internal/ceres/block_jacobi_preconditioner.h

// Ceres Solver - A fast non-linear least squares minimizer
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// Author: keir@google.com (Keir Mierle)

#ifndef CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_
#define CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_

#include <memory>
#include "ceres/block_random_access_diagonal_matrix.h"
#include "ceres/preconditioner.h"

namespace ceres {
namespace internal {

class BlockSparseMatrix;
struct CompressedRowBlockStructure;

// A block Jacobi preconditioner. This is intended for use with
// conjugate gradients, or other iterative symmetric solvers. To use
// the preconditioner, create one by passing a BlockSparseMatrix "A"
// to the constructor. This fixes the sparsity pattern to the pattern
// of the matrix A^TA.
//
// Before each use of the preconditioner in a solve with conjugate gradients,
// update the matrix by running Update(A, D). The values of the matrix A are
// inspected to construct the preconditioner. The vector D is applied as the
// D^TD diagonal term.
class BlockJacobiPreconditioner : public BlockSparseMatrixPreconditioner {
 public:
  // A must remain valid while the BlockJacobiPreconditioner is.
  explicit BlockJacobiPreconditioner(const BlockSparseMatrix& A);
  BlockJacobiPreconditioner(const BlockJacobiPreconditioner&) = delete;
  void operator=(const BlockJacobiPreconditioner&) = delete;

  virtual ~BlockJacobiPreconditioner();

  // Preconditioner interface
  virtual void RightMultiply(const double* x, double* y) const;
  virtual int num_rows() const { return m_->num_rows(); }
  virtual int num_cols() const { return m_->num_rows(); }
  const BlockRandomAccessDiagonalMatrix& matrix() const { return *m_; }

 private:
  virtual bool UpdateImpl(const BlockSparseMatrix& A, const double* D);

  std::unique_ptr<BlockRandomAccessDiagonalMatrix> m_;
};

}  // namespace internal
}  // namespace ceres

#endif  // CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_