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      1 // Ceres Solver - A fast non-linear least squares minimizer
      2 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
      3 // http://code.google.com/p/ceres-solver/
      4 //
      5 // Redistribution and use in source and binary forms, with or without
      6 // modification, are permitted provided that the following conditions are met:
      7 //
      8 // * Redistributions of source code must retain the above copyright notice,
      9 //   this list of conditions and the following disclaimer.
     10 // * Redistributions in binary form must reproduce the above copyright notice,
     11 //   this list of conditions and the following disclaimer in the documentation
     12 //   and/or other materials provided with the distribution.
     13 // * Neither the name of Google Inc. nor the names of its contributors may be
     14 //   used to endorse or promote products derived from this software without
     15 //   specific prior written permission.
     16 //
     17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
     18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
     19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
     20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
     21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
     22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
     23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
     24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
     25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
     26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
     27 // POSSIBILITY OF SUCH DAMAGE.
     28 //
     29 // Author: sameeragarwal (at) google.com (Sameer Agarwal)
     30 
     31 #include "ceres/casts.h"
     32 #include "ceres/compressed_row_sparse_matrix.h"
     33 #include "ceres/internal/scoped_ptr.h"
     34 #include "ceres/linear_least_squares_problems.h"
     35 #include "ceres/linear_solver.h"
     36 #include "ceres/triplet_sparse_matrix.h"
     37 #include "ceres/types.h"
     38 #include "glog/logging.h"
     39 #include "gtest/gtest.h"
     40 
     41 
     42 namespace ceres {
     43 namespace internal {
     44 
     45 class UnsymmetricLinearSolverTest : public ::testing::Test {
     46  protected :
     47   virtual void SetUp() {
     48     scoped_ptr<LinearLeastSquaresProblem> problem(
     49         CreateLinearLeastSquaresProblemFromId(0));
     50 
     51     CHECK_NOTNULL(problem.get());
     52     A_.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
     53     b_.reset(problem->b.release());
     54     D_.reset(problem->D.release());
     55     sol_unregularized_.reset(problem->x.release());
     56     sol_regularized_.reset(problem->x_D.release());
     57   }
     58 
     59   void TestSolver(
     60       LinearSolverType linear_solver_type,
     61       SparseLinearAlgebraLibraryType sparse_linear_algebra_library) {
     62     LinearSolver::Options options;
     63     options.type = linear_solver_type;
     64     options.sparse_linear_algebra_library = sparse_linear_algebra_library;
     65     options.use_block_amd = false;
     66     scoped_ptr<LinearSolver> solver(LinearSolver::Create(options));
     67 
     68     LinearSolver::PerSolveOptions per_solve_options;
     69     LinearSolver::Summary unregularized_solve_summary;
     70     LinearSolver::Summary regularized_solve_summary;
     71     Vector x_unregularized(A_->num_cols());
     72     Vector x_regularized(A_->num_cols());
     73 
     74     scoped_ptr<SparseMatrix> transformed_A;
     75 
     76     if (linear_solver_type == DENSE_QR ||
     77         linear_solver_type == DENSE_NORMAL_CHOLESKY) {
     78       transformed_A.reset(new DenseSparseMatrix(*A_));
     79     } else if (linear_solver_type == SPARSE_NORMAL_CHOLESKY) {
     80       transformed_A.reset(new   CompressedRowSparseMatrix(*A_));
     81     } else {
     82       LOG(FATAL) << "Unknown linear solver : " << linear_solver_type;
     83     }
     84     // Unregularized
     85     unregularized_solve_summary =
     86         solver->Solve(transformed_A.get(),
     87                       b_.get(),
     88                       per_solve_options,
     89                       x_unregularized.data());
     90 
     91     // Regularized solution
     92     per_solve_options.D = D_.get();
     93     regularized_solve_summary =
     94         solver->Solve(transformed_A.get(),
     95                       b_.get(),
     96                       per_solve_options,
     97                       x_regularized.data());
     98 
     99     EXPECT_EQ(unregularized_solve_summary.termination_type, TOLERANCE);
    100 
    101     for (int i = 0; i < A_->num_cols(); ++i) {
    102       EXPECT_NEAR(sol_unregularized_[i], x_unregularized[i], 1e-8);
    103     }
    104 
    105     EXPECT_EQ(regularized_solve_summary.termination_type, TOLERANCE);
    106     for (int i = 0; i < A_->num_cols(); ++i) {
    107       EXPECT_NEAR(sol_regularized_[i], x_regularized[i], 1e-8);
    108     }
    109   }
    110 
    111   scoped_ptr<TripletSparseMatrix> A_;
    112   scoped_array<double> b_;
    113   scoped_array<double> D_;
    114   scoped_array<double> sol_unregularized_;
    115   scoped_array<double> sol_regularized_;
    116 };
    117 
    118 TEST_F(UnsymmetricLinearSolverTest, DenseQR) {
    119   TestSolver(DENSE_QR, SUITE_SPARSE);
    120 }
    121 
    122 TEST_F(UnsymmetricLinearSolverTest, DenseNormalCholesky) {
    123   TestSolver(DENSE_NORMAL_CHOLESKY, SUITE_SPARSE);
    124 }
    125 
    126 #ifndef CERES_NO_SUITESPARSE
    127 TEST_F(UnsymmetricLinearSolverTest, SparseNormalCholeskyUsingSuiteSparse) {
    128   TestSolver(SPARSE_NORMAL_CHOLESKY, SUITE_SPARSE);
    129 }
    130 #endif
    131 
    132 #ifndef CERES_NO_CXSPARSE
    133 TEST_F(UnsymmetricLinearSolverTest, SparseNormalCholeskyUsingCXSparse) {
    134   TestSolver(SPARSE_NORMAL_CHOLESKY, CX_SPARSE);
    135 }
    136 #endif
    137 
    138 }  // namespace internal
    139 }  // namespace ceres
    140