1// Ceres Solver - A fast non-linear least squares minimizer
2// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
3// http://code.google.com/p/ceres-solver/
4//
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28//
29// Author: sameeragarwal@google.com (Sameer Agarwal)
30//
31// Interface definition for sparse matrices.
32
33#ifndef CERES_INTERNAL_SPARSE_MATRIX_H_
34#define CERES_INTERNAL_SPARSE_MATRIX_H_
35
36#include <cstdio>
37#include "ceres/linear_operator.h"
38#include "ceres/internal/eigen.h"
39#include "ceres/types.h"
40
41namespace ceres {
42namespace internal {
43
44// This class defines the interface for storing and manipulating
45// sparse matrices. The key property that differentiates different
46// sparse matrices is how they are organized in memory and how the
47// information about the sparsity structure of the matrix is
48// stored. This has significant implications for linear solvers
49// operating on these matrices.
50//
51// To deal with the different kinds of layouts, we will assume that a
52// sparse matrix will have a two part representation. A values array
53// that will be used to store the entries of the sparse matrix and
54// some sort of a layout object that tells the user the sparsity
55// structure and layout of the values array. For example in case of
56// the TripletSparseMatrix, this information is carried in the rows
57// and cols arrays and for the BlockSparseMatrix, this information is
58// carried in the CompressedRowBlockStructure object.
59//
60// This interface deliberately does not contain any information about
61// the structure of the sparse matrix as that seems to be highly
62// matrix type dependent and we are at this stage unable to come up
63// with an efficient high level interface that spans multiple sparse
64// matrix types.
65class SparseMatrix : public LinearOperator {
66 public:
67  virtual ~SparseMatrix();
68
69  // y += Ax;
70  virtual void RightMultiply(const double* x, double* y) const = 0;
71  // y += A'x;
72  virtual void LeftMultiply(const double* x, double* y) const = 0;
73
74  // In MATLAB notation sum(A.*A, 1)
75  virtual void SquaredColumnNorm(double* x) const = 0;
76  // A = A * diag(scale)
77  virtual void ScaleColumns(const double* scale) = 0;
78
79  // A = 0. A->num_nonzeros() == 0 is true after this call. The
80  // sparsity pattern is preserved.
81  virtual void SetZero() = 0;
82
83  // Resize and populate dense_matrix with a dense version of the
84  // sparse matrix.
85  virtual void ToDenseMatrix(Matrix* dense_matrix) const = 0;
86
87  // Write out the matrix as a sequence of (i,j,s) triplets. This
88  // format is useful for loading the matrix into MATLAB/octave as a
89  // sparse matrix.
90  virtual void ToTextFile(FILE* file) const = 0;
91
92  // Accessors for the values array that stores the entries of the
93  // sparse matrix. The exact interpreptation of the values of this
94  // array depends on the particular kind of SparseMatrix being
95  // accessed.
96  virtual double* mutable_values() = 0;
97  virtual const double* values() const = 0;
98
99  virtual int num_rows() const = 0;
100  virtual int num_cols() const = 0;
101  virtual int num_nonzeros() const = 0;
102};
103
104}  // namespace internal
105}  // namespace ceres
106
107#endif  // CERES_INTERNAL_SPARSE_MATRIX_H_
108