mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 00:50:37 +08:00
Sameer Agarwal
0338f9a8e6
When the Schur complement is of size zero, i.e. none of the parameter blocks interact with each other, the ITERATIVE_SCHUR linear solver crashes due to some checks that are triggered in the SCHUR_JACOBI preconditioner. This patch adds logic to detect this condition and to deal with it and adds tests that verify the fix. Thanks to Soohyun Bae for reporting this bug. Change-Id: If29ddf32463cbb1960414fff0e29bbf0d2ee7989
133 lines
4.8 KiB
C++
133 lines
4.8 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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//
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// TODO(sameeragarwal): Add support for larger, more complicated and
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// poorly conditioned problems both for correctness testing as well as
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// benchmarking.
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#include "ceres/iterative_schur_complement_solver.h"
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#include <cstddef>
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#include "Eigen/Dense"
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#include "ceres/block_random_access_dense_matrix.h"
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#include "ceres/block_sparse_matrix.h"
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#include "ceres/casts.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/scoped_ptr.h"
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#include "ceres/linear_least_squares_problems.h"
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#include "ceres/linear_solver.h"
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#include "ceres/schur_eliminator.h"
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#include "ceres/triplet_sparse_matrix.h"
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#include "ceres/types.h"
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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namespace ceres {
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namespace internal {
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using testing::AssertionResult;
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const double kEpsilon = 1e-14;
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class IterativeSchurComplementSolverTest : public ::testing::Test {
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protected :
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void SetUpProblem(int problem_id) {
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scoped_ptr<LinearLeastSquaresProblem> problem(
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CreateLinearLeastSquaresProblemFromId(problem_id));
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CHECK_NOTNULL(problem.get());
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A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
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b_.reset(problem->b.release());
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D_.reset(problem->D.release());
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num_cols_ = A_->num_cols();
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num_rows_ = A_->num_rows();
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num_eliminate_blocks_ = problem->num_eliminate_blocks;
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}
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AssertionResult TestSolver(double* D) {
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TripletSparseMatrix triplet_A(A_->num_rows(),
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A_->num_cols(),
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A_->num_nonzeros());
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A_->ToTripletSparseMatrix(&triplet_A);
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DenseSparseMatrix dense_A(triplet_A);
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LinearSolver::Options options;
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options.type = DENSE_QR;
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scoped_ptr<LinearSolver> qr(LinearSolver::Create(options));
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LinearSolver::PerSolveOptions per_solve_options;
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per_solve_options.D = D;
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Vector reference_solution(num_cols_);
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qr->Solve(&dense_A, b_.get(), per_solve_options, reference_solution.data());
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options.elimination_groups.push_back(num_eliminate_blocks_);
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options.elimination_groups.push_back(0);
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options.max_num_iterations = num_cols_;
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options.preconditioner_type = SCHUR_JACOBI;
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IterativeSchurComplementSolver isc(options);
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Vector isc_sol(num_cols_);
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per_solve_options.r_tolerance = 1e-12;
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isc.Solve(A_.get(), b_.get(), per_solve_options, isc_sol.data());
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double diff = (isc_sol - reference_solution).norm();
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if (diff < kEpsilon) {
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return testing::AssertionSuccess();
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} else {
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return testing::AssertionFailure()
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<< "The reference solution differs from the ITERATIVE_SCHUR"
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<< " solution by " << diff << " which is more than " << kEpsilon;
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}
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}
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int num_rows_;
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int num_cols_;
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int num_eliminate_blocks_;
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scoped_ptr<BlockSparseMatrix> A_;
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scoped_array<double> b_;
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scoped_array<double> D_;
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};
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TEST_F(IterativeSchurComplementSolverTest, NormalProblem) {
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SetUpProblem(2);
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EXPECT_TRUE(TestSolver(NULL));
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EXPECT_TRUE(TestSolver(D_.get()));
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}
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TEST_F(IterativeSchurComplementSolverTest, ProblemWithNoFBlocks) {
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SetUpProblem(3);
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EXPECT_TRUE(TestSolver(NULL));
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EXPECT_TRUE(TestSolver(D_.get()));
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}
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} // namespace internal
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} // namespace ceres
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