/home/vivien/public_html/.src_seldon/matrix_sparse/Permutation_ScalingMatrix.cxx

// Copyright (C) 2003-2009 Marc Duruflé
// Copyright (C) 2001-2009 Vivien Mallet
//
// This file is part of the linear-algebra library Seldon,
// http://seldon.sourceforge.net/.
//
// Seldon is free software; you can redistribute it and/or modify it under the
// terms of the GNU Lesser General Public License as published by the Free
// Software Foundation; either version 2.1 of the License, or (at your option)
// any later version.
//
// Seldon 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 Lesser General Public License for
// more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with Seldon. If not, see http://www.gnu.org/licenses/.


#ifndef SELDON_FILE_PERMUTATION_SCALING_MATRIX_CXX

/*
  Functions defined in this file:

  ApplyInversePermutation(A, I, J)

  ScaleMatrix(A, Drow, Dcol)

  ScaleLeftMatrix(A, Drow)
*/

namespace Seldon
{



  template<class T, class Prop, class Allocator>
  void ApplyInversePermutation(Matrix<T, Prop, RowSparse, Allocator>& A,
                               const Vector<int>& row_perm,
                               const Vector<int>& col_perm)
  {
    int i, j, k, l, nnz;
    int m = A.GetM();
    int n = A.GetN();
    int* ind = A.GetInd();
    int* ptr = A.GetPtr();
    T* data = A.GetData();

    /*** Permutation of the columns ***/

    Vector<T, VectFull, Allocator> row_data;
    // Column indexes of a given row.
    Vector<int> row_index;
    for (i = 0; i < m; i++)
      if ((nnz = ptr[i + 1] - ptr[i]) != 0)
        {
          row_index.Reallocate(nnz);
          row_data.Reallocate(nnz);
          for (k = 0, l = ptr[i]; k < nnz; k++, l++)
            {
              // Applies the permutation on the columns.
              row_index(k) = col_perm(ind[l]);
              row_data(k) = data[l];
            }

          // The columns must remain in increasing order.
          Sort(row_index, row_data);

          // Putting back the data into the array.
          for (k = 0, l = ptr[i]; k < nnz; k++, l++)
            {
              ind[l] = row_index(k);
              data[l] = row_data(k);
            }
        }
    row_index.Clear();
    row_data.Clear();

    /*** Perturbation of the rows ***/

    // Total number of non-zero elements.
    nnz = ptr[m];

    // 'row_perm' is const, so it must be copied.
    Vector<int> row_permutation(row_perm);
    // Row indexes in the origin matrix: prev_row_index(i) should be the
    // location of the i-th row (from the permuted matrix) in the matrix
    // before permutation.
    Vector<int> prev_row_index(m);
    prev_row_index.Fill();

    Sort(row_permutation, prev_row_index);
    row_permutation.Clear();

    // Description of the matrix after permutations.
    Vector<int, VectFull, CallocAlloc<int> > new_ptr(m + 1);
    Vector<int, VectFull, CallocAlloc<int> > new_ind(nnz);
    Vector<T, VectFull, Allocator> new_data(nnz);

    int ptr_count = 0, length;
    for (i = 0; i < m; i++)
      {
        length = ptr[prev_row_index(i) + 1] - ptr[prev_row_index(i)];
        for (j = 0; j < length; j++)
          {
            new_data(ptr_count + j) = data[ptr[prev_row_index(i)] + j];
            new_ind(ptr_count + j) = ind[ptr[prev_row_index(i)] + j];
          }
        new_ptr(i) = ptr_count;
        ptr_count += length;
      }
    new_ptr(m) = ptr_count;

    A.SetData(m, n, new_data, new_ptr, new_ind);
  }



  template<class T, class Prop, class Allocator>
  void ApplyInversePermutation(Matrix<T, Prop, ColSparse, Allocator>& A,
                               const Vector<int>& row_perm,
                               const Vector<int>& col_perm)
  {
    int i, j, k, l, nnz;
    int m = A.GetM();
    int n = A.GetN();
    int* ind = A.GetInd();
    int* ptr = A.GetPtr();
    T* data = A.GetData();

    /*** Permutation of the rows ***/

    Vector<T, VectFull, Allocator> col_data;
    // Row indexes of a given column.
    Vector<int> col_index;
    for (i = 0; i < n; i++)
      if ((nnz = ptr[i + 1] - ptr[i]) != 0)
        {
          col_index.Reallocate(nnz);
          col_data.Reallocate(nnz);
          for (k = 0, l = ptr[i]; k < nnz; k++, l++)
            {
              // Applies the permutation on the rows.
              col_index(k) = row_perm(ind[l]);
              col_data(k) = data[l];
            }

          // The rows must remain in increasing order.
          Sort(col_index, col_data);

          // Putting back the data into the array.
          for (k = 0, l = ptr[i]; k < nnz; k++, l++)
            {
              ind[l] = col_index(k);
              data[l] = col_data(k);
            }
        }
    col_index.Clear();
    col_data.Clear();

    /*** Perturbation of the columns ***/

    // Total number of non-zero elements.
    nnz = ptr[n];

    // 'col_perm' is const, so it must be copied.
    Vector<int> col_permutation(col_perm);
    // Column indexes in the origin matrix: prev_col_index(i) should be the
    // location of the i-th column (from the permuted matrix) in the matrix
    // before permutation.
    Vector<int> prev_col_index(n);
    prev_col_index.Fill();

    Sort(col_permutation, prev_col_index);
    col_permutation.Clear();

    // Description of the matrix after permutations.
    Vector<int, VectFull, CallocAlloc<int> > new_ptr(n + 1);
    Vector<int, VectFull, CallocAlloc<int> > new_ind(nnz);
    Vector<T, VectFull, Allocator> new_data(nnz);

    int ptr_count = 0, length;
    for (i = 0; i < n; i++)
      {
        length = ptr[prev_col_index(i) + 1] - ptr[prev_col_index(i)];
        for (j = 0; j < length; j++)
          {
            new_data(ptr_count + j) = data[ptr[prev_col_index(i)] + j];
            new_ind(ptr_count + j) = ind[ptr[prev_col_index(i)] + j];
          }
        new_ptr(i) = ptr_count;
        ptr_count += length;
      }
    new_ptr(n) = ptr_count;

    A.SetData(m, n, new_data, new_ptr, new_ind);
  }



  template<class T, class Prop, class Allocator>
  void ApplyInversePermutation(Matrix<T, Prop, ArrayRowSparse, Allocator>& A,
                               const IVect& row_perm, const IVect& col_perm)
  {
    int m = A.GetM(), n, i, i_, j, i2;
    IVect ind_tmp, iperm(m), rperm(m);
    for (i = 0; i < m; i++)
      {
        iperm(i) = i;
        rperm(i) = i;
      }
    // A(rperm(i),:) will be the place where is the initial row i.

    // Algorithm avoiding the allocation of another matrix.
    for (i = 0; i < m; i++)
      {
        // We get the index of row where the row initially placed on row i is.
        i2 = rperm(i);
        // We get the new index of this row.
        i_ = row_perm(i);

        // We fill ind_tmp of the permuted indices of columns of row i.
        n = A.GetRowSize(i2);
        ind_tmp.Reallocate(n);
        for (j = 0; j < n; j++)
          ind_tmp(j) = col_perm(A.Index(i2,j));

        // We swap the two rows i and its destination row_perm(i).
        A.SwapRow(i2, i_);
        A.ReplaceIndexRow(i_, ind_tmp);

        // We update the indices iperm and rperm in order to keep in memory
        // the place where the row row_perm(i) is.
        int i_tmp = iperm(i_);
        iperm(i_) = iperm(i2);
        iperm(i2) = i_tmp;
        rperm(iperm(i_)) = i_;
        rperm(iperm(i2)) = i2;

        // We assemble the row i.
        A.AssembleRow(i_);
      }
  }



  template<class T, class Prop, class Allocator>
  void
  ApplyInversePermutation(Matrix<T, Prop, ArrayColSymSparse, Allocator>& A,
                          const IVect& row_perm, const IVect& col_perm)
  {
    // It is assumed that the permuted matrix is still symmetric! For example,
    // the user can provide row_perm = col_perm.
    int m = A.GetM();
    int nnz = A.GetDataSize();
    IVect IndRow(nnz), IndCol(nnz);
    Vector<T, VectFull, Allocator> Val(nnz);

    // First we convert the matrix in coordinate format and we permute the
    // indices.
    // IndRow -> indices of the permuted rows
    // IndCol -> indices of the permuted columns
    int k = 0;
    for (int i = 0; i < m; i++)
      for (int j = 0; j < A.GetColumnSize(i); j++)
        {
          IndCol(k) = col_perm(i);
          Val(k) = A.Value(i,j);
          IndRow(k) = row_perm(A.Index(i, j));
          if (IndCol(k) <= IndRow(k))
            {
              // We store only the superior part of the symmetric matrix.
              int ind_tmp = IndRow(k);
              IndRow(k) = IndCol(k);
              IndCol(k) = ind_tmp;
            }
          k++;
        }

    // We sort with respect to column numbers.
    Sort(nnz, IndCol, IndRow, Val);

    // A is filled.
    k = 0;
    for (int i = 0; i < m; i++)
      {
        int first_index = k;
        // We get the size of the column i.
        while (k < nnz && IndCol(k) <= i)
          k++;

        int size_column = k - first_index;
        // If column not empty.
        if (size_column > 0)
          {
            A.ReallocateColumn(i, size_column);
            k = first_index;
            Sort(k, k+size_column-1, IndRow, Val);
            for (int j = 0; j < size_column; j++)
              {
                A.Index(i,j) = IndRow(k);
                A.Value(i,j) = Val(k);
                k++;
              }
          }
        else
          A.ClearColumn(i);
      }
  }



  template<class T, class Prop, class Allocator>
  void ApplyInversePermutation(Matrix<T, Prop,
                               ArrayRowSymComplexSparse, Allocator>& A,
                               const IVect& row_perm,const IVect& col_perm)
  {
    // It is assumed that the permuted matrix is still symmetric! For example,
    // the user can provide row_perm = col_perm.
    int m = A.GetM();
    int nnz_real = A.GetRealDataSize(), nnz_imag = A.GetImagDataSize();
    IVect IndRow(nnz_real), IndCol(nnz_real);
    Vector<T, VectFull, Allocator> Val(nnz_real);

    // First we convert the matrix in coordinate format and we permute the
    // indices.
    // IndRow -> indices of the permuted rows
    // IndCol -> indices of the permuted columns
    int k = 0;
    for (int i = 0; i < m; i++)
      {
        for (int j = 0; j < A.GetRealRowSize(i); j++)
          {
            IndRow(k) = row_perm(i);
            Val(k) = A.ValueReal(i,j);
            IndCol(k) = col_perm(A.IndexReal(i, j));
            if (IndCol(k) <= IndRow(k))
              {
                // We store only the superior part of the symmetric matrix.
                int ind_tmp = IndRow(k);
                IndRow(k) = IndCol(k);
                IndCol(k) = ind_tmp;
              }
            k++;
          }
      }

    // We sort by row number.
    Sort(nnz_real, IndRow, IndCol, Val);

    // A is filled.
    k = 0;
    for (int i = 0; i < m; i++)
      {
        int first_index = k;
        // We get the size of the row i.
        while (k < nnz_real && IndRow(k) <= i)
          k++;

        int size_row = k - first_index;
        // If row not empty.
        if (size_row > 0)
          {
            A.ReallocateRealRow(i, size_row);
            k = first_index;
            Sort(k, k+size_row-1, IndCol, Val);
            for (int j = 0; j < size_row; j++)
              {
                A.IndexReal(i,j) = IndCol(k);
                A.ValueReal(i,j) = Val(k);
                k++;
              }
          }
        else
          A.ClearRealRow(i);
      }

    // Same procedure for imaginary part.

    IndRow.Reallocate(nnz_imag);
    IndCol.Reallocate(nnz_imag);
    Val.Reallocate(nnz_imag);

    // First we convert the matrix in coordinate format and we permute the
    // indices.
    // IndRow -> indices of the permuted rows
    // IndCol -> indices of the permuted columns
    k = 0;
    for (int i = 0; i < m; i++)
      {
        for (int j = 0; j < A.GetImagRowSize(i); j++)
          {
            IndRow(k) = row_perm(i);
            Val(k) = A.ValueImag(i,j);
            IndCol(k) = col_perm(A.IndexImag(i,j));
            if (IndCol(k) <= IndRow(k))
              {
                // We store only the superior part of the symmetric matrix.
                int ind_tmp = IndRow(k);
                IndRow(k) = IndCol(k);
                IndCol(k) = ind_tmp;
              }
            k++;
          }
      }
    // We sort by row number.
    Sort(nnz_imag, IndRow, IndCol, Val);

    // A is filled
    k = 0;
    for (int i = 0; i < m; i++)
      {
        int first_index = k;
        // We get the size of the row i.
        while (k < nnz_imag && IndRow(k) <= i)
          k++;
        int size_row = k - first_index;
        // If row not empty.
        if (size_row > 0)
          {
            A.ReallocateImagRow(i, size_row);
            k = first_index;
            Sort(k, k+size_row-1, IndCol, Val);
            for (int j = 0; j < size_row; j++)
              {
                A.IndexImag(i,j) = IndCol(k);
                A.ValueImag(i,j) = Val(k);
                k++;
              }
          }
        else
          A.ClearImagRow(i);
      }
  }



  template<class T, class Prop, class Allocator>
  void
  ApplyInversePermutation(Matrix<T, Prop, ArrayRowSymSparse, Allocator>& A,
                          const IVect& row_perm, const IVect& col_perm)
  {
    // It is assumed that the permuted matrix is still symmetric! For example,
    // the user can provide row_perm = col_perm.
    int m = A.GetM();
    int nnz = A.GetDataSize();
    IVect IndRow(nnz), IndCol(nnz);
    Vector<T,VectFull,Allocator> Val(nnz);

    // First we convert the matrix in coordinate format and we permute the
    // indices.
    // IndRow -> indices of the permuted rows
    // IndCol -> indices of the permuted columns
    int k = 0;
    for (int i = 0; i < m; i++)
      {
        for (int j = 0; j < A.GetRowSize(i); j++)
          {
            IndRow(k) = row_perm(i);
            Val(k) = A.Value(i, j);
            IndCol(k) = col_perm(A.Index(i, j));
            if (IndCol(k) <= IndRow(k))
              {
                // We store only the superior part of the symmetric matrix.
                int ind_tmp = IndRow(k);
                IndRow(k) = IndCol(k);
                IndCol(k) = ind_tmp;
              }
            k++;
          }
      }
    // We sort with respect to row numbers.
    Sort(nnz, IndRow, IndCol, Val);

    // A is filled.
    k = 0;
    for (int i = 0; i < m; i++)
      {
        int first_index = k;
        // We get the size of the row i.
        while (k < nnz && IndRow(k) <= i)
          k++;
        int size_row = k - first_index;
        // If row not empty.
        if (size_row > 0)
          {
            A.ReallocateRow(i, size_row);
            k = first_index;
            Sort(k, k+size_row-1, IndCol, Val);
            for (int j = 0; j < size_row; j++)
              {
                A.Index(i,j) = IndCol(k);
                A.Value(i,j) = Val(k);
                k++;
              }
          }
        else
          A.ClearRow(i);
      }
  }



  template<class Prop, class T1, class Allocator1,
           class T2, class Allocator2, class T3, class Allocator3>
  void ScaleMatrix(Matrix<T1, Prop, ArrayRowSparse, Allocator1>& A,
                   const Vector<T2, VectFull, Allocator2>& scale_left,
                   const Vector<T3, VectFull, Allocator3>& scale_right)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      for (int j = 0; j < A.GetRowSize(i); j++ )
        A.Value(i,j) *= scale_left(i) * scale_right(A.Index(i, j));

  }



  template<class Prop, class T1, class Allocator1,
           class T2, class Allocator2, class T3, class Allocator3>
  void ScaleMatrix(Matrix<T1, Prop, ArrayRowSymSparse, Allocator1>& A,
                   const Vector<T2, VectFull, Allocator2>& scale_left,
                   const Vector<T3, VectFull, Allocator3>& scale_right)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      for (int j = 0; j < A.GetRowSize(i); j++ )
        A.Value(i,j) *= scale_left(i) * scale_right(A.Index(i, j));

  }



  template<class Prop, class T1, class Allocator1,
           class T2, class Allocator2, class T3, class Allocator3>
  void ScaleMatrix(Matrix<T1, Prop, ArrayRowSymComplexSparse, Allocator1>& A,
                   const Vector<T2, VectFull, Allocator2>& scale_left,
                   const Vector<T3, VectFull, Allocator3>& scale_right)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      {
        for (int j = 0; j < A.GetRealRowSize(i); j++ )
          A.ValueReal(i,j) *= scale_left(i) * scale_right(A.IndexReal(i, j));

        for (int j = 0; j < A.GetImagRowSize(i); j++ )
          A.ValueImag(i,j) *= scale_left(i) * scale_right(A.IndexImag(i, j));
      }
  }



  template<class Prop, class T1, class Allocator1,
           class T2, class Allocator2, class T3, class Allocator3>
  void ScaleMatrix(Matrix<T1, Prop, ArrayRowComplexSparse, Allocator1>& A,
                   const Vector<T2, VectFull, Allocator2>& scale_left,
                   const Vector<T3, VectFull, Allocator3>& scale_right)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      {
        for (int j = 0; j < A.GetRealRowSize(i); j++ )
          A.ValueReal(i,j) *= scale_left(i) * scale_right(A.IndexReal(i, j));

        for (int j = 0; j < A.GetImagRowSize(i); j++ )
          A.ValueImag(i,j) *= scale_left(i) * scale_right(A.IndexImag(i, j));
      }
  }



  template<class T1, class Allocator1,
           class Prop, class T2, class Allocator2>
  void ScaleLeftMatrix(Matrix<T1, Prop, ArrayRowSparse, Allocator1>& A,
                       const Vector<T2, VectFull, Allocator2>& scale)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      for (int j = 0; j < A.GetRowSize(i); j++ )
        A.Value(i,j) *= scale(i);
  }



  template<class T1, class Allocator1,
           class Prop, class T2, class Allocator2>
  void ScaleLeftMatrix(Matrix<T1, Prop, ArrayRowSymSparse, Allocator1>& A,
                       const Vector<T2, VectFull, Allocator2>& scale)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      for (int j = 0; j < A.GetRowSize(i); j++ )
        A.Value(i,j) *= scale(i);
  }



  template<class T1, class Allocator1,
           class Prop, class T2, class Allocator2>
  void ScaleLeftMatrix(Matrix<T1, Prop, ArrayRowSymComplexSparse, Allocator1>& A,
                       const Vector<T2, VectFull, Allocator2>& scale)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      {
        for (int j = 0; j < A.GetRealRowSize(i); j++ )
          A.ValueReal(i,j) *= scale(i);

        for (int j = 0; j < A.GetImagRowSize(i); j++ )
          A.ValueImag(i,j) *= scale(i);
      }
  }



  template<class T1, class Allocator1,
           class Prop, class T2, class Allocator2>
  void ScaleLeftMatrix(Matrix<T1, Prop, ArrayRowComplexSparse, Allocator1>& A,
                       const Vector<T2, VectFull, Allocator2>& scale)
  {
    int m = A.GetM();
    for (int i = 0; i < m; i++ )
      {
        for (int j = 0; j < A.GetRealRowSize(i); j++ )
          A.ValueReal(i,j) *= scale(i);

        for (int j = 0; j < A.GetImagRowSize(i); j++ )
          A.ValueImag(i,j) *= scale(i);
      }

  }


} // end namespace

#define SELDON_FILE_PERMUTATION_SCALING_MATRIX_CXX
#endif