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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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// modification, are permitted provided that the following conditions are met:
//
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// this list of conditions and the following disclaimer.
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// this list of conditions and the following disclaimer in the documentation
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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 <memory>
#include <vector>
#include "ceres/block_structure.h"
#include "ceres/internal/config.h"
#include "ceres/internal/disable_warnings.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/export.h"
#include "ceres/linear_solver.h"
#include "ceres/small_blas.h"
#include "glog/logging.h"
namespace ceres::internal {
class ContextImpl;
// Given generalized bi-partite matrix A = [E F], with the same block
// structure as required by the Schur complement based solver, found
// in 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_NO_EXPORT PartitionedMatrixViewBase {
public:
virtual ~PartitionedMatrixViewBase();
// y += E'x
virtual void LeftMultiplyAndAccumulateE(const double* x, double* y) const = 0;
// y += F'x
virtual void LeftMultiplyAndAccumulateF(const double* x, double* y) const = 0;
// y += Ex
virtual void RightMultiplyAndAccumulateE(const double* x,
double* y) const = 0;
virtual void RightMultiplyAndAccumulateE(const double* x,
double* y,
ContextImpl* context,
int num_threads) const = 0;
// y += Fx
virtual void RightMultiplyAndAccumulateF(const double* x,
double* y) const = 0;
virtual void RightMultiplyAndAccumulateF(const double* x,
double* y,
ContextImpl* context,
int num_threads) const = 0;
// Create and return the block diagonal of the matrix E'E.
virtual std::unique_ptr<BlockSparseMatrix> CreateBlockDiagonalEtE() const = 0;
// Create and return the block diagonal of the matrix F'F. Caller
// owns the result.
virtual std::unique_ptr<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 std::unique_ptr<PartitionedMatrixViewBase> Create(
const LinearSolver::Options& options, const BlockSparseMatrix& matrix);
};
template <int kRowBlockSize = Eigen::Dynamic,
int kEBlockSize = Eigen::Dynamic,
int kFBlockSize = Eigen::Dynamic>
class CERES_NO_EXPORT PartitionedMatrixView final
: 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);
void LeftMultiplyAndAccumulateE(const double* x, double* y) const final;
void LeftMultiplyAndAccumulateF(const double* x, double* y) const final;
void RightMultiplyAndAccumulateE(const double* x, double* y) const final;
void RightMultiplyAndAccumulateF(const double* x, double* y) const final;
void RightMultiplyAndAccumulateE(const double* x,
double* y,
ContextImpl* context,
int num_threads) const final;
void RightMultiplyAndAccumulateF(const double* x,
double* y,
ContextImpl* context,
int num_threads) const final;
std::unique_ptr<BlockSparseMatrix> CreateBlockDiagonalEtE() const final;
std::unique_ptr<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:
std::unique_ptr<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 ceres::internal
#include "ceres/internal/reenable_warnings.h"
#endif // CERES_INTERNAL_PARTITIONED_MATRIX_VIEW_H_