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Death to BlockSparseMatrixBase

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Change-Id: I13b2b951297ae81bfab0a7b4991a791ed91d594c
This commit is contained in:
Sameer Agarwal
2013-04-24 11:58:24 -07:00
committed by Gerrit Code Review
parent cbdeb79e91
commit c1e10d9f57
22 changed files with 94 additions and 132 deletions
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internal/ceres/block_jacobi_preconditioner.cc
+4 -4
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@@ -41,7 +41,7 @@ namespace ceres {
namespace internal {
BlockJacobiPreconditioner::BlockJacobiPreconditioner(
const BlockSparseMatrixBase& A)
const BlockSparseMatrix& A)
: num_rows_(A.num_rows()),
block_structure_(*A.block_structure()) {
// Calculate the amount of storage needed.
@@ -66,19 +66,19 @@ BlockJacobiPreconditioner::BlockJacobiPreconditioner(
BlockJacobiPreconditioner::~BlockJacobiPreconditioner() {}
bool BlockJacobiPreconditioner::Update(const BlockSparseMatrixBase& A,
bool BlockJacobiPreconditioner::Update(const BlockSparseMatrix& A,
const double* D) {
const CompressedRowBlockStructure* bs = A.block_structure();
// Compute the diagonal blocks by block inner products.
std::fill(block_storage_.begin(), block_storage_.end(), 0.0);
const double* values = A.values();
for (int r = 0; r < bs->rows.size(); ++r) {
const int row_block_size = bs->rows[r].block.size;
const vector<Cell>& cells = bs->rows[r].cells;
const double* row_values = A.RowBlockValues(r);
for (int c = 0; c < cells.size(); ++c) {
const int col_block_size = bs->cols[cells[c].block_id].size;
ConstMatrixRef m(row_values + cells[c].position,
ConstMatrixRef m(values + cells[c].position,
row_block_size,
col_block_size);
internal/ceres/block_jacobi_preconditioner.h
+3 -3
View File
@@ -37,7 +37,7 @@
namespace ceres {
namespace internal {
class BlockSparseMatrixBase;
class BlockSparseMatrix;
struct CompressedRowBlockStructure;
class LinearOperator;
@@ -54,11 +54,11 @@ class LinearOperator;
class BlockJacobiPreconditioner : public Preconditioner {
public:
// A must remain valid while the BlockJacobiPreconditioner is.
explicit BlockJacobiPreconditioner(const BlockSparseMatrixBase& A);
explicit BlockJacobiPreconditioner(const BlockSparseMatrix& A);
virtual ~BlockJacobiPreconditioner();
// Preconditioner interface
virtual bool Update(const BlockSparseMatrixBase& A, const double* D);
virtual bool Update(const BlockSparseMatrix& A, const double* D);
virtual void RightMultiply(const double* x, double* y) const;
virtual void LeftMultiply(const double* x, double* y) const;
virtual int num_rows() const { return num_rows_; }
internal/ceres/block_sparse_matrix.h
+3 -38
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@@ -46,37 +46,6 @@ namespace internal {
class SparseMatrixProto;
class TripletSparseMatrix;
// A further extension of the SparseMatrix interface to support block-oriented
// matrices. The key addition is the RowBlockValues() accessor, which enables
// the lazy block sparse matrix implementation.
class BlockSparseMatrixBase : public SparseMatrix {
public:
BlockSparseMatrixBase() {}
virtual ~BlockSparseMatrixBase() {}
// Convert this matrix into a triplet sparse matrix.
virtual void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const = 0;
// Returns a pointer to the block structure. Does not transfer
// ownership.
virtual const CompressedRowBlockStructure* block_structure() const = 0;
// Returns a pointer to a row of the matrix. The returned array is only valid
// until the next call to RowBlockValues. The caller does not own the result.
//
// The returned array is laid out such that cells on the specified row are
// contiguous in the returned array, though neighbouring cells in row order
// may not be contiguous in the row values. The cell values for cell
// (row_block, cell_block) are found at offset
//
// block_structure()->rows[row_block].cells[cell_block].position
//
virtual const double* RowBlockValues(int row_block_index) const = 0;
private:
CERES_DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrixBase);
};
// This class implements the SparseMatrix interface for storing and
// manipulating block sparse matrices. The block structure is stored
// in the CompressedRowBlockStructure object and one is needed to
@@ -85,7 +54,7 @@ class BlockSparseMatrixBase : public SparseMatrix {
//
// internal/ceres/block_structure.h
//
class BlockSparseMatrix : public BlockSparseMatrixBase {
class BlockSparseMatrix : public SparseMatrix {
public:
// Construct a block sparse matrix with a fully initialized
// CompressedRowBlockStructure objected. The matrix takes over
@@ -121,12 +90,8 @@ class BlockSparseMatrix : public BlockSparseMatrixBase {
virtual const double* values() const { return values_.get(); }
virtual double* mutable_values() { return values_.get(); }
// Implementation of BlockSparseMatrixBase interface.
virtual void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const;
virtual const CompressedRowBlockStructure* block_structure() const;
virtual const double* RowBlockValues(int row_block_index) const {
return values_.get();
}
void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const;
const CompressedRowBlockStructure* block_structure() const;
private:
int num_rows_;
internal/ceres/cgnr_solver.cc
+1 -1
View File
@@ -46,7 +46,7 @@ CgnrSolver::CgnrSolver(const LinearSolver::Options& options)
}
LinearSolver::Summary CgnrSolver::SolveImpl(
BlockSparseMatrixBase* A,
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) {
internal/ceres/cgnr_solver.h
+2 -2
View File
@@ -48,11 +48,11 @@ class BlockJacobiPreconditioner;
//
// as required for solving for x in the least squares sense. Currently only
// block diagonal preconditioning is supported.
class CgnrSolver : public BlockSparseMatrixBaseSolver {
class CgnrSolver : public BlockSparseMatrixSolver {
public:
explicit CgnrSolver(const LinearSolver::Options& options);
virtual Summary SolveImpl(
BlockSparseMatrixBase* A,
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x);
internal/ceres/implicit_schur_complement.cc
+1 -1
View File
@@ -55,7 +55,7 @@ ImplicitSchurComplement::ImplicitSchurComplement(int num_eliminate_blocks,
ImplicitSchurComplement::~ImplicitSchurComplement() {
}
void ImplicitSchurComplement::Init(const BlockSparseMatrixBase& A,
void ImplicitSchurComplement::Init(const BlockSparseMatrix& A,
const double* D,
const double* b) {
// Since initialization is reasonably heavy, perhaps we can save on
internal/ceres/implicit_schur_complement.h
+1 -2
View File
@@ -44,7 +44,6 @@ namespace ceres {
namespace internal {
class BlockSparseMatrix;
class BlockSparseMatrixBase;
// This class implements various linear algebraic operations related
// to the Schur complement without explicitly forming it.
@@ -110,7 +109,7 @@ class ImplicitSchurComplement : public LinearOperator {
// is important that the matrix A have a BlockStructure object
// associated with it and has a block structure that is compatible
// with the SchurComplement solver.
void Init(const BlockSparseMatrixBase& A, const double* D, const double* b);
void Init(const BlockSparseMatrix& A, const double* D, const double* b);
// y += Sx, where S is the Schur complement.
virtual void RightMultiply(const double* x, double* y) const;
internal/ceres/iterative_schur_complement_solver.cc
+1 -1
View File
@@ -62,7 +62,7 @@ IterativeSchurComplementSolver::~IterativeSchurComplementSolver() {
}
LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl(
BlockSparseMatrixBase* A,
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) {
internal/ceres/iterative_schur_complement_solver.h
+3 -3
View File
@@ -39,7 +39,7 @@
namespace ceres {
namespace internal {
class BlockSparseMatrixBase;
class BlockSparseMatrix;
class ImplicitSchurComplement;
class Preconditioner;
@@ -67,14 +67,14 @@ class Preconditioner;
// a proof of this fact and others related to this solver please see
// the section on Domain Decomposition Methods in Saad's book
// "Iterative Methods for Sparse Linear Systems".
class IterativeSchurComplementSolver : public BlockSparseMatrixBaseSolver {
class IterativeSchurComplementSolver : public BlockSparseMatrixSolver {
public:
explicit IterativeSchurComplementSolver(const LinearSolver::Options& options);
virtual ~IterativeSchurComplementSolver();
private:
virtual LinearSolver::Summary SolveImpl(
BlockSparseMatrixBase* A,
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& options,
double* x);
internal/ceres/linear_solver.h
-1
View File
@@ -316,7 +316,6 @@ class TypedLinearSolver : public LinearSolver {
// Linear solvers that depend on acccess to the low level structure of
// a SparseMatrix.
typedef TypedLinearSolver<BlockSparseMatrix> BlockSparseMatrixSolver; // NOLINT
typedef TypedLinearSolver<BlockSparseMatrixBase> BlockSparseMatrixBaseSolver; // NOLINT
typedef TypedLinearSolver<CompressedRowSparseMatrix> CompressedRowSparseMatrixSolver; // NOLINT
typedef TypedLinearSolver<DenseSparseMatrix> DenseSparseMatrixSolver; // NOLINT
typedef TypedLinearSolver<TripletSparseMatrix> TripletSparseMatrixSolver; // NOLINT
internal/ceres/partitioned_matrix_view.cc
+15 -16
View File
@@ -45,7 +45,7 @@ namespace ceres {
namespace internal {
PartitionedMatrixView::PartitionedMatrixView(
const BlockSparseMatrixBase& matrix,
const BlockSparseMatrix& matrix,
int num_col_blocks_a)
: matrix_(matrix),
num_col_blocks_e_(num_col_blocks_a) {
@@ -96,8 +96,8 @@ void PartitionedMatrixView::RightMultiplyE(const double* x, double* y) const {
// Iterate over the first num_row_blocks_e_ row blocks, and multiply
// by the first cell in each row block.
const double* values = matrix_.values();
for (int r = 0; r < num_row_blocks_e_; ++r) {
const double* row_values = matrix_.RowBlockValues(r);
const Cell& cell = bs->rows[r].cells[0];
const int row_block_pos = bs->rows[r].block.position;
const int row_block_size = bs->rows[r].block.size;
@@ -105,7 +105,7 @@ void PartitionedMatrixView::RightMultiplyE(const double* x, double* y) const {
const int col_block_pos = bs->cols[col_block_id].position;
const int col_block_size = bs->cols[col_block_id].size;
MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + cell.position, row_block_size, col_block_size,
values + cell.position, row_block_size, col_block_size,
x + col_block_pos,
y + row_block_pos);
}
@@ -119,17 +119,17 @@ void PartitionedMatrixView::RightMultiplyF(const double* x, double* y) const {
// E. If the row block is not in E (i.e its in the bottom
// num_row_blocks - num_row_blocks_e row blocks), then all the cells
// are of type F and multiply by them all.
const double* values = matrix_.values();
for (int r = 0; r < bs->rows.size(); ++r) {
const int row_block_pos = bs->rows[r].block.position;
const int row_block_size = bs->rows[r].block.size;
const vector<Cell>& cells = bs->rows[r].cells;
for (int c = (r < num_row_blocks_e_) ? 1 : 0; c < cells.size(); ++c) {
const double* row_values = matrix_.RowBlockValues(r);
const int col_block_id = cells[c].block_id;
const int col_block_pos = bs->cols[col_block_id].position;
const int col_block_size = bs->cols[col_block_id].size;
MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + cells[c].position, row_block_size, col_block_size,
values + cells[c].position, row_block_size, col_block_size,
x + col_block_pos - num_cols_e(),
y + row_block_pos);
}
@@ -141,16 +141,16 @@ void PartitionedMatrixView::LeftMultiplyE(const double* x, double* y) const {
// Iterate over the first num_row_blocks_e_ row blocks, and multiply
// by the first cell in each row block.
const double* values = matrix_.values();
for (int r = 0; r < num_row_blocks_e_; ++r) {
const Cell& cell = bs->rows[r].cells[0];
const double* row_values = matrix_.RowBlockValues(r);
const int row_block_pos = bs->rows[r].block.position;
const int row_block_size = bs->rows[r].block.size;
const int col_block_id = cell.block_id;
const int col_block_pos = bs->cols[col_block_id].position;
const int col_block_size = bs->cols[col_block_id].size;
MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + cell.position, row_block_size, col_block_size,
values + cell.position, row_block_size, col_block_size,
x + row_block_pos,
y + col_block_pos);
}
@@ -164,17 +164,17 @@ void PartitionedMatrixView::LeftMultiplyF(const double* x, double* y) const {
// E. If the row block is not in E (i.e its in the bottom
// num_row_blocks - num_row_blocks_e row blocks), then all the cells
// are of type F and multiply by them all.
const double* values = matrix_.values();
for (int r = 0; r < bs->rows.size(); ++r) {
const int row_block_pos = bs->rows[r].block.position;
const int row_block_size = bs->rows[r].block.size;
const vector<Cell>& cells = bs->rows[r].cells;
for (int c = (r < num_row_blocks_e_) ? 1 : 0; c < cells.size(); ++c) {
const double* row_values = matrix_.RowBlockValues(r);
const int col_block_id = cells[c].block_id;
const int col_block_pos = bs->cols[col_block_id].position;
const int col_block_size = bs->cols[col_block_id].size;
MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + cells[c].position, row_block_size, col_block_size,
values + cells[c].position, row_block_size, col_block_size,
x + row_block_pos,
y + col_block_pos - num_cols_e());
}
@@ -248,9 +248,8 @@ void PartitionedMatrixView::UpdateBlockDiagonalEtE(
block_diagonal->block_structure();
block_diagonal->SetZero();
const double* values = matrix_.values();
for (int r = 0; r < num_row_blocks_e_ ; ++r) {
const double* row_values = matrix_.RowBlockValues(r);
const Cell& cell = bs->rows[r].cells[0];
const int row_block_size = bs->rows[r].block.size;
const int block_id = cell.block_id;
@@ -260,8 +259,8 @@ void PartitionedMatrixView::UpdateBlockDiagonalEtE(
MatrixTransposeMatrixMultiply
<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + cell.position, row_block_size, col_block_size,
row_values + cell.position, row_block_size, col_block_size,
values + cell.position, row_block_size, col_block_size,
values + cell.position, row_block_size, col_block_size,
block_diagonal->mutable_values() + cell_position,
0, 0, col_block_size, col_block_size);
}
@@ -279,10 +278,10 @@ void PartitionedMatrixView::UpdateBlockDiagonalFtF(
block_diagonal->block_structure();
block_diagonal->SetZero();
const double* values = matrix_.values();
for (int r = 0; r < bs->rows.size(); ++r) {
const int row_block_size = bs->rows[r].block.size;
const vector<Cell>& cells = bs->rows[r].cells;
const double* row_values = matrix_.RowBlockValues(r);
for (int c = (r < num_row_blocks_e_) ? 1 : 0; c < cells.size(); ++c) {
const int col_block_id = cells[c].block_id;
const int col_block_size = bs->cols[col_block_id].size;
@@ -292,8 +291,8 @@ void PartitionedMatrixView::UpdateBlockDiagonalFtF(
MatrixTransposeMatrixMultiply
<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + cells[c].position, row_block_size, col_block_size,
row_values + cells[c].position, row_block_size, col_block_size,
values + cells[c].position, row_block_size, col_block_size,
values + cells[c].position, row_block_size, col_block_size,
block_diagonal->mutable_values() + cell_position,
0, 0, col_block_size, col_block_size);
}
internal/ceres/partitioned_matrix_view.h
+2 -2
View File
@@ -60,7 +60,7 @@ class PartitionedMatrixView {
public:
// matrix = [E F], where the matrix E contains the first
// num_col_blocks_a column blocks.
PartitionedMatrixView(const BlockSparseMatrixBase& matrix,
PartitionedMatrixView(const BlockSparseMatrix& matrix,
int num_col_blocks_a);
~PartitionedMatrixView();
@@ -107,7 +107,7 @@ class PartitionedMatrixView {
BlockSparseMatrix* CreateBlockDiagonalMatrixLayout(int start_col_block,
int end_col_block) const;
const BlockSparseMatrixBase& matrix_;
const BlockSparseMatrix& matrix_;
int num_row_blocks_e_;
int num_col_blocks_e_;
int num_col_blocks_f_;
internal/ceres/preconditioner.cc
+1 -1
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@@ -45,7 +45,7 @@ SparseMatrixPreconditionerWrapper::SparseMatrixPreconditionerWrapper(
SparseMatrixPreconditionerWrapper::~SparseMatrixPreconditionerWrapper() {
}
bool SparseMatrixPreconditionerWrapper::Update(const BlockSparseMatrixBase& A,
bool SparseMatrixPreconditionerWrapper::Update(const BlockSparseMatrix& A,
const double* D) {
return true;
}
internal/ceres/preconditioner.h
+3 -3
View File
@@ -38,7 +38,7 @@
namespace ceres {
namespace internal {
class BlockSparseMatrixBase;
class BlockSparseMatrix;
class SparseMatrix;
class Preconditioner : public LinearOperator {
@@ -105,7 +105,7 @@ class Preconditioner : public LinearOperator {
//
// D can be NULL, in which case its interpreted as a diagonal matrix
// of size zero.
virtual bool Update(const BlockSparseMatrixBase& A, const double* D) = 0;
virtual bool Update(const BlockSparseMatrix& A, const double* D) = 0;
// LinearOperator interface. Since the operator is symmetric,
// LeftMultiply and num_cols are just calls to RightMultiply and
@@ -130,7 +130,7 @@ class SparseMatrixPreconditionerWrapper : public Preconditioner {
virtual ~SparseMatrixPreconditionerWrapper();
// Preconditioner interface
virtual bool Update(const BlockSparseMatrixBase& A, const double* D);
virtual bool Update(const BlockSparseMatrix& A, const double* D);
virtual void RightMultiply(const double* x, double* y) const;
virtual int num_rows() const;
internal/ceres/schur_complement_solver.cc
+1 -1
View File
@@ -58,7 +58,7 @@ namespace ceres {
namespace internal {
LinearSolver::Summary SchurComplementSolver::SolveImpl(
BlockSparseMatrixBase* A,
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) {
internal/ceres/schur_complement_solver.h
+3 -3
View File
@@ -48,7 +48,7 @@
namespace ceres {
namespace internal {
class BlockSparseMatrixBase;
class BlockSparseMatrix;
// Base class for Schur complement based linear least squares
// solvers. It assumes that the input linear system Ax = b can be
@@ -100,7 +100,7 @@ class BlockSparseMatrixBase;
// set to DENSE_SCHUR and SPARSE_SCHUR
// respectively. LinearSolver::Options::elimination_groups[0] should be
// at least 1.
class SchurComplementSolver : public BlockSparseMatrixBaseSolver {
class SchurComplementSolver : public BlockSparseMatrixSolver {
public:
explicit SchurComplementSolver(const LinearSolver::Options& options)
: options_(options) {
@@ -111,7 +111,7 @@ class SchurComplementSolver : public BlockSparseMatrixBaseSolver {
// LinearSolver methods
virtual ~SchurComplementSolver() {}
virtual LinearSolver::Summary SolveImpl(
BlockSparseMatrixBase* A,
BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x);
internal/ceres/schur_eliminator.h
+10 -10
View File
@@ -170,7 +170,7 @@ class SchurEliminatorBase {
// also the caller's responsibilty to ensure that the
// CompressedRowBlockStructure object passed to this method is the
// same one (or is equivalent to) the one associated with the
// BlockSparseMatrixBase objects below.
// BlockSparseMatrix objects below.
virtual void Init(int num_eliminate_blocks,
const CompressedRowBlockStructure* bs) = 0;
@@ -185,7 +185,7 @@ class SchurEliminatorBase {
//
// Since the Schur complement is a symmetric matrix, only the upper
// triangular part of the Schur complement is computed.
virtual void Eliminate(const BlockSparseMatrixBase* A,
virtual void Eliminate(const BlockSparseMatrix* A,
const double* b,
const double* D,
BlockRandomAccessMatrix* lhs,
@@ -194,7 +194,7 @@ class SchurEliminatorBase {
// Given values for the variables z in the F block of A, solve for
// the optimal values of the variables y corresponding to the E
// block in A.
virtual void BackSubstitute(const BlockSparseMatrixBase* A,
virtual void BackSubstitute(const BlockSparseMatrix* A,
const double* b,
const double* D,
const double* z,
@@ -226,12 +226,12 @@ class SchurEliminator : public SchurEliminatorBase {
virtual ~SchurEliminator();
virtual void Init(int num_eliminate_blocks,
const CompressedRowBlockStructure* bs);
virtual void Eliminate(const BlockSparseMatrixBase* A,
virtual void Eliminate(const BlockSparseMatrix* A,
const double* b,
const double* D,
BlockRandomAccessMatrix* lhs,
double* rhs);
virtual void BackSubstitute(const BlockSparseMatrixBase* A,
virtual void BackSubstitute(const BlockSparseMatrix* A,
const double* b,
const double* D,
const double* z,
@@ -273,7 +273,7 @@ class SchurEliminator : public SchurEliminatorBase {
void ChunkDiagonalBlockAndGradient(
const Chunk& chunk,
const BlockSparseMatrixBase* A,
const BlockSparseMatrix* A,
const double* b,
int row_block_counter,
typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix* eet,
@@ -282,7 +282,7 @@ class SchurEliminator : public SchurEliminatorBase {
BlockRandomAccessMatrix* lhs);
void UpdateRhs(const Chunk& chunk,
const BlockSparseMatrixBase* A,
const BlockSparseMatrix* A,
const double* b,
int row_block_counter,
const double* inverse_ete_g,
@@ -293,18 +293,18 @@ class SchurEliminator : public SchurEliminatorBase {
const double* buffer,
const BufferLayoutType& buffer_layout,
BlockRandomAccessMatrix* lhs);
void EBlockRowOuterProduct(const BlockSparseMatrixBase* A,
void EBlockRowOuterProduct(const BlockSparseMatrix* A,
int row_block_index,
BlockRandomAccessMatrix* lhs);
void NoEBlockRowsUpdate(const BlockSparseMatrixBase* A,
void NoEBlockRowsUpdate(const BlockSparseMatrix* A,
const double* b,
int row_block_counter,
BlockRandomAccessMatrix* lhs,
double* rhs);
void NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
void NoEBlockRowOuterProduct(const BlockSparseMatrix* A,
int row_block_index,
BlockRandomAccessMatrix* lhs);
internal/ceres/schur_eliminator_impl.h
+33 -33
View File
@@ -168,7 +168,7 @@ Init(int num_eliminate_blocks, const CompressedRowBlockStructure* bs) {
template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
Eliminate(const BlockSparseMatrixBase* A,
Eliminate(const BlockSparseMatrix* A,
const double* b,
const double* D,
BlockRandomAccessMatrix* lhs,
@@ -299,7 +299,7 @@ Eliminate(const BlockSparseMatrixBase* A,
template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
BackSubstitute(const BlockSparseMatrixBase* A,
BackSubstitute(const BlockSparseMatrix* A,
const double* b,
const double* D,
const double* z,
@@ -324,9 +324,9 @@ BackSubstitute(const BlockSparseMatrixBase* A,
ete.setZero();
}
const double* values = A->values();
for (int j = 0; j < chunk.size; ++j) {
const CompressedRow& row = bs->rows[chunk.start + j];
const double* row_values = A->RowBlockValues(chunk.start + j);
const Cell& e_cell = row.cells.front();
DCHECK_EQ(e_block_id, e_cell.block_id);
@@ -342,20 +342,20 @@ BackSubstitute(const BlockSparseMatrixBase* A,
const int r_block = f_block_id - num_eliminate_blocks_;
MatrixVectorMultiply<kRowBlockSize, kFBlockSize, -1>(
row_values + row.cells[c].position, row.block.size, f_block_size,
values + row.cells[c].position, row.block.size, f_block_size,
z + lhs_row_layout_[r_block],
sj.get());
}
MatrixTransposeVectorMultiply<kRowBlockSize, kEBlockSize, 1>(
row_values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
sj.get(),
y_ptr);
MatrixTransposeMatrixMultiply
<kRowBlockSize, kEBlockSize, kRowBlockSize, kEBlockSize, 1>(
row_values + e_cell.position, row.block.size, e_block_size,
row_values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
ete.data(), 0, 0, e_block_size, e_block_size);
}
@@ -370,7 +370,7 @@ template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
UpdateRhs(const Chunk& chunk,
const BlockSparseMatrixBase* A,
const BlockSparseMatrix* A,
const double* b,
int row_block_counter,
const double* inverse_ete_g,
@@ -380,9 +380,9 @@ UpdateRhs(const Chunk& chunk,
const int e_block_size = bs->cols[e_block_id].size;
int b_pos = bs->rows[row_block_counter].block.position;
const double* values = A->values();
for (int j = 0; j < chunk.size; ++j) {
const CompressedRow& row = bs->rows[row_block_counter + j];
const double *row_values = A->RowBlockValues(row_block_counter + j);
const Cell& e_cell = row.cells.front();
typename EigenTypes<kRowBlockSize>::Vector sj =
@@ -390,7 +390,7 @@ UpdateRhs(const Chunk& chunk,
(b + b_pos, row.block.size);
MatrixVectorMultiply<kRowBlockSize, kEBlockSize, -1>(
row_values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
inverse_ete_g, sj.data());
for (int c = 1; c < row.cells.size(); ++c) {
@@ -399,7 +399,7 @@ UpdateRhs(const Chunk& chunk,
const int block = block_id - num_eliminate_blocks_;
CeresMutexLock l(rhs_locks_[block]);
MatrixTransposeVectorMultiply<kRowBlockSize, kFBlockSize, 1>(
row_values + row.cells[c].position,
values + row.cells[c].position,
row.block.size, block_size,
sj.data(), rhs + lhs_row_layout_[block]);
}
@@ -431,7 +431,7 @@ void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
ChunkDiagonalBlockAndGradient(
const Chunk& chunk,
const BlockSparseMatrixBase* A,
const BlockSparseMatrix* A,
const double* b,
int row_block_counter,
typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix* ete,
@@ -447,9 +447,9 @@ ChunkDiagonalBlockAndGradient(
// contribution of its F blocks to the Schur complement, the
// contribution of its E block to the matrix EE' (ete), and the
// corresponding block in the gradient vector.
const double* values = A->values();
for (int j = 0; j < chunk.size; ++j) {
const CompressedRow& row = bs->rows[row_block_counter + j];
const double *row_values = A->RowBlockValues(row_block_counter + j);
if (row.cells.size() > 1) {
EBlockRowOuterProduct(A, row_block_counter + j, lhs);
@@ -459,13 +459,13 @@ ChunkDiagonalBlockAndGradient(
const Cell& e_cell = row.cells.front();
MatrixTransposeMatrixMultiply
<kRowBlockSize, kEBlockSize, kRowBlockSize, kEBlockSize, 1>(
row_values + e_cell.position, row.block.size, e_block_size,
row_values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
ete->data(), 0, 0, e_block_size, e_block_size);
// g += E_i' b_i
MatrixTransposeVectorMultiply<kRowBlockSize, kEBlockSize, 1>(
row_values + e_cell.position, row.block.size, e_block_size,
values + e_cell.position, row.block.size, e_block_size,
b + b_pos,
g);
@@ -479,8 +479,8 @@ ChunkDiagonalBlockAndGradient(
buffer + FindOrDie(chunk.buffer_layout, f_block_id);
MatrixTransposeMatrixMultiply
<kRowBlockSize, kEBlockSize, kRowBlockSize, kFBlockSize, 1>(
row_values + e_cell.position, row.block.size, e_block_size,
row_values + row.cells[c].position, row.block.size, f_block_size,
values + e_cell.position, row.block.size, e_block_size,
values + row.cells[c].position, row.block.size, f_block_size,
buffer_ptr, 0, 0, e_block_size, f_block_size);
}
b_pos += row.block.size;
@@ -551,21 +551,21 @@ ChunkOuterProduct(const CompressedRowBlockStructure* bs,
template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
NoEBlockRowsUpdate(const BlockSparseMatrixBase* A,
NoEBlockRowsUpdate(const BlockSparseMatrix* A,
const double* b,
int row_block_counter,
BlockRandomAccessMatrix* lhs,
double* rhs) {
const CompressedRowBlockStructure* bs = A->block_structure();
const double* values = A->values();
for (; row_block_counter < bs->rows.size(); ++row_block_counter) {
const CompressedRow& row = bs->rows[row_block_counter];
const double *row_values = A->RowBlockValues(row_block_counter);
for (int c = 0; c < row.cells.size(); ++c) {
const int block_id = row.cells[c].block_id;
const int block_size = bs->cols[block_id].size;
const int block = block_id - num_eliminate_blocks_;
MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + row.cells[c].position, row.block.size, block_size,
values + row.cells[c].position, row.block.size, block_size,
b + row.block.position,
rhs + lhs_row_layout_[block]);
}
@@ -591,12 +591,12 @@ NoEBlockRowsUpdate(const BlockSparseMatrixBase* A,
template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
NoEBlockRowOuterProduct(const BlockSparseMatrix* A,
int row_block_index,
BlockRandomAccessMatrix* lhs) {
const CompressedRowBlockStructure* bs = A->block_structure();
const CompressedRow& row = bs->rows[row_block_index];
const double *row_values = A->RowBlockValues(row_block_index);
const double* values = A->values();
for (int i = 0; i < row.cells.size(); ++i) {
const int block1 = row.cells[i].block_id - num_eliminate_blocks_;
DCHECK_GE(block1, 0);
@@ -612,8 +612,8 @@ NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
// symmetric outer product.
MatrixTransposeMatrixMultiply
<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + row.cells[i].position, row.block.size, block1_size,
row_values + row.cells[i].position, row.block.size, block1_size,
values + row.cells[i].position, row.block.size, block1_size,
values + row.cells[i].position, row.block.size, block1_size,
cell_info->values, r, c, row_stride, col_stride);
}
@@ -630,8 +630,8 @@ NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
CeresMutexLock l(&cell_info->m);
MatrixTransposeMatrixMultiply
<Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, Eigen::Dynamic, 1>(
row_values + row.cells[i].position, row.block.size, block1_size,
row_values + row.cells[j].position, row.block.size, block2_size,
values + row.cells[i].position, row.block.size, block1_size,
values + row.cells[j].position, row.block.size, block2_size,
cell_info->values, r, c, row_stride, col_stride);
}
}
@@ -644,12 +644,12 @@ NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
template <int kRowBlockSize, int kEBlockSize, int kFBlockSize>
void
SchurEliminator<kRowBlockSize, kEBlockSize, kFBlockSize>::
EBlockRowOuterProduct(const BlockSparseMatrixBase* A,
EBlockRowOuterProduct(const BlockSparseMatrix* A,
int row_block_index,
BlockRandomAccessMatrix* lhs) {
const CompressedRowBlockStructure* bs = A->block_structure();
const CompressedRow& row = bs->rows[row_block_index];
const double *row_values = A->RowBlockValues(row_block_index);
const double* values = A->values();
for (int i = 1; i < row.cells.size(); ++i) {
const int block1 = row.cells[i].block_id - num_eliminate_blocks_;
DCHECK_GE(block1, 0);
@@ -664,8 +664,8 @@ EBlockRowOuterProduct(const BlockSparseMatrixBase* A,
// block += b1.transpose() * b1;
MatrixTransposeMatrixMultiply
<kRowBlockSize, kFBlockSize, kRowBlockSize, kFBlockSize, 1>(
row_values + row.cells[i].position, row.block.size, block1_size,
row_values + row.cells[i].position, row.block.size, block1_size,
values + row.cells[i].position, row.block.size, block1_size,
values + row.cells[i].position, row.block.size, block1_size,
cell_info->values, r, c, row_stride, col_stride);
}
@@ -683,8 +683,8 @@ EBlockRowOuterProduct(const BlockSparseMatrixBase* A,
CeresMutexLock l(&cell_info->m);
MatrixTransposeMatrixMultiply
<kRowBlockSize, kFBlockSize, kRowBlockSize, kFBlockSize, 1>(
row_values + row.cells[i].position, row.block.size, block1_size,
row_values + row.cells[j].position, row.block.size, block2_size,
values + row.cells[i].position, row.block.size, block1_size,
values + row.cells[j].position, row.block.size, block2_size,
cell_info->values, r, c, row_stride, col_stride);
}
}
internal/ceres/schur_jacobi_preconditioner.cc
+1 -1
View File
@@ -91,7 +91,7 @@ void SchurJacobiPreconditioner::InitEliminator(
}
// Update the values of the preconditioner matrix and factorize it.
bool SchurJacobiPreconditioner::Update(const BlockSparseMatrixBase& A,
bool SchurJacobiPreconditioner::Update(const BlockSparseMatrix& A,
const double* D) {
const int num_rows = m_->num_rows();
CHECK_GT(num_rows, 0);
internal/ceres/schur_jacobi_preconditioner.h
+2 -2
View File
@@ -50,7 +50,7 @@ namespace ceres {
namespace internal {
class BlockRandomAccessSparseMatrix;
class BlockSparseMatrixBase;
class BlockSparseMatrix;
struct CompressedRowBlockStructure;
class SchurEliminatorBase;
@@ -86,7 +86,7 @@ class SchurJacobiPreconditioner : public Preconditioner {
virtual ~SchurJacobiPreconditioner();
// Preconditioner interface.
virtual bool Update(const BlockSparseMatrixBase& A, const double* D);
virtual bool Update(const BlockSparseMatrix& A, const double* D);
virtual void RightMultiply(const double* x, double* y) const;
virtual int num_rows() const;
internal/ceres/visibility_based_preconditioner.cc
+1 -1
View File
@@ -324,7 +324,7 @@ void VisibilityBasedPreconditioner::InitEliminator(
}
// Update the values of the preconditioner matrix and factorize it.
bool VisibilityBasedPreconditioner::Update(const BlockSparseMatrixBase& A,
bool VisibilityBasedPreconditioner::Update(const BlockSparseMatrix& A,
const double* D) {
const time_t start_time = time(NULL);
const int num_rows = m_->num_rows();
internal/ceres/visibility_based_preconditioner.h
+3 -3
View File
@@ -62,7 +62,7 @@ namespace ceres {
namespace internal {
class BlockRandomAccessSparseMatrix;
class BlockSparseMatrixBase;
class BlockSparseMatrix;
struct CompressedRowBlockStructure;
class SchurEliminatorBase;
@@ -136,7 +136,7 @@ class VisibilityBasedPreconditioner : public Preconditioner {
virtual ~VisibilityBasedPreconditioner();
// Preconditioner interface
virtual bool Update(const BlockSparseMatrixBase& A, const double* D);
virtual bool Update(const BlockSparseMatrix& A, const double* D);
virtual void RightMultiply(const double* x, double* y) const;
virtual int num_rows() const;
@@ -215,7 +215,7 @@ class VisibilityBasedPreconditioner : public Preconditioner {
virtual void LeftMultiply(const double* x, double* y) const {}
virtual int num_rows() const { return -1; }
virtual int num_cols() const { return -1; }
bool Update(const BlockSparseMatrixBase& A, const double* D) {
bool Update(const BlockSparseMatrix& A, const double* D) {
return false;
}
};