// 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/ // // 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) #ifndef CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H_ #define CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H_ #include "ceres/sparse_matrix.h" #include "ceres/internal/eigen.h" #include "ceres/internal/scoped_ptr.h" #include "ceres/types.h" namespace ceres { namespace internal { // An implementation of the SparseMatrix interface to store and // manipulate sparse matrices in triplet (i,j,s) form. This object is // inspired by the design of the cholmod_triplet struct used in the // SuiteSparse package and is memory layout compatible with it. class TripletSparseMatrix : public SparseMatrix { public: TripletSparseMatrix(); TripletSparseMatrix(int num_rows, int num_cols, int max_num_nonzeros); explicit TripletSparseMatrix(const TripletSparseMatrix& orig); TripletSparseMatrix& operator=(const TripletSparseMatrix& rhs); ~TripletSparseMatrix(); // Implementation of the 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(); } virtual void set_num_nonzeros(int num_nonzeros); // Increase max_num_nonzeros and correspondingly increase the size // of rows_, cols_ and values_. If new_max_num_nonzeros is smaller // than max_num_nonzeros_, then num_non_zeros should be less than or // equal to new_max_num_nonzeros, otherwise data loss is possible // and the method crashes. void Reserve(int new_max_num_nonzeros); // Append the matrix B at the bottom of this matrix. B should have // the same number of columns as num_cols_. void AppendRows(const TripletSparseMatrix& B); // Append the matrix B at the right of this matrix. B should have // the same number of rows as num_rows_; void AppendCols(const TripletSparseMatrix& B); // Resize the matrix. Entries which fall outside the new matrix // bounds are dropped and the num_non_zeros changed accordingly. void Resize(int new_num_rows, int new_num_cols); int max_num_nonzeros() const { return max_num_nonzeros_; } const int* rows() const { return rows_.get(); } const int* cols() const { return cols_.get(); } int* mutable_rows() { return rows_.get(); } int* mutable_cols() { return cols_.get(); } // Returns true if the entries of the matrix obey the row, column, // and column size bounds and false otherwise. bool AllTripletsWithinBounds() const; bool IsValid() const { return AllTripletsWithinBounds(); } // Build a sparse diagonal matrix of size num_rows x num_rows from // the array values. Entries of the values array are copied into the // sparse matrix. static TripletSparseMatrix* CreateSparseDiagonalMatrix(const double* values, int num_rows); private: void AllocateMemory(); void CopyData(const TripletSparseMatrix& orig); int num_rows_; int num_cols_; int max_num_nonzeros_; int num_nonzeros_; // The data is stored as three arrays. For each i, values_[i] is // stored at the location (rows_[i], cols_[i]). If the there are // multiple entries with the same (rows_[i], cols_[i]), the values_ // entries corresponding to them are summed up. scoped_array<int> rows_; scoped_array<int> cols_; scoped_array<double> values_; }; } // namespace internal } // namespace ceres #endif // CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H__