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// 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__
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