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- // 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 <cmath>
- #include <cstdlib>
- #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<F1, 1, 1, 1>(new F1), nullptr, &x_[0], &x_[1]);
- problem_.AddResidualBlock(
- new AutoDiffCostFunction<F2, 1, 1, 1>(new F2), nullptr, &x_[2], &x_[3]);
- problem_.AddResidualBlock(
- new AutoDiffCostFunction<F3, 1, 1, 1>(new F3), nullptr, &x_[1], &x_[2]);
- problem_.AddResidualBlock(
- new AutoDiffCostFunction<F4, 1, 1, 1>(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 <typename T>
- 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 <typename T>
- 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 <typename T>
- 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 <typename T>
- 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<PowellsFunction>;
- 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
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