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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_COMPRESSED_ROW_SPARSE_MATRIX_H_
#define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
#include <vector>
#include "ceres/internal/macros.h"
#include "ceres/internal/port.h"
#include "ceres/sparse_matrix.h"
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres {
struct CRSMatrix;
namespace internal {
class TripletSparseMatrix;
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);
// 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;
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_[0]; }
virtual double* mutable_values() { return &values_[0]; }
// 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_[0]; }
int* mutable_cols() { return &cols_[0]; }
const int* rows() const { return &rows_[0]; }
int* mutable_rows() { return &rows_[0]; }
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_; }
// Non-destructive array resizing method.
void set_num_rows(const int num_rows) { num_rows_ = num_rows; }
void set_num_cols(const int num_cols) { num_cols_ = num_cols; }
void SolveLowerTriangularInPlace(double* solution) const;
void SolveLowerTriangularTransposeInPlace(double* solution) const;
CompressedRowSparseMatrix* Transpose() const;
static CompressedRowSparseMatrix* CreateBlockDiagonalMatrix(
const double* diagonal,
const vector<int>& blocks);
private:
int num_rows_;
int num_cols_;
vector<int> rows_;
vector<int> cols_;
vector<double> values_;
// 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_
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