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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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//
// Author: sameeragarwal@google.com (Sameer Agarwal)
//
// For generalized bi-partite Jacobian matrices that arise in
// Structure from Motion related problems, it is sometimes useful to
// have access to the two parts of the matrix as linear operators
// themselves. This class provides that functionality.
#ifndef CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_
#define CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_
#include <algorithm>
#include <cstring>
#include <vector>
#include "ceres/block_structure.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
#include "ceres/linear_solver.h"
#include "ceres/small_blas.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
// Given generalized bi-partite matrix A = [E F], with the same block
// structure as required by the Schur complement based solver, found
// in explicit_schur_complement_solver.h, provide access to the
// matrices E and F and their outer products E'E and F'F with
// themselves.
//
// Lack of BlockStructure object will result in a crash and if the
// block structure of the matrix does not satisfy the requirements of
// the Schur complement solver it will result in unpredictable and
// wrong output.
class CERES_EXPORT_INTERNAL PartitionedMatrixViewBase {
public:
virtual ~PartitionedMatrixViewBase() {}
// y += E'x
virtual void LeftMultiplyE(const double* x, double* y) const = 0;
// y += F'x
virtual void LeftMultiplyF(const double* x, double* y) const = 0;
// y += Ex
virtual void RightMultiplyE(const double* x, double* y) const = 0;
// y += Fx
virtual void RightMultiplyF(const double* x, double* y) const = 0;
// Create and return the block diagonal of the matrix E'E.
virtual BlockSparseMatrix* CreateBlockDiagonalEtE() const = 0;
// Create and return the block diagonal of the matrix F'F. Caller
// owns the result.
virtual BlockSparseMatrix* CreateBlockDiagonalFtF() const = 0;
// Compute the block diagonal of the matrix E'E and store it in
// block_diagonal. The matrix block_diagonal is expected to have a
// BlockStructure (preferably created using
// CreateBlockDiagonalMatrixEtE) which is has the same structure as
// the block diagonal of E'E.
virtual void UpdateBlockDiagonalEtE(
BlockSparseMatrix* block_diagonal) const = 0;
// Compute the block diagonal of the matrix F'F and store it in
// block_diagonal. The matrix block_diagonal is expected to have a
// BlockStructure (preferably created using
// CreateBlockDiagonalMatrixFtF) which is has the same structure as
// the block diagonal of F'F.
virtual void UpdateBlockDiagonalFtF(
BlockSparseMatrix* block_diagonal) const = 0;
// clang-format off
virtual int num_col_blocks_e() const = 0;
virtual int num_col_blocks_f() const = 0;
virtual int num_cols_e() const = 0;
virtual int num_cols_f() const = 0;
virtual int num_rows() const = 0;
virtual int num_cols() const = 0;
// clang-format on
static PartitionedMatrixViewBase* Create(const LinearSolver::Options& options,
const BlockSparseMatrix& matrix);
};
template <int kRowBlockSize = Eigen::Dynamic,
int kEBlockSize = Eigen::Dynamic,
int kFBlockSize = Eigen::Dynamic>
class PartitionedMatrixView : public PartitionedMatrixViewBase {
public:
// matrix = [E F], where the matrix E contains the first
// num_col_blocks_a column blocks.
PartitionedMatrixView(const BlockSparseMatrix& matrix, int num_col_blocks_e);
virtual ~PartitionedMatrixView();
void LeftMultiplyE(const double* x, double* y) const final;
void LeftMultiplyF(const double* x, double* y) const final;
void RightMultiplyE(const double* x, double* y) const final;
void RightMultiplyF(const double* x, double* y) const final;
BlockSparseMatrix* CreateBlockDiagonalEtE() const final;
BlockSparseMatrix* CreateBlockDiagonalFtF() const final;
void UpdateBlockDiagonalEtE(BlockSparseMatrix* block_diagonal) const final;
void UpdateBlockDiagonalFtF(BlockSparseMatrix* block_diagonal) const final;
// clang-format off
int num_col_blocks_e() const final { return num_col_blocks_e_; }
int num_col_blocks_f() const final { return num_col_blocks_f_; }
int num_cols_e() const final { return num_cols_e_; }
int num_cols_f() const final { return num_cols_f_; }
int num_rows() const final { return matrix_.num_rows(); }
int num_cols() const final { return matrix_.num_cols(); }
// clang-format on
private:
BlockSparseMatrix* CreateBlockDiagonalMatrixLayout(int start_col_block,
int end_col_block) const;
const BlockSparseMatrix& matrix_;
int num_row_blocks_e_;
int num_col_blocks_e_;
int num_col_blocks_f_;
int num_cols_e_;
int num_cols_f_;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_