internal/ceres/eigensparse.cc

// Ceres Solver - A fast non-linear least squares minimizer
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include "ceres/eigensparse.h"

#ifdef CERES_USE_EIGEN_SPARSE

#include <sstream>
#include "Eigen/SparseCholesky"
#include "Eigen/SparseCore"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/linear_solver.h"

namespace ceres {
namespace internal {

template <typename Solver>
class EigenSparseCholeskyTemplate : public EigenSparseCholesky {
 public:
  EigenSparseCholeskyTemplate() : analyzed_(false) {}
  virtual ~EigenSparseCholeskyTemplate() {}
  virtual CompressedRowSparseMatrix::StorageType StorageType() const {
    return CompressedRowSparseMatrix::LOWER_TRIANGULAR;
  }

  virtual LinearSolverTerminationType Factorize(
      const Eigen::SparseMatrix<double>& lhs, std::string* message) {
    if (!analyzed_) {
      solver_.analyzePattern(lhs);

      if (VLOG_IS_ON(2)) {
        std::stringstream ss;
        solver_.dumpMemory(ss);
        VLOG(2) << "Symbolic Analysis\n" << ss.str();
      }

      if (solver_.info() != Eigen::Success) {
        *message = "Eigen failure. Unable to find symbolic factorization.";
        return LINEAR_SOLVER_FATAL_ERROR;
      }

      analyzed_ = true;
    }

    solver_.factorize(lhs);
    if (solver_.info() != Eigen::Success) {
      *message = "Eigen failure. Unable to find numeric factorization.";
      return LINEAR_SOLVER_FAILURE;
    }
    return LINEAR_SOLVER_SUCCESS;
  }

  virtual LinearSolverTerminationType Solve(const double* rhs,
                                            double* solution,
                                            std::string* message) {
    CHECK(analyzed_) << "Solve called without a call to Factorize first.";

    VectorRef(solution, solver_.cols()) =
        solver_.solve(ConstVectorRef(rhs, solver_.cols()));
    if (solver_.info() != Eigen::Success) {
      *message = "Eigen failure. Unable to do triangular solve.";
      return LINEAR_SOLVER_FAILURE;
    }
    return LINEAR_SOLVER_SUCCESS;
  }

  virtual LinearSolverTerminationType Factorize(CompressedRowSparseMatrix* lhs,
                                                std::string* message) {
    CHECK_EQ(lhs->storage_type(), StorageType());
    Eigen::MappedSparseMatrix<double, Eigen::ColMajor> eigen_lhs(
        lhs->num_rows(),
        lhs->num_rows(),
        lhs->num_nonzeros(),
        lhs->mutable_rows(),
        lhs->mutable_cols(),
        lhs->mutable_values());
    return Factorize(eigen_lhs, message);
  }

 private:
  bool analyzed_;
  Solver solver_;
};

EigenSparseCholesky* EigenSparseCholesky::Create(
    const OrderingType ordering_type) {
  // The preprocessor gymnastics here are dealing with the fact that
  // before version 3.2.2, Eigen did not support a third template
  // parameter to specify the ordering and it always defaults to AMD.
#if EIGEN_VERSION_AT_LEAST(3, 2, 2)
  typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>,
                                Eigen::Upper,
                                Eigen::AMDOrdering<int> >
      WithAMDOrdering;
  typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>,
                                Eigen::Upper,
                                Eigen::NaturalOrdering<int> >
      WithNaturalOrdering;
  if (ordering_type == AMD) {
    return new EigenSparseCholeskyTemplate<WithAMDOrdering>();
  } else {
    return new EigenSparseCholeskyTemplate<WithNaturalOrdering>();
  }
#else
  typedef Eigen::SimplicialLDLT<Eigen::SparseMatrix<double>, Eigen::Upper>
      WithAMDOrdering;
  return new EigenSparseCholeskyTemplate<WithAMDOrdering>();
#endif
}

EigenSparseCholesky::~EigenSparseCholesky() {}

}  // namespace internal
}  // namespace ceres

#endif  // CERES_USE_EIGEN_SPARSE