1 // Ceres Solver - A fast non-linear least squares minimizer
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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 
38 #include "ceres/internal/eigen.h"
39 #include "ceres/internal/port.h"
40 #include "ceres/linear_operator.h"
41 #include "ceres/types.h"
42 
43 namespace ceres {
44 namespace internal {
45 
46 // This class defines the interface for storing and manipulating
47 // sparse matrices. The key property that differentiates different
48 // sparse matrices is how they are organized in memory and how the
49 // information about the sparsity structure of the matrix is
50 // stored. This has significant implications for linear solvers
51 // operating on these matrices.
52 //
53 // To deal with the different kinds of layouts, we will assume that a
54 // sparse matrix will have a two part representation. A values array
55 // that will be used to store the entries of the sparse matrix and
56 // some sort of a layout object that tells the user the sparsity
57 // structure and layout of the values array. For example in case of
58 // the TripletSparseMatrix, this information is carried in the rows
59 // and cols arrays and for the BlockSparseMatrix, this information is
60 // carried in the CompressedRowBlockStructure object.
61 //
62 // This interface deliberately does not contain any information about
63 // the structure of the sparse matrix as that seems to be highly
64 // matrix type dependent and we are at this stage unable to come up
65 // with an efficient high level interface that spans multiple sparse
66 // matrix types.
67 class CERES_EXPORT_INTERNAL SparseMatrix : public LinearOperator {
68  public:
69   virtual ~SparseMatrix();
70 
71   // y += Ax;
72   virtual void RightMultiply(const double* x, double* y) const = 0;
73   // y += A'x;
74   virtual void LeftMultiply(const double* x, double* y) const = 0;
75 
76   // In MATLAB notation sum(A.*A, 1)
77   virtual void SquaredColumnNorm(double* x) const = 0;
78   // A = A * diag(scale)
79   virtual void ScaleColumns(const double* scale) = 0;
80 
81   // A = 0. A->num_nonzeros() == 0 is true after this call. The
82   // sparsity pattern is preserved.
83   virtual void SetZero() = 0;
84 
85   // Resize and populate dense_matrix with a dense version of the
86   // sparse matrix.
87   virtual void ToDenseMatrix(Matrix* dense_matrix) const = 0;
88 
89   // Write out the matrix as a sequence of (i,j,s) triplets. This
90   // format is useful for loading the matrix into MATLAB/octave as a
91   // sparse matrix.
92   virtual void ToTextFile(FILE* file) const = 0;
93 
94   // Accessors for the values array that stores the entries of the
95   // sparse matrix. The exact interpretation of the values of this
96   // array depends on the particular kind of SparseMatrix being
97   // accessed.
98   virtual double* mutable_values() = 0;
99   virtual const double* values() const = 0;
100 
101   virtual int num_rows() const = 0;
102   virtual int num_cols() const = 0;
103   virtual int num_nonzeros() const = 0;
104 };
105 
106 }  // namespace internal
107 }  // namespace ceres
108 
109 #endif  // CERES_INTERNAL_SPARSE_MATRIX_H_
110