// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2023 Google Inc. All rights reserved. // http://ceres-solver.org/ // // 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: keir@google.com (Keir Mierle) // sameeragarwal@google.com (Sameer Agarwal) // // End-to-end tests for Ceres using Powell's function. #include #include #include "ceres/autodiff_cost_function.h" #include "ceres/internal/config.h" #include "ceres/problem.h" #include "ceres/solver.h" #include "ceres/test_util.h" #include "ceres/types.h" #include "glog/logging.h" #include "gtest/gtest.h" namespace ceres::internal { // This class implements the SystemTestProblem interface and provides // access to an implementation of Powell's singular function. // // F = 1/2 (f1^2 + f2^2 + f3^2 + f4^2) // // f1 = x1 + 10*x2; // f2 = sqrt(5) * (x3 - x4) // f3 = (x2 - 2*x3)^2 // f4 = sqrt(10) * (x1 - x4)^2 // // The starting values are x1 = 3, x2 = -1, x3 = 0, x4 = 1. // The minimum is 0 at (x1, x2, x3, x4) = 0. // // From: Testing Unconstrained Optimization Software by Jorge J. More, Burton S. // Garbow and Kenneth E. Hillstrom in ACM Transactions on Mathematical Software, // Vol 7(1), March 1981. class PowellsFunction { public: PowellsFunction() { x_[0] = 3.0; x_[1] = -1.0; x_[2] = 0.0; x_[3] = 1.0; problem_.AddResidualBlock( new AutoDiffCostFunction(new F1), nullptr, &x_[0], &x_[1]); problem_.AddResidualBlock( new AutoDiffCostFunction(new F2), nullptr, &x_[2], &x_[3]); problem_.AddResidualBlock( new AutoDiffCostFunction(new F3), nullptr, &x_[1], &x_[2]); problem_.AddResidualBlock( new AutoDiffCostFunction(new F4), nullptr, &x_[0], &x_[3]); // Settings for the reference solution. options_.linear_solver_type = ceres::DENSE_QR; options_.max_num_iterations = 10; options_.num_threads = 1; } Problem* mutable_problem() { return &problem_; } Solver::Options* mutable_solver_options() { return &options_; } static double kResidualTolerance; private: // Templated functions used for automatically differentiated cost // functions. class F1 { public: template bool operator()(const T* const x1, const T* const x2, T* residual) const { // f1 = x1 + 10 * x2; *residual = x1[0] + 10.0 * x2[0]; return true; } }; class F2 { public: template bool operator()(const T* const x3, const T* const x4, T* residual) const { // f2 = sqrt(5) (x3 - x4) *residual = sqrt(5.0) * (x3[0] - x4[0]); return true; } }; class F3 { public: template bool operator()(const T* const x2, const T* const x3, T* residual) const { // f3 = (x2 - 2 x3)^2 residual[0] = (x2[0] - 2.0 * x3[0]) * (x2[0] - 2.0 * x3[0]); return true; } }; class F4 { public: template bool operator()(const T* const x1, const T* const x4, T* residual) const { // f4 = sqrt(10) (x1 - x4)^2 residual[0] = sqrt(10.0) * (x1[0] - x4[0]) * (x1[0] - x4[0]); return true; } }; double x_[4]; Problem problem_; Solver::Options options_; }; double PowellsFunction::kResidualTolerance = 1e-8; using PowellTest = SystemTest; TEST_F(PowellTest, DenseQR) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = DENSE_QR; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } TEST_F(PowellTest, DenseNormalCholesky) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = DENSE_NORMAL_CHOLESKY; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } TEST_F(PowellTest, DenseSchur) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = DENSE_SCHUR; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } TEST_F(PowellTest, IterativeSchurWithJacobi) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = ITERATIVE_SCHUR; options->sparse_linear_algebra_library_type = NO_SPARSE; options->preconditioner_type = JACOBI; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } #ifndef CERES_NO_SUITESPARSE TEST_F(PowellTest, SparseNormalCholeskyUsingSuiteSparse) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = SPARSE_NORMAL_CHOLESKY; options->sparse_linear_algebra_library_type = SUITE_SPARSE; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } #endif // CERES_NO_SUITESPARSE #ifndef CERES_NO_ACCELERATE_SPARSE TEST_F(PowellTest, SparseNormalCholeskyUsingAccelerateSparse) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = SPARSE_NORMAL_CHOLESKY; options->sparse_linear_algebra_library_type = ACCELERATE_SPARSE; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } #endif // CERES_NO_ACCELERATE_SPARSE #ifdef CERES_USE_EIGEN_SPARSE TEST_F(PowellTest, SparseNormalCholeskyUsingEigenSparse) { PowellsFunction powells_function; Solver::Options* options = powells_function.mutable_solver_options(); options->linear_solver_type = SPARSE_NORMAL_CHOLESKY; options->sparse_linear_algebra_library_type = EIGEN_SPARSE; RunSolverForConfigAndExpectResidualsMatch(*options, powells_function.mutable_problem()); } #endif // CERES_USE_EIGEN_SPARSE } // namespace ceres::internal