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29 // Author: sameeragarwal@google.com (Sameer Agarwal)
30 //
31 // Implementation of the SparseMatrix interface for block sparse
32 // matrices.
33 
34 #ifndef CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_
35 #define CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_
36 
37 #include <memory>
38 #include "ceres/block_structure.h"
39 #include "ceres/sparse_matrix.h"
40 #include "ceres/internal/eigen.h"
41 
42 namespace ceres {
43 namespace internal {
44 
45 class TripletSparseMatrix;
46 
47 // This class implements the SparseMatrix interface for storing and
48 // manipulating block sparse matrices. The block structure is stored
49 // in the CompressedRowBlockStructure object and one is needed to
50 // initialize the matrix. For details on how the blocks structure of
51 // the matrix is stored please see the documentation
52 //
53 //   internal/ceres/block_structure.h
54 //
55 class BlockSparseMatrix : public SparseMatrix {
56  public:
57   // Construct a block sparse matrix with a fully initialized
58   // CompressedRowBlockStructure objected. The matrix takes over
59   // ownership of this object and destroys it upon destruction.
60   //
61   // TODO(sameeragarwal): Add a function which will validate legal
62   // CompressedRowBlockStructure objects.
63   explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure);
64 
65   BlockSparseMatrix();
66   BlockSparseMatrix(const BlockSparseMatrix&) = delete;
67   void operator=(const BlockSparseMatrix&) = delete;
68 
69   virtual ~BlockSparseMatrix();
70 
71   // Implementation of SparseMatrix interface.
72   void SetZero() final;
73   void RightMultiply(const double* x, double* y) const final;
74   void LeftMultiply(const double* x, double* y) const final;
75   void SquaredColumnNorm(double* x) const final;
76   void ScaleColumns(const double* scale) final;
77   void ToDenseMatrix(Matrix* dense_matrix) const final;
78   void ToTextFile(FILE* file) const final;
79 
num_rows()80   int num_rows()         const final { return num_rows_;     }
num_cols()81   int num_cols()         const final { return num_cols_;     }
num_nonzeros()82   int num_nonzeros()     const final { return num_nonzeros_; }
values()83   const double* values() const final { return values_.get(); }
mutable_values()84   double* mutable_values()     final { return values_.get(); }
85 
86   void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const;
87   const CompressedRowBlockStructure* block_structure() const;
88 
89   // Append the contents of m to the bottom of this matrix. m must
90   // have the same column blocks structure as this matrix.
91   void AppendRows(const BlockSparseMatrix& m);
92 
93   // Delete the bottom delta_rows_blocks.
94   void DeleteRowBlocks(int delta_row_blocks);
95 
96   static BlockSparseMatrix* CreateDiagonalMatrix(
97       const double* diagonal,
98       const std::vector<Block>& column_blocks);
99 
100   struct RandomMatrixOptions {
101     int num_row_blocks = 0;
102     int min_row_block_size = 0;
103     int max_row_block_size = 0;
104     int num_col_blocks = 0;
105     int min_col_block_size = 0;
106     int max_col_block_size = 0;
107 
108     // 0 < block_density <= 1 is the probability of a block being
109     // present in the matrix. A given random matrix will not have
110     // precisely this density.
111     double block_density = 0.0;
112 
113     // If col_blocks is non-empty, then the generated random matrix
114     // has this block structure and the column related options in this
115     // struct are ignored.
116     std::vector<Block> col_blocks;
117   };
118 
119   // Create a random BlockSparseMatrix whose entries are normally
120   // distributed and whose structure is determined by
121   // RandomMatrixOptions.
122   //
123   // Caller owns the result.
124   static BlockSparseMatrix* CreateRandomMatrix(
125       const RandomMatrixOptions& options);
126 
127  private:
128   int num_rows_;
129   int num_cols_;
130   int num_nonzeros_;
131   int max_num_nonzeros_;
132   std::unique_ptr<double[]> values_;
133   std::unique_ptr<CompressedRowBlockStructure> block_structure_;
134 };
135 
136 // A number of algorithms like the SchurEliminator do not need
137 // access to the full BlockSparseMatrix interface. They only
138 // need read only access to the values array and the block structure.
139 //
140 // BlockSparseDataMatrix a struct that carries these two bits of
141 // information
142 class BlockSparseMatrixData {
143  public:
BlockSparseMatrixData(const BlockSparseMatrix & m)144   BlockSparseMatrixData(const BlockSparseMatrix& m)
145       : block_structure_(m.block_structure()), values_(m.values()){};
146 
BlockSparseMatrixData(const CompressedRowBlockStructure * block_structure,const double * values)147   BlockSparseMatrixData(const CompressedRowBlockStructure* block_structure,
148                         const double* values)
149       : block_structure_(block_structure), values_(values) {}
150 
block_structure()151   const CompressedRowBlockStructure* block_structure() const {
152     return block_structure_;
153   }
values()154   const double* values() const { return values_; }
155 
156  private:
157   const CompressedRowBlockStructure* block_structure_;
158   const double* values_;
159 };
160 
161 }  // namespace internal
162 }  // namespace ceres
163 
164 #endif  // CERES_INTERNAL_BLOCK_SPARSE_MATRIX_H_
165