/*!
 * \file
 * \brief Definition of a class for algebra on GF(2) (binary) matrices
 * \author Erik G. Larsson and Adam Piatyszek
 *
 * -------------------------------------------------------------------------
 *
 * Copyright (C) 1995-2010  (see AUTHORS file for a list of contributors)
 *
 * This file is part of IT++ - a C++ library of mathematical, signal
 * processing, speech processing, and communications classes and functions.
 *
 * IT++ is free software: you can redistribute it and/or modify it under the
 * terms of the GNU General Public License as published by the Free Software
 * Foundation, either version 3 of the License, or (at your option) any
 * later version.
 *
 * IT++ is distributed in the hope that it will be useful, but WITHOUT ANY
 * WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 * FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
 * details.
 *
 * You should have received a copy of the GNU General Public License along
 * with IT++.  If not, see <http://www.gnu.org/licenses/>.
 *
 * -------------------------------------------------------------------------
 *
 * Two representations are offered: GF2mat_sparse for sparse GF(2)
 * matrices and GF2mat for dense GF(2) matrices. Conversions between
 * dense and sparse GF(2) are also possible.
 *
 * Binary vectors are represented either via the bvec class (memory
 * typically is not an issue here) or as n*1 (or 1*n) GF(2) matrix.
 *
 * Note that the \c bmat class also provides some functionality for
 * matrix algebra over GF(2) but this class is based on \c Mat<> which
 * has a fundamentally different addressing mechanism and which is
 * much less memory efficient (\c Mat<> uses one byte memory minimum
 * per element).
 */

#ifndef GF2MAT_H
#define GF2MAT_H

#include <itpp/base/vec.h>
#include <itpp/base/mat.h>
#include <itpp/base/svec.h>
#include <itpp/base/smat.h>
#include <itpp/base/itfile.h>


namespace itpp
{

// ----------------------------------------------------------------------
// Sparse GF(2) matrix class
// ----------------------------------------------------------------------

//! Sparse GF(2) vector
typedef Sparse_Vec<bin> GF2vec_sparse;

//! Sparse GF(2) matrix
typedef Sparse_Mat<bin> GF2mat_sparse;


// ----------------------------------------------------------------------
// Alist parameterization of sparse GF(2) matrix class
// ----------------------------------------------------------------------

/*!
  \relatesalso GF2mat_sparse
  \brief Parameterized "alist" representation of sparse GF(2) matrix
  \author Adam Piatyszek and Erik G. Larsson

  This class is used to provide a parameterized representation of a \c
  GF2mat_sparse class. The format is compatible with the "alist" format
  defined by David MacKay, Matthew Davey and John Lafferty:
  - http://www.inference.phy.cam.ac.uk/mackay/codes/alist.html

  For examples of "alist" representation visit David MacKay's Encyclopedia
  of Sparse Graph Codes:
  - http://www.inference.phy.cam.ac.uk/mackay/codes/data.html
*/
class GF2mat_sparse_alist
{
public:
  //! Default constructor
  GF2mat_sparse_alist() : data_ok(false) {}
  //! Constructor, which reads alist data from a file named \c fname
  GF2mat_sparse_alist(const std::string &fname);

  //! Read alist data from a file named \c fname
  void read(const std::string &fname);
  //! Write alist data to a file named \c fname
  void write(const std::string &fname) const;

  /*!
    \brief Convert "alist" representation to \c GF2mat_sparse

    \param transpose Indicates whether a matrix should be transposed
    during the conversion process
  */
  GF2mat_sparse to_sparse(bool transpose = false) const;

  /*!
    \brief Import "alist" representation from \c GF2mat_sparse

    \param mat Matrix to import
    \param transpose Indicates whether a matrix should be transposed
    during the conversion process
  */
  void from_sparse(const GF2mat_sparse &mat, bool transpose = false);

protected:
  //! Flag indicating that "alist" matrix data are properly set
  bool data_ok;
  //! Size of the matrix: \c M rows x \c N columns
  int M;
  //! Size of the matrix: \c M rows x \c N columns
  int N;
  //! List of integer coordinates in the m direction with non-zero entries
  imat mlist;
  //! List of integer coordinates in the n direction with non-zero entries
  imat nlist;
  //! Weight of each row m
  ivec num_mlist;
  //! Weight of each column n
  ivec num_nlist;
  //! Maximum weight of rows
  int max_num_m;
  //! Maximum weight of columns
  int max_num_n;
};


// ----------------------------------------------------------------------
// Dense GF(2) matrix class
// ----------------------------------------------------------------------

/*!
  \relatesalso bmat
  \brief Class for dense GF(2) matrices
  \author Erik G. Larsson

  This class can be used as an alternative to \c bmat to represent
  GF(2) matrices. It extends the functionality of \c bmat in two ways:

  - \c GF2mat makes more efficient use of computer memory than \c bmat
  (one bit in the matrix requires one bit of memory)
  - \c GF2mat provides several functions for linear algebra and matrix
  factorizations

  See also \c GF2mat_sparse which offers an efficient representation
  of sparse GF(2) matrices, and \c GF2mat_sparse_alist for a
  parameterized representation of sparse GF(2) matrices.
*/
class GF2mat
{
public:

  // ----------- Constructors -----------

  //! Default constructor (gives an empty 1 x 1 matrix)
  GF2mat();

  //! Construct an empty (all-zero) m x n matrix
  GF2mat(int m, int n);

  //! Construct a dense GF(2) matrix from a sparse GF(2) matrix
  GF2mat(const GF2mat_sparse &X);

  /*! \brief Constructor, from subset of sparse GF(2) matrix

  This constructor forms a dense GF(2) matrix from a subset (m1,n1)
  to (m2,n2) of a sparse GF(2) matrix */
  GF2mat(const GF2mat_sparse &X, int m1, int n1, int m2, int n2);

  /*! \brief Constructor, from subset of sparse GF(2) matrix

  This constructor forms a dense GF(2) matrix from a subset of
  columns in sparse GF(2) matrix

  \param X matrix to copy from
  \param columns subset of columns to copy
  */
  GF2mat(const GF2mat_sparse &X, const ivec &columns);

  /*!
    \brief Create a dense GF(2) matrix from a single vector.

    \param x The input vector
    \param is_column A parameter that indicates whether the result should
    be a row vector (false), or a column vector (true - default)
  */
  GF2mat(const bvec &x, bool is_column = true);

  //! Create a dense GF(2) matrix from a bmat
  GF2mat(const bmat &X);

  //! Set size of GF(2) matrix. If copy = true, keep data before resizing.
  void set_size(int m, int n, bool copy = false);

  //! Create a sparse GF(2) matrix from a dense GF(2) matrix
  GF2mat_sparse sparsify() const;

  //! Create a bvec from a GF(2) matrix (must have one column or one row)
  bvec bvecify() const;

  // ----------- Elementwise manipulation and simple functions -------------

  //! Getting element
  inline bin get(int i, int j) const;

  //! Getting element
  inline bin operator()(int i, int j) const { return get(i, j); };

  //! Set element i,j to s (0 or 1)
  inline void set(int i, int j, bin s);

  //! Add s (0 or 1) to element (i,j)
  inline void addto_element(int i, int j, bin s);

  //! Set column j to a binary vector x
  void set_col(int j, bvec x);

  //! Set row i to a binary vector x
  void set_row(int i, bvec x);

  //! Check whether the matrix is identical to zero
  bool is_zero() const;

  //! Swap rows i and j
  void swap_rows(int i, int j);

  //! Swap columns i and j
  void swap_cols(int i, int j);

  /*! \brief Multiply from left with permutation matrix (permute rows).

  \param perm Permutation vector
  \param I Parameter that determines permutation.
  I=0: apply permutation, I=1: apply inverse permutation
  */
  void permute_rows(ivec &perm, bool I);

  /*! \brief Multiply a matrix from right with a permutation matrix
    (i.e., permute the columns).

  \param perm Permutation vector
  \param I Parameter that determines permutation.
  I=0: apply permutation, I=1: apply inverse permutation
  */
  void permute_cols(ivec &perm, bool I);

  //! Transpose
  GF2mat transpose() const;

  //! Submatrix from (m1,n1) to (m2,n2)
  GF2mat get_submatrix(int m1, int n1, int m2, int n2) const;

  //! Concatenate horizontally (append X on the right side of matrix)
  GF2mat concatenate_horizontal(const GF2mat &X) const;

  //! Concatenate vertically (append X underneath)
  GF2mat concatenate_vertical(const GF2mat &X) const;

  //! Get row
  bvec get_row(int i) const;

  //! Get column
  bvec get_col(int j) const;

  //! Compute the matrix density (fraction of elements equal to "1")
  double density() const;

  //! Get number of rows
  int rows() const { return nrows; }

  //! Get number of columns
  int cols() const { return ncols; }

  /*! \brief Add (or equivalently, subtract) rows

  This function updates row i according to row_i = row_i+row_j

  \param i Row to add to. This row will be modified
  \param j Row to add. This row will <b>not</b> be modified.
  */
  void add_rows(int i, int j);

  // ---------- Linear algebra --------------

  /*!  \brief Inversion.

  The matrix must be invertible, otherwise the
    function will terminate with an error.
  */
  GF2mat inverse() const;

  //! Returns the number of linearly independent rows
  int row_rank() const;

  /*! \brief TXP factorization.

  Given X, compute a factorization of the form U=TXP, where U is
    upper triangular, T is square and invertible, and P is a
    permutation matrix.  This is basically an "LU"-factorization,
    but not called so here because T is not necessarily lower
    triangular.  The matrix X may have any dimension. The
    permutation matrix P is represented as a permutation vector.

    The function returns the row rank of X.  (If X is full row rank,
    then the number of rows is returned.)

    The function uses Gaussian elimination combined with
    permutations.  The computational complexity is O(m*m*n) for an
    m*n matrix.
  */
  int T_fact(GF2mat &T, GF2mat &U, ivec &P) const;

  /*! \brief TXP factorization update, when bit is flipped.

  Update upper triangular factor U in the TXP-factorization (U=TXP)
  when the bit at position (r,c) is changed (0->1 or 1->0). The
  purpose of this function is to avoid re-running a complete
  T-factorization when a single bit is changed. The function assumes
  that T, U, and P already exist and that U=TXP before the function
  is called. The function also assumes that the rank provided is
  correct. The function updates T, U and P these matrices.  The
  function returns the new rank of the matrix after the bitflip.

  \note T, U, P and the rank value supplied to the function must be
  correct one. This is not checked by the function (for reasons of
  efficiency).

  The function works by performing permutations to bring the matrix
  to a form where the Gaussian eliminated can be restarted from the
  point (rank-1,rank-1). The function is very fast for matrices with
  close to full rank but it is generally slower for non-full rank
  matrices.
  */
  int T_fact_update_bitflip(GF2mat &T, GF2mat &U,
                            ivec &P, int rank, int r, int c) const;

  /*!  \brief TXP factorization update, when column is added

  Update upper triangular factor U in the T-factorization (U=TXP)
  when a column (newcol) is appended at the right side of the
  matrix.  The purpose of this function is to avoid re-running a
  complete T-factorization when a column is added. The function ONLY
  adds the column if it improves the rank of the matrix (nothing is
  done otherwise).  The function returns "true" if the column was
  added, and "false" otherwise.

  \note This function does not actually add the column newcol to the
  GF2 matrix. It only checks whether doing so would increase the
  rank, and if this is the case, it updates the T-factorization.  A
  typical calling sequence would be
  \code
  bool rank_will_improve =  X.T_fact_update_addcol(T,U,perm,c);
  if (rank_will_improve) { X = X.concatenate_horizontal(c); }
  \endcode

  The complexity is O(m^2) for an m*n matrix.
  */
  bool T_fact_update_addcol(GF2mat &T, GF2mat &U,
                            ivec &P, bvec newcol) const;

  // ----- Operators -----------

  //! Assignment operator
  void operator=(const GF2mat &X);

  //! Check if equal
  bool operator==(const GF2mat &X) const;

  // ----- Friends ------

  //! Multiplication operator
  friend GF2mat operator*(const GF2mat &X, const GF2mat &Y);

  //! Multiplication operator with binary vector
  friend bvec operator*(const GF2mat &X, const bvec &y);

  /*! \brief Addition operator

  Subtraction is not implemented because it is
    equivalent to addition. */
  friend GF2mat operator+(const GF2mat &X, const GF2mat &Y);

  //! Output stream operator (plain text)
  friend std::ostream &operator<<(std::ostream &os, const GF2mat &X);

  //! Write the matrix to file
  friend it_file &operator<<(it_file &f, const GF2mat &X);

  //! Read the matrix from file
  friend it_ifile &operator>>(it_ifile &f, GF2mat &X);

  //!Multiplication X*Y' where X and Y are GF(2) matrices
  friend GF2mat mult_trans(const GF2mat &X, const GF2mat &Y);

private:
  int nrows, ncols;            // number of rows and columns of matrix
  int nwords;                  // number of bytes used
  Mat<unsigned char> data;   // data structure

  // This value is used to perform division by bit shift and is equal to
  // log2(8)
  static const unsigned char shift_divisor = 3;

  // This value is used as a mask when computing the bit position of the
  // division remainder
  static const unsigned char rem_mask = (1 << shift_divisor) - 1;
};


// ----------------------------------------------------------------------
// GF2mat related functions
// ----------------------------------------------------------------------

/*!
  /relatesalso GF2mat
  /brief Write GF(2) matrix to file.
*/
it_file &operator<<(it_file &f, const GF2mat &X);

/*!
  /relatesalso GF2mat
  /brief Read GF(2) matrix from file.
*/
it_ifile &operator>>(it_ifile &f, GF2mat &X);

/*!
  \relatesalso GF2mat
  \brief GF(2) matrix multiplication
*/
GF2mat operator*(const GF2mat &X, const GF2mat &Y);

/*!
  \relatesalso GF2mat
  \brief GF(2) matrix multiplication with "regular" binary vector
*/
bvec operator*(const GF2mat &X, const bvec &y);

/*!
  \relatesalso GF2mat
  \brief GF(2) matrix addition
*/
GF2mat operator+(const GF2mat &X, const GF2mat &Y);

/*!
  \relatesalso GF2mat
  \brief Output stream (plain text) operator for dense GF(2) matrices
*/
std::ostream &operator<<(std::ostream &os, const GF2mat &X);

/*!
  \relatesalso GF2mat
  \brief GF(2) Identity matrix
*/
GF2mat gf2dense_eye(int m);

/*!
  \relatesalso GF2mat
  \brief Multiplication X*Y' where X and Y are GF(2) matrices
*/
GF2mat mult_trans(const GF2mat &X, const GF2mat &Y);


// ----------------------------------------------------------------------
// Inline implementations
// ----------------------------------------------------------------------

inline void GF2mat::addto_element(int i, int j, bin s)
{
  it_assert_debug(i >= 0 && i < nrows, "GF2mat::addto_element()");
  it_assert_debug(j >= 0 && j < ncols, "GF2mat::addto_element()");
  if (s == 1)
    data(i, (j >> shift_divisor)) ^= (1 << (j & rem_mask));
}

inline bin GF2mat::get(int i, int j) const
{
  it_assert_debug(i >= 0 && i < nrows, "GF2mat::get_element()");
  it_assert_debug(j >= 0 && j < ncols, "GF2mat::get_element()");
  return (data(i, (j >> shift_divisor)) >> (j & rem_mask)) & 1;
}

inline void GF2mat::set(int i, int j, bin s)
{
  it_assert_debug(i >= 0 && i < nrows, "GF2mat::set_element()");
  it_assert_debug(j >= 0 && j < ncols, "GF2mat::set_element()");
  if (s == 1) // set bit to one
    data(i, (j >> shift_divisor)) |= (1 << (j & rem_mask));
  else // set bit to zero
    data(i, (j >> shift_divisor)) &= (~(1 << (j & rem_mask)));
}

} // namespace itpp

#endif // #ifndef GF2MAT_H
