Files
ceres-solver/internal/ceres/block_sparse_matrix.h
Sameer Agarwal 9d02b76dce An implementation of SubsetPreconditioner.
The key idea being, use some subset of the rows of the Jacobian
as the preconditioner.

This CL only implements the preconditioner assuming that the row
selection has already been done. How the rows are selected will be
left to the user based on their knowledge of the problem.

A follow up CL will hook this preconditioner into the rest of the
solver.

Change-Id: I3e18dc57811116534e9ddf35d7b154bcce496d3b
2018-02-21 13:58:45 -08:00

149 lines
5.5 KiB
C++

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
//
// Implementation of the SparseMatrix interface for block sparse
// matrices.
#ifndef CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_
#define CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_
#include "ceres/block_structure.h"
#include "ceres/sparse_matrix.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/macros.h"
#include "ceres/internal/scoped_ptr.h"
namespace ceres {
namespace internal {
class TripletSparseMatrix;
// 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
// initialize the matrix. For details on how the blocks structure of
// the matrix is stored please see the documentation
//
// internal/ceres/block_structure.h
//
class BlockSparseMatrix : public SparseMatrix {
public:
// Construct a block sparse matrix with a fully initialized
// CompressedRowBlockStructure objected. The matrix takes over
// ownership of this object and destroys it upon destruction.
//
// TODO(sameeragarwal): Add a function which will validate legal
// CompressedRowBlockStructure objects.
explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure);
BlockSparseMatrix();
virtual ~BlockSparseMatrix();
// Implementation of SparseMatrix interface.
virtual void SetZero();
virtual void RightMultiply(const double* x, double* y) const;
virtual void LeftMultiply(const double* x, double* y) const;
virtual void SquaredColumnNorm(double* x) const;
virtual void ScaleColumns(const double* scale);
virtual void ToDenseMatrix(Matrix* dense_matrix) const;
virtual void ToTextFile(FILE* file) const;
virtual int num_rows() const { return num_rows_; }
virtual int num_cols() const { return num_cols_; }
virtual int num_nonzeros() const { return num_nonzeros_; }
virtual const double* values() const { return values_.get(); }
virtual double* mutable_values() { return values_.get(); }
void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const;
const CompressedRowBlockStructure* block_structure() const;
// Append the contents of m to the bottom of this matrix. m must
// have the same column blocks structure as this matrix.
void AppendRows(const BlockSparseMatrix& m);
// Delete the bottom delta_rows_blocks.
void DeleteRowBlocks(int delta_row_blocks);
static BlockSparseMatrix* CreateDiagonalMatrix(
const double* diagonal,
const std::vector<Block>& column_blocks);
struct RandomMatrixOptions {
RandomMatrixOptions()
: num_row_blocks(0),
min_row_block_size(0),
max_row_block_size(0),
num_col_blocks(0),
min_col_block_size(0),
max_col_block_size(0),
block_density(0.0) {
}
int num_row_blocks;
int min_row_block_size;
int max_row_block_size;
int num_col_blocks;
int min_col_block_size;
int max_col_block_size;
// 0 < block_density <= 1 is the probability of a block being
// present in the matrix. A given random matrix will not have
// precisely this density.
double block_density;
// If col_blocks is non-empty, then the generated random matrix
// has this block structure and the column related options in this
// struct are ignored.
std::vector<Block> col_blocks;
};
// Create a random BlockSparseMatrix whose entries are normally
// distributed and whose structure is determined by
// RandomMatrixOptions.
//
// Caller owns the result.
static BlockSparseMatrix* CreateRandomMatrix(
const RandomMatrixOptions& options);
private:
int num_rows_;
int num_cols_;
int num_nonzeros_;
int max_num_nonzeros_;
scoped_array<double> values_;
scoped_ptr<CompressedRowBlockStructure> block_structure_;
CERES_DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrix);
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_