| // 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 <glog/logging.h> |
| #include "gtest/gtest.h" |
| #include "ceres/casts.h" |
| #include "ceres/compressed_row_sparse_matrix.h" |
| #include "ceres/linear_least_squares_problems.h" |
| #include "ceres/linear_solver.h" |
| #include "ceres/triplet_sparse_matrix.h" |
| #include "ceres/internal/scoped_ptr.h" |
| #include "ceres/types.h" |
| |
| |
| namespace ceres { |
| namespace internal { |
| |
| class UnsymmetricLinearSolverTest : public ::testing::Test { |
| protected : |
| virtual void SetUp() { |
| scoped_ptr<LinearLeastSquaresProblem> problem( |
| CreateLinearLeastSquaresProblemFromId(0)); |
| |
| CHECK_NOTNULL(problem.get()); |
| A_.reset(down_cast<TripletSparseMatrix*>(problem->A.release())); |
| b_.reset(problem->b.release()); |
| D_.reset(problem->D.release()); |
| sol1_.reset(problem->x.release()); |
| sol2_.reset(problem->x_D.release()); |
| x_.reset(new double[A_->num_cols()]); |
| } |
| |
| void TestSolver(LinearSolverType linear_solver_type) { |
| LinearSolver::Options options; |
| options.type = linear_solver_type; |
| scoped_ptr<LinearSolver> solver(LinearSolver::Create(options)); |
| |
| LinearSolver::PerSolveOptions per_solve_options; |
| |
| // Unregularized |
| LinearSolver::Summary summary = |
| solver->Solve(A_.get(), b_.get(), per_solve_options, x_.get()); |
| |
| EXPECT_EQ(summary.termination_type, TOLERANCE); |
| |
| for (int i = 0; i < A_->num_cols(); ++i) { |
| EXPECT_NEAR(sol1_[i], x_[i], 1e-8); |
| } |
| |
| // Regularized solution |
| per_solve_options.D = D_.get(); |
| summary = solver->Solve(A_.get(), b_.get(), per_solve_options, x_.get()); |
| |
| EXPECT_EQ(summary.termination_type, TOLERANCE); |
| |
| for (int i = 0; i < A_->num_cols(); ++i) { |
| EXPECT_NEAR(sol2_[i], x_[i], 1e-8); |
| } |
| } |
| |
| scoped_ptr<TripletSparseMatrix> A_; |
| scoped_array<double> b_; |
| scoped_array<double> D_; |
| scoped_array<double> sol1_; |
| scoped_array<double> sol2_; |
| |
| scoped_array<double> x_; |
| }; |
| |
| // TODO(keir): Reduce duplication. |
| TEST_F(UnsymmetricLinearSolverTest, DenseQR) { |
| LinearSolver::Options options; |
| options.type = DENSE_QR; |
| scoped_ptr<LinearSolver> solver(LinearSolver::Create(options)); |
| |
| LinearSolver::PerSolveOptions per_solve_options; |
| DenseSparseMatrix A(*A_); |
| |
| // Unregularized |
| LinearSolver::Summary summary = |
| solver->Solve(&A, b_.get(), per_solve_options, x_.get()); |
| |
| EXPECT_EQ(summary.termination_type, TOLERANCE); |
| for (int i = 0; i < A_->num_cols(); ++i) { |
| EXPECT_NEAR(sol1_[i], x_[i], 1e-8); |
| } |
| |
| VectorRef x(x_.get(), A_->num_cols()); |
| VectorRef b(b_.get(), A_->num_rows()); |
| Vector r = A.matrix()*x - b; |
| LOG(INFO) << "r = A*x - b: \n" << r; |
| |
| // Regularized solution |
| per_solve_options.D = D_.get(); |
| summary = solver->Solve(&A, b_.get(), per_solve_options, x_.get()); |
| |
| EXPECT_EQ(summary.termination_type, TOLERANCE); |
| for (int i = 0; i < A_->num_cols(); ++i) { |
| EXPECT_NEAR(sol2_[i], x_[i], 1e-8); |
| } |
| } |
| |
| #ifndef CERES_NO_SUITESPARSE |
| TEST_F(UnsymmetricLinearSolverTest, SparseNormalCholesky) { |
| LinearSolver::Options options; |
| options.type = SPARSE_NORMAL_CHOLESKY; |
| scoped_ptr<LinearSolver>solver(LinearSolver::Create(options)); |
| |
| LinearSolver::PerSolveOptions per_solve_options; |
| CompressedRowSparseMatrix A(*A_); |
| |
| // Unregularized |
| LinearSolver::Summary summary = |
| solver->Solve(&A, b_.get(), per_solve_options, x_.get()); |
| |
| EXPECT_EQ(summary.termination_type, TOLERANCE); |
| for (int i = 0; i < A_->num_cols(); ++i) { |
| EXPECT_NEAR(sol1_[i], x_[i], 1e-8); |
| } |
| |
| // Regularized solution |
| per_solve_options.D = D_.get(); |
| summary = solver->Solve(&A, b_.get(), per_solve_options, x_.get()); |
| |
| EXPECT_EQ(summary.termination_type, TOLERANCE); |
| for (int i = 0; i < A_->num_cols(); ++i) { |
| EXPECT_NEAR(sol2_[i], x_[i], 1e-8); |
| } |
| } |
| #endif // CERES_NO_SUITESPARSE |
| |
| } // namespace internal |
| } // namespace ceres |