| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2010, 2011, 2012 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 "gtest/gtest.h" | |
| #include "ceres/linear_solver.h" | |
| #include "ceres/parameter_block.h" | |
| #include "ceres/problem_impl.h" | |
| #include "ceres/program.h" | |
| #include "ceres/residual_block.h" | |
| #include "ceres/solver_impl.h" | |
| #include "ceres/sized_cost_function.h" | |
| namespace ceres { | |
| namespace internal { | |
| // Templated base class for the CostFunction signatures. | |
| template <int kNumResiduals, int N0, int N1, int N2> | |
| class MockCostFunctionBase : public | |
| SizedCostFunction<kNumResiduals, N0, N1, N2> { | |
| public: | |
| virtual bool Evaluate(double const* const* parameters, | |
| double* residuals, | |
| double** jacobians) const { | |
| // Do nothing. This is never called. | |
| return true; | |
| } | |
| }; | |
| class UnaryCostFunction : public MockCostFunctionBase<2, 1, 0, 0> {}; | |
| class BinaryCostFunction : public MockCostFunctionBase<2, 1, 1, 0> {}; | |
| class TernaryCostFunction : public MockCostFunctionBase<2, 1, 1, 1> {}; | |
| TEST(SolverImpl, RemoveFixedBlocksNothingConstant) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y); | |
| problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z); | |
| string error; | |
| { | |
| int num_eliminate_blocks = 0; | |
| Program program(*problem.mutable_program()); | |
| EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program, | |
| &num_eliminate_blocks, | |
| &error)); | |
| EXPECT_EQ(program.NumParameterBlocks(), 3); | |
| EXPECT_EQ(program.NumResidualBlocks(), 3); | |
| EXPECT_EQ(num_eliminate_blocks, 0); | |
| } | |
| // Check that num_eliminate_blocks is preserved, when it contains | |
| // all blocks. | |
| { | |
| int num_eliminate_blocks = 3; | |
| Program program(problem.program()); | |
| EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program, | |
| &num_eliminate_blocks, | |
| &error)); | |
| EXPECT_EQ(program.NumParameterBlocks(), 3); | |
| EXPECT_EQ(program.NumResidualBlocks(), 3); | |
| EXPECT_EQ(num_eliminate_blocks, 3); | |
| } | |
| } | |
| TEST(SolverImpl, RemoveFixedBlocksAllParameterBlocksConstant) { | |
| ProblemImpl problem; | |
| double x; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.SetParameterBlockConstant(&x); | |
| int num_eliminate_blocks = 0; | |
| Program program(problem.program()); | |
| string error; | |
| EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program, | |
| &num_eliminate_blocks, | |
| &error)); | |
| EXPECT_EQ(program.NumParameterBlocks(), 0); | |
| EXPECT_EQ(program.NumResidualBlocks(), 0); | |
| EXPECT_EQ(num_eliminate_blocks, 0); | |
| } | |
| TEST(SolverImpl, RemoveFixedBlocksNoResidualBlocks) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| int num_eliminate_blocks = 0; | |
| Program program(problem.program()); | |
| string error; | |
| EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program, | |
| &num_eliminate_blocks, | |
| &error)); | |
| EXPECT_EQ(program.NumParameterBlocks(), 0); | |
| EXPECT_EQ(program.NumResidualBlocks(), 0); | |
| EXPECT_EQ(num_eliminate_blocks, 0); | |
| } | |
| TEST(SolverImpl, RemoveFixedBlocksOneParameterBlockConstant) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y); | |
| problem.SetParameterBlockConstant(&x); | |
| int num_eliminate_blocks = 0; | |
| Program program(problem.program()); | |
| string error; | |
| EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program, | |
| &num_eliminate_blocks, | |
| &error)); | |
| EXPECT_EQ(program.NumParameterBlocks(), 1); | |
| EXPECT_EQ(program.NumResidualBlocks(), 1); | |
| EXPECT_EQ(num_eliminate_blocks, 0); | |
| } | |
| TEST(SolverImpl, RemoveFixedBlocksNumEliminateBlocks) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y); | |
| problem.SetParameterBlockConstant(&x); | |
| int num_eliminate_blocks = 2; | |
| Program program(problem.program()); | |
| string error; | |
| EXPECT_TRUE(SolverImpl::RemoveFixedBlocksFromProgram(&program, | |
| &num_eliminate_blocks, | |
| &error)); | |
| EXPECT_EQ(program.NumParameterBlocks(), 2); | |
| EXPECT_EQ(program.NumResidualBlocks(), 2); | |
| EXPECT_EQ(num_eliminate_blocks, 1); | |
| } | |
| TEST(SolverImpl, ReorderResidualBlockNonSchurSolver) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y); | |
| const vector<ResidualBlock*>& residual_blocks = | |
| problem.program().residual_blocks(); | |
| vector<ResidualBlock*> current_residual_blocks(residual_blocks); | |
| Solver::Options options; | |
| options.linear_solver_type = SPARSE_NORMAL_CHOLESKY; | |
| string error; | |
| EXPECT_TRUE(SolverImpl::MaybeReorderResidualBlocks(options, | |
| problem.mutable_program(), | |
| &error)); | |
| for (int i = 0; i < current_residual_blocks.size(); ++i) { | |
| EXPECT_EQ(current_residual_blocks[i], residual_blocks[i]); | |
| } | |
| } | |
| TEST(SolverImpl, ReorderResidualBlockNumEliminateBlockDeathTest) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.AddResidualBlock(new TernaryCostFunction(), NULL, &x, &y, &z); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y); | |
| Solver::Options options; | |
| options.linear_solver_type = DENSE_SCHUR; | |
| options.num_eliminate_blocks = 0; | |
| string error; | |
| EXPECT_DEATH( | |
| SolverImpl::MaybeReorderResidualBlocks( | |
| options, problem.mutable_program(), &error), | |
| "Congratulations"); | |
| } | |
| TEST(SolverImpl, ReorderResidualBlockNormalFunction) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &x); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &z, &x); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &z, &y); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &z); | |
| problem.AddResidualBlock(new BinaryCostFunction(), NULL, &x, &y); | |
| problem.AddResidualBlock(new UnaryCostFunction(), NULL, &y); | |
| Solver::Options options; | |
| options.linear_solver_type = DENSE_SCHUR; | |
| options.num_eliminate_blocks = 2; | |
| const vector<ResidualBlock*>& residual_blocks = | |
| problem.program().residual_blocks(); | |
| vector<ResidualBlock*> expected_residual_blocks; | |
| // This is a bit fragile, but it serves the purpose. We know the | |
| // bucketing algorithm that the reordering function uses, so we | |
| // expect the order for residual blocks for each e_block to be | |
| // filled in reverse. | |
| expected_residual_blocks.push_back(residual_blocks[4]); | |
| expected_residual_blocks.push_back(residual_blocks[1]); | |
| expected_residual_blocks.push_back(residual_blocks[0]); | |
| expected_residual_blocks.push_back(residual_blocks[5]); | |
| expected_residual_blocks.push_back(residual_blocks[2]); | |
| expected_residual_blocks.push_back(residual_blocks[3]); | |
| Program* program = problem.mutable_program(); | |
| program->SetParameterOffsetsAndIndex(); | |
| string error; | |
| EXPECT_TRUE(SolverImpl::MaybeReorderResidualBlocks(options, | |
| problem.mutable_program(), | |
| &error)); | |
| for (int i = 0; i < expected_residual_blocks.size(); ++i) { | |
| EXPECT_EQ(residual_blocks[i], expected_residual_blocks[i]); | |
| } | |
| } | |
| TEST(SolverImpl, ApplyUserOrderingOrderingTooSmall) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| vector<double*> ordering; | |
| ordering.push_back(&x); | |
| ordering.push_back(&z); | |
| Program program(problem.program()); | |
| string error; | |
| EXPECT_FALSE(SolverImpl::ApplyUserOrdering(problem, | |
| ordering, | |
| &program, | |
| &error)); | |
| } | |
| TEST(SolverImpl, ApplyUserOrderingHasDuplicates) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| vector<double*> ordering; | |
| ordering.push_back(&x); | |
| ordering.push_back(&z); | |
| ordering.push_back(&z); | |
| Program program(problem.program()); | |
| string error; | |
| EXPECT_FALSE(SolverImpl::ApplyUserOrdering(problem, | |
| ordering, | |
| &program, | |
| &error)); | |
| } | |
| TEST(SolverImpl, ApplyUserOrderingNormal) { | |
| ProblemImpl problem; | |
| double x; | |
| double y; | |
| double z; | |
| problem.AddParameterBlock(&x, 1); | |
| problem.AddParameterBlock(&y, 1); | |
| problem.AddParameterBlock(&z, 1); | |
| vector<double*> ordering; | |
| ordering.push_back(&x); | |
| ordering.push_back(&z); | |
| ordering.push_back(&y); | |
| Program* program = problem.mutable_program(); | |
| string error; | |
| EXPECT_TRUE(SolverImpl::ApplyUserOrdering(problem, | |
| ordering, | |
| program, | |
| &error)); | |
| const vector<ParameterBlock*>& parameter_blocks = program->parameter_blocks(); | |
| EXPECT_EQ(parameter_blocks.size(), 3); | |
| EXPECT_EQ(parameter_blocks[0]->user_state(), &x); | |
| EXPECT_EQ(parameter_blocks[1]->user_state(), &z); | |
| EXPECT_EQ(parameter_blocks[2]->user_state(), &y); | |
| } | |
| #ifdef CERES_NO_SUITESPARSE | |
| TEST(SolverImpl, CreateLinearSolverNoSuiteSparse) { | |
| Solver::Options options; | |
| options.linear_solver_type = SPARSE_NORMAL_CHOLESKY; | |
| string error; | |
| EXPECT_FALSE(SolverImpl::CreateLinearSolver(&options, &error)); | |
| } | |
| #endif // CERES_NO_SUITESPARSE | |
| TEST(SolverImpl, CreateLinearSolverNegativeMaxNumIterations) { | |
| Solver::Options options; | |
| options.linear_solver_type = DENSE_QR; | |
| options.linear_solver_max_num_iterations = -1; | |
| string error; | |
| EXPECT_EQ(SolverImpl::CreateLinearSolver(&options, &error), | |
| static_cast<LinearSolver*>(NULL)); | |
| } | |
| TEST(SolverImpl, CreateLinearSolverNegativeMinNumIterations) { | |
| Solver::Options options; | |
| options.linear_solver_type = DENSE_QR; | |
| options.linear_solver_min_num_iterations = -1; | |
| string error; | |
| EXPECT_EQ(SolverImpl::CreateLinearSolver(&options, &error), | |
| static_cast<LinearSolver*>(NULL)); | |
| } | |
| TEST(SolverImpl, CreateLinearSolverMaxLessThanMinIterations) { | |
| Solver::Options options; | |
| options.linear_solver_type = DENSE_QR; | |
| options.linear_solver_min_num_iterations = 10; | |
| options.linear_solver_max_num_iterations = 5; | |
| string error; | |
| EXPECT_EQ(SolverImpl::CreateLinearSolver(&options, &error), | |
| static_cast<LinearSolver*>(NULL)); | |
| } | |
| TEST(SolverImpl, CreateLinearSolverZeroNumEliminateBlocks) { | |
| Solver::Options options; | |
| options.num_eliminate_blocks = 0; | |
| options.linear_solver_type = DENSE_SCHUR; | |
| string error; | |
| scoped_ptr<LinearSolver> solver( | |
| SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_TRUE(solver != NULL); | |
| #ifndef CERES_NO_SUITESPARSE | |
| EXPECT_EQ(options.linear_solver_type, SPARSE_NORMAL_CHOLESKY); | |
| #else | |
| EXPECT_EQ(options.linear_solver_type, DENSE_QR); | |
| #endif // CERES_NO_SUITESPARSE | |
| } | |
| TEST(SolverImpl, CreateLinearSolverDenseSchurMultipleThreads) { | |
| Solver::Options options; | |
| options.num_eliminate_blocks = 1; | |
| options.linear_solver_type = DENSE_SCHUR; | |
| options.num_linear_solver_threads = 2; | |
| string error; | |
| scoped_ptr<LinearSolver> solver( | |
| SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_TRUE(solver != NULL); | |
| EXPECT_EQ(options.linear_solver_type, DENSE_SCHUR); | |
| EXPECT_EQ(options.num_linear_solver_threads, 1); | |
| } | |
| TEST(SolverImpl, CreateLinearSolverNormalOperation) { | |
| Solver::Options options; | |
| scoped_ptr<LinearSolver> solver; | |
| options.linear_solver_type = DENSE_QR; | |
| string error; | |
| solver.reset(SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_EQ(options.linear_solver_type, DENSE_QR); | |
| EXPECT_TRUE(solver.get() != NULL); | |
| #ifndef CERES_NO_SUITESPARSE | |
| options.linear_solver_type = SPARSE_NORMAL_CHOLESKY; | |
| solver.reset(SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_EQ(options.linear_solver_type, SPARSE_NORMAL_CHOLESKY); | |
| EXPECT_TRUE(solver.get() != NULL); | |
| #endif // CERES_NO_SUITESPARSE | |
| options.linear_solver_type = DENSE_SCHUR; | |
| options.num_eliminate_blocks = 2; | |
| solver.reset(SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_EQ(options.linear_solver_type, DENSE_SCHUR); | |
| EXPECT_TRUE(solver.get() != NULL); | |
| options.linear_solver_type = SPARSE_SCHUR; | |
| options.num_eliminate_blocks = 2; | |
| #ifndef CERES_NO_SUITESPARSE | |
| solver.reset(SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_TRUE(solver.get() != NULL); | |
| EXPECT_EQ(options.linear_solver_type, SPARSE_SCHUR); | |
| #else // CERES_NO_SUITESPARSE | |
| EXPECT_TRUE(SolverImpl::CreateLinearSolver(&options, &error) == NULL); | |
| #endif // CERES_NO_SUITESPARSE | |
| options.linear_solver_type = ITERATIVE_SCHUR; | |
| options.num_eliminate_blocks = 2; | |
| solver.reset(SolverImpl::CreateLinearSolver(&options, &error)); | |
| EXPECT_EQ(options.linear_solver_type, ITERATIVE_SCHUR); | |
| EXPECT_TRUE(solver.get() != NULL); | |
| } | |
| } // namespace internal | |
| } // namespace ceres |