// 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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// Author: sameeragarwal@google.com (Sameer Agarwal)
//
// Interface definition for sparse matrices.

#ifndef CERES_INTERNAL_SPARSE_MATRIX_H_
#define CERES_INTERNAL_SPARSE_MATRIX_H_

#include <cstdio>
#include "ceres/linear_operator.h"
#include "ceres/internal/eigen.h"
#include "ceres/types.h"

namespace ceres {
namespace internal {

class SparseMatrixProto;

// This class defines the interface for storing and manipulating
// sparse matrices. The key property that differentiates different
// sparse matrices is how they are organized in memory and how the
// information about the sparsity structure of the matrix is
// stored. This has significant implications for linear solvers
// operating on these matrices.
//
// To deal with the different kinds of layouts, we will assume that a
// sparse matrix will have a two part representation. A values array
// that will be used to store the entries of the sparse matrix and
// some sort of a layout object that tells the user the sparsity
// structure and layout of the values array. For example in case of
// the TripletSparseMatrix, this information is carried in the rows
// and cols arrays and for the BlockSparseMatrix, this information is
// carried in the CompressedRowBlockStructure object.
//
// This interface deliberately does not contain any information about
// the structure of the sparse matrix as that seems to be highly
// matrix type dependent and we are at this stage unable to come up
// with an efficient high level interface that spans multiple sparse
// matrix types.
class SparseMatrix : public LinearOperator {
 public:
  virtual ~SparseMatrix();

  // y += Ax;
  virtual void RightMultiply(const double* x, double* y) const = 0;
  // y += A'x;
  virtual void LeftMultiply(const double* x, double* y) const = 0;

  // In MATLAB notation sum(A.*A, 1)
  virtual void SquaredColumnNorm(double* x) const = 0;
  // A = A * diag(scale)
  virtual void ScaleColumns(const double* scale) = 0;

  // A = 0. A->num_nonzeros() == 0 is true after this call. The
  // sparsity pattern is preserved.
  virtual void SetZero() = 0;

  // Resize and populate dense_matrix with a dense version of the
  // sparse matrix.
  virtual void ToDenseMatrix(Matrix* dense_matrix) const = 0;

#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
  // Dump the sparse matrix to a proto. Destroys the contents of proto.
  virtual void ToProto(SparseMatrixProto* proto) const = 0;
#endif

  // Write out the matrix as a sequence of (i,j,s) triplets. This
  // format is useful for loading the matrix into MATLAB/octave as a
  // sparse matrix.
  virtual void ToTextFile(FILE* file) const = 0;

  // Accessors for the values array that stores the entries of the
  // sparse matrix. The exact interpreptation of the values of this
  // array depends on the particular kind of SparseMatrix being
  // accessed.
  virtual double* mutable_values() = 0;
  virtual const double* values() const = 0;

  virtual int num_rows() const = 0;
  virtual int num_cols() const = 0;
  virtual int num_nonzeros() const = 0;
};

}  // namespace internal
}  // namespace ceres

#endif  // CERES_INTERNAL_SPARSE_MATRIX_H_