| // Ceres Solver - A fast non-linear least squares minimizer | 
 | // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. | 
 | // http://code.google.com/p/ceres-solver/ | 
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 | // | 
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 | // | 
 | // Author: sameeragarwal@google.com (Sameer Agarwal) | 
 |  | 
 | #ifndef CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ | 
 | #define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ | 
 |  | 
 | #include <vector> | 
 |  | 
 | #include "ceres/internal/eigen.h" | 
 | #include "ceres/internal/macros.h" | 
 | #include "ceres/internal/port.h" | 
 | #include "ceres/sparse_matrix.h" | 
 | #include "ceres/triplet_sparse_matrix.h" | 
 | #include "ceres/types.h" | 
 | #include "glog/logging.h" | 
 |  | 
 | namespace ceres { | 
 |  | 
 | struct CRSMatrix; | 
 |  | 
 | namespace internal { | 
 |  | 
 | class SparseMatrixProto; | 
 |  | 
 | class CompressedRowSparseMatrix : public SparseMatrix { | 
 |  public: | 
 |   // Build a matrix with the same content as the TripletSparseMatrix | 
 |   // m. TripletSparseMatrix objects are easier to construct | 
 |   // incrementally, so we use them to initialize SparseMatrix | 
 |   // objects. | 
 |   // | 
 |   // We assume that m does not have any repeated entries. | 
 |   explicit CompressedRowSparseMatrix(const TripletSparseMatrix& m); | 
 | #ifndef CERES_NO_PROTOCOL_BUFFERS | 
 |   explicit CompressedRowSparseMatrix(const SparseMatrixProto& proto); | 
 | #endif | 
 |  | 
 |   // Use this constructor only if you know what you are doing. This | 
 |   // creates a "blank" matrix with the appropriate amount of memory | 
 |   // allocated. However, the object itself is in an inconsistent state | 
 |   // as the rows and cols matrices do not match the values of | 
 |   // num_rows, num_cols and max_num_nonzeros. | 
 |   // | 
 |   // The use case for this constructor is that when the user knows the | 
 |   // size of the matrix to begin with and wants to update the layout | 
 |   // manually, instead of going via the indirect route of first | 
 |   // constructing a TripletSparseMatrix, which leads to more than | 
 |   // double the peak memory usage. | 
 |   CompressedRowSparseMatrix(int num_rows, | 
 |                             int num_cols, | 
 |                             int max_num_nonzeros); | 
 |  | 
 |   // Build a square sparse diagonal matrix with num_rows rows and | 
 |   // columns. The diagonal m(i,i) = diagonal(i); | 
 |   CompressedRowSparseMatrix(const double* diagonal, int num_rows); | 
 |  | 
 |   virtual ~CompressedRowSparseMatrix(); | 
 |  | 
 |   // 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; | 
 | #ifndef CERES_NO_PROTOCOL_BUFFERS | 
 |   virtual void ToProto(SparseMatrixProto* proto) const; | 
 | #endif | 
 |   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 rows_[num_rows_]; } | 
 |   virtual const double* values() const { return values_.get(); } | 
 |   virtual double* mutable_values() { return values_.get(); } | 
 |  | 
 |   // Delete the bottom delta_rows. | 
 |   // num_rows -= delta_rows | 
 |   void DeleteRows(int delta_rows); | 
 |  | 
 |   // Append the contents of m to the bottom of this matrix. m must | 
 |   // have the same number of columns as this matrix. | 
 |   void AppendRows(const CompressedRowSparseMatrix& m); | 
 |  | 
 |   void ToCRSMatrix(CRSMatrix* matrix) const; | 
 |  | 
 |   // Low level access methods that expose the structure of the matrix. | 
 |   const int* cols() const { return cols_.get(); } | 
 |   int* mutable_cols() { return cols_.get(); } | 
 |  | 
 |   const int* rows() const { return rows_.get(); } | 
 |   int* mutable_rows() { return rows_.get(); } | 
 |  | 
 |   const vector<int>& row_blocks() const { return row_blocks_; } | 
 |   vector<int>* mutable_row_blocks() { return &row_blocks_; } | 
 |  | 
 |   const vector<int>& col_blocks() const { return col_blocks_; } | 
 |   vector<int>* mutable_col_blocks() { return &col_blocks_; } | 
 |  | 
 |  private: | 
 |   scoped_array<int> cols_; | 
 |   scoped_array<int> rows_; | 
 |   scoped_array<double> values_; | 
 |  | 
 |   int num_rows_; | 
 |   int num_cols_; | 
 |   int max_num_nonzeros_; | 
 |  | 
 |   // If the matrix has an underlying block structure, then it can also | 
 |   // carry with it row and column block sizes. This is auxilliary and | 
 |   // optional information for use by algorithms operating on the | 
 |   // matrix. The class itself does not make use of this information in | 
 |   // any way. | 
 |   vector<int> row_blocks_; | 
 |   vector<int> col_blocks_; | 
 |  | 
 |   CERES_DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix); | 
 | }; | 
 |  | 
 | }  // namespace internal | 
 | }  // namespace ceres | 
 |  | 
 | #endif  // CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_ |