// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2014 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 "ceres/reorder_program.h" #include "ceres/parameter_block.h" #include "ceres/problem_impl.h" #include "ceres/program.h" #include "ceres/sized_cost_function.h" #include "ceres/solver.h" #include "gtest/gtest.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(_, 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); ParameterBlockOrdering* linear_solver_ordering = new ParameterBlockOrdering; linear_solver_ordering->AddElementToGroup(&x, 0); linear_solver_ordering->AddElementToGroup(&y, 0); linear_solver_ordering->AddElementToGroup(&z, 1); Solver::Options options; options.linear_solver_type = DENSE_SCHUR; options.linear_solver_ordering.reset(linear_solver_ordering); 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 message; EXPECT_TRUE(LexicographicallyOrderResidualBlocks( 2, problem.mutable_program(), &message)); EXPECT_EQ(residual_blocks.size(), expected_residual_blocks.size()); for (int i = 0; i < expected_residual_blocks.size(); ++i) { EXPECT_EQ(residual_blocks[i], expected_residual_blocks[i]); } } TEST(_, ApplyOrderingOrderingTooSmall) { ProblemImpl problem; double x; double y; double z; problem.AddParameterBlock(&x, 1); problem.AddParameterBlock(&y, 1); problem.AddParameterBlock(&z, 1); ParameterBlockOrdering linear_solver_ordering; linear_solver_ordering.AddElementToGroup(&x, 0); linear_solver_ordering.AddElementToGroup(&y, 1); Program program(problem.program()); string message; EXPECT_FALSE(ApplyOrdering(problem.parameter_map(), linear_solver_ordering, &program, &message)); } TEST(_, ApplyOrderingNormal) { ProblemImpl problem; double x; double y; double z; problem.AddParameterBlock(&x, 1); problem.AddParameterBlock(&y, 1); problem.AddParameterBlock(&z, 1); ParameterBlockOrdering linear_solver_ordering; linear_solver_ordering.AddElementToGroup(&x, 0); linear_solver_ordering.AddElementToGroup(&y, 2); linear_solver_ordering.AddElementToGroup(&z, 1); Program* program = problem.mutable_program(); string message; EXPECT_TRUE(ApplyOrdering(problem.parameter_map(), linear_solver_ordering, program, &message)); 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); } } // namespace internal } // namespace ceres