mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
5742b7d0f1
The outer product computation logic in SparseNormalCholeskySolver does not work well with dynamic sparsity. The overhead of computing the sparsity pattern of the normal equations is only amortized if the sparsity is constant. If the sparsity can change from call to call SparseNormalCholeskySolver will actually be more expensive. For Eigen and for CXSparse we now explicitly compute the normal equations using their respective matrix-matrix product routines and solve. Change-Id: Ifbd8ed78987cdf71640e66ed69500442526a23d4
128 lines
4.4 KiB
C++
128 lines
4.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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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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// A solver for sparse linear least squares problem based on solving
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// the normal equations via a sparse cholesky factorization.
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#ifndef CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
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#define CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
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#include <vector>
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// This include must come before any #ifndef check on Ceres compile options.
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#include "ceres/internal/port.h"
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#include "ceres/internal/macros.h"
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#include "ceres/linear_solver.h"
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#include "ceres/suitesparse.h"
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#include "ceres/cxsparse.h"
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#ifdef CERES_USE_EIGEN_SPARSE
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#include "Eigen/SparseCholesky"
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#endif
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namespace ceres {
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namespace internal {
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class CompressedRowSparseMatrix;
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// Solves the normal equations (A'A + D'D) x = A'b, using the CHOLMOD sparse
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// cholesky solver.
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class SparseNormalCholeskySolver : public CompressedRowSparseMatrixSolver {
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public:
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explicit SparseNormalCholeskySolver(const LinearSolver::Options& options);
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virtual ~SparseNormalCholeskySolver();
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private:
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virtual LinearSolver::Summary SolveImpl(
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CompressedRowSparseMatrix* A,
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const double* b,
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const LinearSolver::PerSolveOptions& options,
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double* x);
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LinearSolver::Summary SolveImplUsingSuiteSparse(
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CompressedRowSparseMatrix* A,
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double* rhs_and_solution);
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LinearSolver::Summary SolveImplUsingCXSparse(
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CompressedRowSparseMatrix* A,
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double* rhs_and_solution);
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LinearSolver::Summary SolveImplUsingEigen(
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CompressedRowSparseMatrix* A,
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double* rhs_and_solution);
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void FreeFactorization();
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SuiteSparse ss_;
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// Cached factorization
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cholmod_factor* factor_;
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CXSparse cxsparse_;
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// Cached factorization
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cs_dis* cxsparse_factor_;
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#ifdef CERES_USE_EIGEN_SPARSE
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// The preprocessor gymnastics here are dealing with the fact that
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// before version 3.2.2, Eigen did not support a third template
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// parameter to specify the ordering.
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#if EIGEN_VERSION_AT_LEAST(3,2,2)
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typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper,
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Eigen::NaturalOrdering<int> >
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SimplicialLDLTWithNaturalOrdering;
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scoped_ptr<SimplicialLDLTWithNaturalOrdering> natural_ldlt_;
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typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper,
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Eigen::AMDOrdering<int> >
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SimplicialLDLTWithAMDOrdering;
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scoped_ptr<SimplicialLDLTWithAMDOrdering> amd_ldlt_;
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#else
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typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper>
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SimplicialLDLTWithAMDOrdering;
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scoped_ptr<SimplicialLDLTWithAMDOrdering> amd_ldlt_;
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#endif
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#endif
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scoped_ptr<CompressedRowSparseMatrix> outer_product_;
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std::vector<int> pattern_;
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const LinearSolver::Options options_;
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CERES_DISALLOW_COPY_AND_ASSIGN(SparseNormalCholeskySolver);
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};
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
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