DOUBLE_EQ(fixed_cost, expected_fixed_cost); |
| 234 | } |
| 235 | |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 236 | class BlockJacobianTest : public ::testing::TestWithParam<int> {}; |
| 237 | |
| 238 | TEST_P(BlockJacobianTest, CreateJacobianBlockSparsityTranspose) { |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 239 | ProblemImpl problem; |
| 240 | double x[2]; |
| 241 | double y[3]; |
| 242 | double z; |
| 243 | |
| 244 | problem.AddParameterBlock(x, 2); |
| 245 | problem.AddParameterBlock(y, 3); |
| 246 | problem.AddParameterBlock(&z, 1); |
| 247 | |
| 248 | problem.AddResidualBlock(new MockCostFunctionBase<2, 2>(), nullptr, x); |
| 249 | problem.AddResidualBlock(new MockCostFunctionBase<3, 1, 2>(), nullptr, &z, x); |
| 250 | problem.AddResidualBlock(new MockCostFunctionBase<4, 1, 3>(), nullptr, &z, y); |
| 251 | problem.AddResidualBlock(new MockCostFunctionBase<5, 1, 3>(), nullptr, &z, y); |
| 252 | problem.AddResidualBlock(new MockCostFunctionBase<1, 2, 1>(), nullptr, x, &z); |
| 253 | problem.AddResidualBlock(new MockCostFunctionBase<2, 1, 3>(), nullptr, &z, y); |
| 254 | problem.AddResidualBlock(new MockCostFunctionBase<2, 2, 1>(), nullptr, x, &z); |
| 255 | problem.AddResidualBlock(new MockCostFunctionBase<1, 3>(), nullptr, y); |
| 256 | |
| 257 | TripletSparseMatrix expected_block_sparse_jacobian(3, 8, 14); |
| 258 | { |
| 259 | int* rows = expected_block_sparse_jacobian.mutable_rows(); |
| 260 | int* cols = expected_block_sparse_jacobian.mutable_cols(); |
| 261 | double* values = expected_block_sparse_jacobian.mutable_values(); |
| 262 | rows[0] = 0; |
| 263 | cols[0] = 0; |
| 264 | |
| 265 | rows[1] = 2; |
| 266 | cols[1] = 1; |
| 267 | rows[2] = 0; |
| 268 | cols[2] = 1; |
| 269 | |
| 270 | rows[3] = 2; |
| 271 | cols[3] = 2; |
| 272 | rows[4] = 1; |
| 273 | cols[4] = 2; |
| 274 | |
| 275 | rows[5] = 2; |
| 276 | cols[5] = 3; |
| 277 | rows[6] = 1; |
| 278 | cols[6] = 3; |
| 279 | |
| 280 | rows[7] = 0; |
| 281 | cols[7] = 4; |
| 282 | rows[8] = 2; |
| 283 | cols[8] = 4; |
| 284 | |
| 285 | rows[9] = 2; |
| 286 | cols[9] = 5; |
| 287 | rows[10] = 1; |
| 288 | cols[10] = 5; |
| 289 | |
| 290 | rows[11] = 0; |
| 291 | cols[11] = 6; |
| 292 | rows[12] = 2; |
| 293 | cols[12] = 6; |
| 294 | |
| 295 | rows[13] = 1; |
| 296 | cols[13] = 7; |
| 297 | std::fill(values, values + 14, 1.0); |
| 298 | expected_block_sparse_jacobian.set_num_nonzeros(14); |
| 299 | } |
| 300 | |
| 301 | Program* program = problem.mutable_program(); |
| 302 | program->SetParameterOffsetsAndIndex(); |
| 303 | |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 304 | const int start_row_block = GetParam(); |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 305 | std::unique_ptr<TripletSparseMatrix> actual_block_sparse_jacobian( |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 306 | program->CreateJacobianBlockSparsityTranspose(start_row_block)); |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 307 | |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 308 | Matrix expected_full_dense_jacobian; |
| 309 | expected_block_sparse_jacobian.ToDenseMatrix(&expected_full_dense_jacobian); |
| 310 | Matrix expected_dense_jacobian = |
| 311 | expected_full_dense_jacobian.rightCols(8 - start_row_block); |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 312 | |
| 313 | Matrix actual_dense_jacobian; |
| 314 | actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian); |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 315 | EXPECT_EQ(expected_dense_jacobian.rows(), actual_dense_jacobian.rows()); |
| 316 | EXPECT_EQ(expected_dense_jacobian.cols(), actual_dense_jacobian.cols()); |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 317 | EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0); |
| 318 | } |
| 319 | |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 320 | INSTANTIATE_TEST_SUITE_P(AllColumns, BlockJacobianTest, ::testing::Range(0, 7)); |
| 321 | |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 322 | template <int kNumResiduals, int kNumParameterBlocks> |
| 323 | class NumParameterBlocksCostFunction : public CostFunction { |
| 324 | public: |
| 325 | NumParameterBlocksCostFunction() { |
| 326 | set_num_residuals(kNumResiduals); |
| 327 | for (int i = 0; i < kNumParameterBlocks; ++i) { |
| 328 | mutable_parameter_block_sizes()->push_back(1); |
| 329 | } |
| 330 | } |
| 331 | |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 332 | bool Evaluate(double const* const* parameters, |
| 333 | double* residuals, |
| 334 | double** jacobians) const final { |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 335 | return true; |
| 336 | } |
| 337 | }; |
| 338 | |
| 339 | TEST(Program, ReallocationInCreateJacobianBlockSparsityTranspose) { |
| 340 | // CreateJacobianBlockSparsityTranspose starts with a conservative |
| 341 | // estimate of the size of the sparsity pattern. This test ensures |
| 342 | // that when those estimates are violated, the reallocation/resizing |
| 343 | // logic works correctly. |
| 344 | |
| 345 | ProblemImpl problem; |
| 346 | double x[20]; |
| 347 | |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 348 | std::vector<double*> parameter_blocks; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 349 | for (int i = 0; i < 20; ++i) { |
| 350 | problem.AddParameterBlock(x + i, 1); |
| 351 | parameter_blocks.push_back(x + i); |
| 352 | } |
| 353 | |
| 354 | problem.AddResidualBlock(new NumParameterBlocksCostFunction<1, 20>(), |
| 355 | nullptr, |
| 356 | parameter_blocks.data(), |
| 357 | static_cast<int>(parameter_blocks.size())); |
| 358 | |
| 359 | TripletSparseMatrix expected_block_sparse_jacobian(20, 1, 20); |
| 360 | { |
| 361 | int* rows = expected_block_sparse_jacobian.mutable_rows(); |
| 362 | int* cols = expected_block_sparse_jacobian.mutable_cols(); |
| 363 | for (int i = 0; i < 20; ++i) { |
| 364 | rows[i] = i; |
| 365 | cols[i] = 0; |
| 366 | } |
| 367 | |
| 368 | double* values = expected_block_sparse_jacobian.mutable_values(); |
| 369 | std::fill(values, values + 20, 1.0); |
| 370 | expected_block_sparse_jacobian.set_num_nonzeros(20); |
| 371 | } |
| 372 | |
| 373 | Program* program = problem.mutable_program(); |
| 374 | program->SetParameterOffsetsAndIndex(); |
| 375 | |
| 376 | std::unique_ptr<TripletSparseMatrix> actual_block_sparse_jacobian( |
| 377 | program->CreateJacobianBlockSparsityTranspose()); |
| 378 | |
| 379 | Matrix expected_dense_jacobian; |
| 380 | expected_block_sparse_jacobian.ToDenseMatrix(&expected_dense_jacobian); |
| 381 | |
| 382 | Matrix actual_dense_jacobian; |
| 383 | actual_block_sparse_jacobian->ToDenseMatrix(&actual_dense_jacobian); |
| 384 | EXPECT_EQ((expected_dense_jacobian - actual_dense_jacobian).norm(), 0.0); |
| 385 | } |
| 386 | |
| 387 | TEST(Program, ProblemHasNanParameterBlocks) { |
| 388 | ProblemImpl problem; |
| 389 | double x[2]; |
| 390 | x[0] = 1.0; |
| 391 | x[1] = std::numeric_limits<double>::quiet_NaN(); |
| 392 | problem.AddResidualBlock(new MockCostFunctionBase<1, 2>(), nullptr, x); |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 393 | std::string error; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 394 | EXPECT_FALSE(problem.program().ParameterBlocksAreFinite(&error)); |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 395 | EXPECT_NE(error.find("has at least one invalid value"), std::string::npos) |
Austin Schuh | 1d1e6ea | 2020-12-23 21:56:30 -0800 | [diff] [blame] | 396 | << error; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 397 | } |
| 398 | |
| 399 | TEST(Program, InfeasibleParameterBlock) { |
| 400 | ProblemImpl problem; |
| 401 | double x[] = {0.0, 0.0}; |
| 402 | problem.AddResidualBlock(new MockCostFunctionBase<1, 2>(), nullptr, x); |
| 403 | problem.SetParameterLowerBound(x, 0, 2.0); |
| 404 | problem.SetParameterUpperBound(x, 0, 1.0); |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 405 | std::string error; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 406 | EXPECT_FALSE(problem.program().IsFeasible(&error)); |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 407 | EXPECT_NE(error.find("infeasible bound"), std::string::npos) << error; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 408 | } |
| 409 | |
| 410 | TEST(Program, InfeasibleConstantParameterBlock) { |
| 411 | ProblemImpl problem; |
| 412 | double x[] = {0.0, 0.0}; |
| 413 | problem.AddResidualBlock(new MockCostFunctionBase<1, 2>(), nullptr, x); |
| 414 | problem.SetParameterLowerBound(x, 0, 1.0); |
| 415 | problem.SetParameterUpperBound(x, 0, 2.0); |
| 416 | problem.SetParameterBlockConstant(x); |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 417 | std::string error; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 418 | EXPECT_FALSE(problem.program().IsFeasible(&error)); |
Austin Schuh | 3de38b0 | 2024-06-25 18:25:10 -0700 | [diff] [blame^] | 419 | EXPECT_NE(error.find("infeasible value"), std::string::npos) << error; |
Austin Schuh | 70cc955 | 2019-01-21 19:46:48 -0800 | [diff] [blame] | 420 | } |
| 421 | |
| 422 | } // namespace internal |
| 423 | } // namespace ceres |