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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2017 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: sameeragarwal@google.com (Sameer Agarwal)
#ifndef CERES_INTERNAL_SPARSE_CHOLESKY_H_
#define CERES_INTERNAL_SPARSE_CHOLESKY_H_
// This include must come before any #ifndef check on Ceres compile options.
// clang-format off
#include "ceres/internal/port.h"
// clang-format on
#include <memory>
#include "ceres/linear_solver.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
// An interface that abstracts away the internal details of various
// sparse linear algebra libraries and offers a simple API for solving
// symmetric positive definite linear systems using a sparse Cholesky
// factorization.
//
// Instances of SparseCholesky are expected to cache the symbolic
// factorization of the linear system. They do this on the first call
// to Factorize or FactorAndSolve. Subsequent calls to Factorize and
// FactorAndSolve are expected to have the same sparsity structure.
//
// Example usage:
//
// std::unique_ptr<SparseCholesky>
// sparse_cholesky(SparseCholesky::Create(SUITE_SPARSE, AMD));
//
// CompressedRowSparseMatrix lhs = ...;
// std::string message;
// CHECK_EQ(sparse_cholesky->Factorize(&lhs, &message), LINEAR_SOLVER_SUCCESS);
// Vector rhs = ...;
// Vector solution = ...;
// CHECK_EQ(sparse_cholesky->Solve(rhs.data(), solution.data(), &message),
// LINEAR_SOLVER_SUCCESS);
class CERES_EXPORT_INTERNAL SparseCholesky {
public:
static std::unique_ptr<SparseCholesky> Create(
const LinearSolver::Options& options);
virtual ~SparseCholesky();
// Due to the symmetry of the linear system, sparse linear algebra
// libraries only use one half of the input matrix. Whether it is
// the upper or the lower triangular part of the matrix depends on
// the library and the re-ordering strategy being used. This
// function tells the user the storage type expected of the input
// matrix for the sparse linear algebra library and reordering
// strategy used.
virtual CompressedRowSparseMatrix::StorageType StorageType() const = 0;
// Computes the numeric factorization of the given matrix. If this
// is the first call to Factorize, first the symbolic factorization
// will be computed and cached and the numeric factorization will be
// computed based on that.
//
// Subsequent calls to Factorize will use that symbolic
// factorization assuming that the sparsity of the matrix has
// remained constant.
virtual LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
std::string* message) = 0;
// Computes the solution to the equation
//
// lhs * solution = rhs
virtual LinearSolverTerminationType Solve(const double* rhs,
double* solution,
std::string* message) = 0;
// Convenience method which combines a call to Factorize and
// Solve. Solve is only called if Factorize returns
// LINEAR_SOLVER_SUCCESS.
virtual LinearSolverTerminationType FactorAndSolve(
CompressedRowSparseMatrix* lhs,
const double* rhs,
double* solution,
std::string* message);
};
class IterativeRefiner;
// Computes an initial solution using the given instance of
// SparseCholesky, and then refines it using the IterativeRefiner.
class CERES_EXPORT_INTERNAL RefinedSparseCholesky : public SparseCholesky {
public:
RefinedSparseCholesky(std::unique_ptr<SparseCholesky> sparse_cholesky,
std::unique_ptr<IterativeRefiner> iterative_refiner);
virtual ~RefinedSparseCholesky();
virtual CompressedRowSparseMatrix::StorageType StorageType() const;
virtual LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
std::string* message);
virtual LinearSolverTerminationType Solve(const double* rhs,
double* solution,
std::string* message);
private:
std::unique_ptr<SparseCholesky> sparse_cholesky_;
std::unique_ptr<IterativeRefiner> iterative_refiner_;
CompressedRowSparseMatrix* lhs_ = nullptr;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_SPARSE_CHOLESKY_H_
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