block_sparsity_pattern.cc

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//
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#include <deal.II/base/memory_consumption.h>

#include <deal.II/lac/block_sparsity_pattern.h>

DEAL_II_NAMESPACE_OPEN


template <class SparsityPatternBase>
BlockSparsityPatternBase<SparsityPatternBase>::BlockSparsityPatternBase()
  : rows(0)
  , columns(0)
{}



template <class SparsityPatternBase>
BlockSparsityPatternBase<SparsityPatternBase>::BlockSparsityPatternBase(
  const size_type n_block_rows,
  const size_type n_block_columns)
  : rows(0)
  , columns(0)
{
  reinit(n_block_rows, n_block_columns);
}



template <class SparsityPatternBase>
BlockSparsityPatternBase<SparsityPatternBase>::BlockSparsityPatternBase(
  const BlockSparsityPatternBase &s)
  : Subscriptor()
  , rows(0)
  , columns(0)
{
  (void)s;
  Assert(s.rows == 0 && s.columns == 0,
         ExcMessage(
           "This constructor can only be called if the provided argument "
           "is the sparsity pattern for an empty matrix. This constructor can "
           "not be used to copy-construct a non-empty sparsity pattern."));
}



template <class SparsityPatternBase>
BlockSparsityPatternBase<SparsityPatternBase>::~BlockSparsityPatternBase()
{
  // clear all memory
  try
    {
      reinit(0, 0);
    }
  catch (...)
    {}
}



template <class SparsityPatternBase>
void
BlockSparsityPatternBase<SparsityPatternBase>::reinit(
  const size_type n_block_rows,
  const size_type n_block_columns)
{
  // delete previous content and
  // clean the sub_objects array
  // completely
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      {
        SparsityPatternBase *sp = sub_objects[i][j];
        sub_objects[i][j]       = nullptr;
        delete sp;
      }
  sub_objects.reinit(0, 0);

  // then set new sizes
  rows    = n_block_rows;
  columns = n_block_columns;
  sub_objects.reinit(rows, columns);

  // allocate new objects
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      {
        SparsityPatternBase *p = new SparsityPatternBase;
        sub_objects[i][j]      = p;
      }
}


template <class SparsityPatternBase>
BlockSparsityPatternBase<SparsityPatternBase> &
BlockSparsityPatternBase<SparsityPatternBase>::
operator=(const BlockSparsityPatternBase<SparsityPatternBase> &bsp)
{
  Assert(rows == bsp.rows, ExcDimensionMismatch(rows, bsp.rows));
  Assert(columns == bsp.columns, ExcDimensionMismatch(columns, bsp.columns));
  // copy objects
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      *sub_objects[i][j] = *bsp.sub_objects[i][j];
  // update index objects
  collect_sizes();

  return *this;
}



template <class SparsityPatternBase>
void
BlockSparsityPatternBase<SparsityPatternBase>::collect_sizes()
{
  std::vector<size_type> row_sizes(rows);
  std::vector<size_type> col_sizes(columns);

  // first find out the row sizes
  // from the first block column
  for (size_type r = 0; r < rows; ++r)
    row_sizes[r] = sub_objects[r][0]->n_rows();
  // then check that the following
  // block columns have the same
  // sizes
  for (size_type c = 1; c < columns; ++c)
    for (size_type r = 0; r < rows; ++r)
      Assert(row_sizes[r] == sub_objects[r][c]->n_rows(),
             ExcIncompatibleRowNumbers(r, 0, r, c));

  // finally initialize the row
  // indices with this array
  row_indices.reinit(row_sizes);


  // then do the same with the columns
  for (size_type c = 0; c < columns; ++c)
    col_sizes[c] = sub_objects[0][c]->n_cols();
  for (size_type r = 1; r < rows; ++r)
    for (size_type c = 0; c < columns; ++c)
      Assert(col_sizes[c] == sub_objects[r][c]->n_cols(),
             ExcIncompatibleRowNumbers(0, c, r, c));

  // finally initialize the row
  // indices with this array
  column_indices.reinit(col_sizes);
}



template <class SparsityPatternBase>
void
BlockSparsityPatternBase<SparsityPatternBase>::compress()
{
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      sub_objects[i][j]->compress();
}



template <class SparsityPatternBase>
bool
BlockSparsityPatternBase<SparsityPatternBase>::empty() const
{
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      if (sub_objects[i][j]->empty() == false)
        return false;
  return true;
}



template <class SparsityPatternBase>
typename BlockSparsityPatternBase<SparsityPatternBase>::size_type
BlockSparsityPatternBase<SparsityPatternBase>::max_entries_per_row() const
{
  size_type max_entries = 0;
  for (size_type block_row = 0; block_row < rows; ++block_row)
    {
      size_type this_row = 0;
      for (size_type c = 0; c < columns; ++c)
        this_row += sub_objects[block_row][c]->max_entries_per_row();

      if (this_row > max_entries)
        max_entries = this_row;
    }
  return max_entries;
}



template <class SparsityPatternBase>
typename BlockSparsityPatternBase<SparsityPatternBase>::size_type
BlockSparsityPatternBase<SparsityPatternBase>::n_rows() const
{
  // only count in first column, since
  // all rows should be equivalent
  size_type count = 0;
  for (size_type r = 0; r < rows; ++r)
    count += sub_objects[r][0]->n_rows();
  return count;
}



template <class SparsityPatternBase>
typename BlockSparsityPatternBase<SparsityPatternBase>::size_type
BlockSparsityPatternBase<SparsityPatternBase>::n_cols() const
{
  // only count in first row, since
  // all rows should be equivalent
  size_type count = 0;
  for (size_type c = 0; c < columns; ++c)
    count += sub_objects[0][c]->n_cols();
  return count;
}



template <class SparsityPatternBase>
typename BlockSparsityPatternBase<SparsityPatternBase>::size_type
BlockSparsityPatternBase<SparsityPatternBase>::n_nonzero_elements() const
{
  size_type count = 0;
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      count += sub_objects[i][j]->n_nonzero_elements();
  return count;
}



template <class SparsityPatternBase>
void
BlockSparsityPatternBase<SparsityPatternBase>::print(std::ostream &out) const
{
  size_type k = 0;
  for (size_type ib = 0; ib < n_block_rows(); ++ib)
    {
      for (size_type i = 0; i < block(ib, 0).n_rows(); ++i)
        {
          out << '[' << i + k;
          size_type l = 0;
          for (size_type jb = 0; jb < n_block_cols(); ++jb)
            {
              const SparsityPatternBase &b = block(ib, jb);
              for (size_type j = 0; j < b.n_cols(); ++j)
                if (b.exists(i, j))
                  out << ',' << l + j;
              l += b.n_cols();
            }
          out << ']' << std::endl;
        }
      k += block(ib, 0).n_rows();
    }
}


#ifndef DOXYGEN
template <>
void
BlockSparsityPatternBase<DynamicSparsityPattern>::print(std::ostream &out) const
{
  size_type k = 0;
  for (size_type ib = 0; ib < n_block_rows(); ++ib)
    {
      for (size_type i = 0; i < block(ib, 0).n_rows(); ++i)
        {
          out << '[' << i + k;
          size_type l = 0;
          for (size_type jb = 0; jb < n_block_cols(); ++jb)
            {
              const DynamicSparsityPattern &b = block(ib, jb);
              if (b.row_index_set().size() == 0 ||
                  b.row_index_set().is_element(i))
                for (size_type j = 0; j < b.n_cols(); ++j)
                  if (b.exists(i, j))
                    out << ',' << l + j;
              l += b.n_cols();
            }
          out << ']' << std::endl;
        }
      k += block(ib, 0).n_rows();
    }
}
#endif


template <class SparsityPatternBase>
void
BlockSparsityPatternBase<SparsityPatternBase>::print_gnuplot(
  std::ostream &out) const
{
  size_type k = 0;
  for (size_type ib = 0; ib < n_block_rows(); ++ib)
    {
      for (size_type i = 0; i < block(ib, 0).n_rows(); ++i)
        {
          size_type l = 0;
          for (size_type jb = 0; jb < n_block_cols(); ++jb)
            {
              const SparsityPatternBase &b = block(ib, jb);
              for (size_type j = 0; j < b.n_cols(); ++j)
                if (b.exists(i, j))
                  out << l + j << " " << -static_cast<signed int>(i + k)
                      << std::endl;
              l += b.n_cols();
            }
        }
      k += block(ib, 0).n_rows();
    }
}



BlockSparsityPattern::BlockSparsityPattern(const size_type n_rows,
                                           const size_type n_columns)
  : BlockSparsityPatternBase<SparsityPattern>(n_rows, n_columns)
{}


void
BlockSparsityPattern::reinit(
  const BlockIndices &                          rows,
  const BlockIndices &                          cols,
  const std::vector<std::vector<unsigned int>> &row_lengths)
{
  AssertDimension(row_lengths.size(), cols.size());

  this->reinit(rows.size(), cols.size());
  for (size_type j = 0; j < cols.size(); ++j)
    for (size_type i = 0; i < rows.size(); ++i)
      {
        const size_type start  = rows.local_to_global(i, 0);
        const size_type length = rows.block_size(i);

        if (row_lengths[j].size() == 1)
          block(i, j).reinit(rows.block_size(i),
                             cols.block_size(j),
                             row_lengths[j][0]);
        else
          {
            Assert(row_lengths[j].begin() + start + length <=
                     row_lengths[j].end(),
                   ExcInternalError());
            ArrayView<const unsigned int> block_rows(row_lengths[j].data() +
                                                       start,
                                                     length);
            block(i, j).reinit(rows.block_size(i),
                               cols.block_size(j),
                               block_rows);
          }
      }
  this->collect_sizes();
  Assert(this->row_indices == rows, ExcInternalError());
  Assert(this->column_indices == cols, ExcInternalError());
}


bool
BlockSparsityPattern::is_compressed() const
{
  for (size_type i = 0; i < rows; ++i)
    for (size_type j = 0; j < columns; ++j)
      if (sub_objects[i][j]->is_compressed() == false)
        return false;
  return true;
}


std::size_t
BlockSparsityPattern::memory_consumption() const
{
  std::size_t mem = 0;
  mem += (MemoryConsumption::memory_consumption(rows) +
          MemoryConsumption::memory_consumption(columns) +
          MemoryConsumption::memory_consumption(sub_objects) +
          MemoryConsumption::memory_consumption(row_indices) +
          MemoryConsumption::memory_consumption(column_indices));
  for (size_type r = 0; r < rows; ++r)
    for (size_type c = 0; c < columns; ++c)
      mem += MemoryConsumption::memory_consumption(*sub_objects[r][c]);

  return mem;
}



void
BlockSparsityPattern::copy_from(const BlockDynamicSparsityPattern &dsp)
{
  // delete old content, set block
  // sizes anew
  reinit(dsp.n_block_rows(), dsp.n_block_cols());

  // copy over blocks
  for (size_type i = 0; i < n_block_rows(); ++i)
    for (size_type j = 0; j < n_block_cols(); ++j)
      block(i, j).copy_from(dsp.block(i, j));

  // and finally enquire their new
  // sizes
  collect_sizes();
}



BlockDynamicSparsityPattern::BlockDynamicSparsityPattern(
  const size_type n_rows,
  const size_type n_columns)
  : BlockSparsityPatternBase<DynamicSparsityPattern>(n_rows, n_columns)
{}



BlockDynamicSparsityPattern::BlockDynamicSparsityPattern(
  const std::vector<size_type> &row_indices,
  const std::vector<size_type> &col_indices)
  : BlockSparsityPatternBase<DynamicSparsityPattern>(row_indices.size(),
                                                     col_indices.size())
{
  for (size_type i = 0; i < row_indices.size(); ++i)
    for (size_type j = 0; j < col_indices.size(); ++j)
      this->block(i, j).reinit(row_indices[i], col_indices[j]);
  this->collect_sizes();
}


BlockDynamicSparsityPattern::BlockDynamicSparsityPattern(
  const std::vector<IndexSet> &partitioning)
  : BlockSparsityPatternBase<DynamicSparsityPattern>(partitioning.size(),
                                                     partitioning.size())
{
  for (size_type i = 0; i < partitioning.size(); ++i)
    for (size_type j = 0; j < partitioning.size(); ++j)
      this->block(i, j).reinit(partitioning[i].size(),
                               partitioning[j].size(),
                               partitioning[i]);
  this->collect_sizes();
}


BlockDynamicSparsityPattern::BlockDynamicSparsityPattern(
  const BlockIndices &row_indices,
  const BlockIndices &col_indices)
{
  reinit(row_indices, col_indices);
}


void
BlockDynamicSparsityPattern::reinit(
  const std::vector<size_type> &row_block_sizes,
  const std::vector<size_type> &col_block_sizes)
{
  BlockSparsityPatternBase<DynamicSparsityPattern>::reinit(
    row_block_sizes.size(), col_block_sizes.size());
  for (size_type i = 0; i < row_block_sizes.size(); ++i)
    for (size_type j = 0; j < col_block_sizes.size(); ++j)
      this->block(i, j).reinit(row_block_sizes[i], col_block_sizes[j]);
  this->collect_sizes();
}

void
BlockDynamicSparsityPattern::reinit(const std::vector<IndexSet> &partitioning)
{
  BlockSparsityPatternBase<DynamicSparsityPattern>::reinit(partitioning.size(),
                                                           partitioning.size());
  for (size_type i = 0; i < partitioning.size(); ++i)
    for (size_type j = 0; j < partitioning.size(); ++j)
      this->block(i, j).reinit(partitioning[i].size(),
                               partitioning[j].size(),
                               partitioning[i]);
  this->collect_sizes();
}

void
BlockDynamicSparsityPattern::reinit(const BlockIndices &row_indices,
                                    const BlockIndices &col_indices)
{
  BlockSparsityPatternBase<DynamicSparsityPattern>::reinit(row_indices.size(),
                                                           col_indices.size());
  for (size_type i = 0; i < row_indices.size(); ++i)
    for (size_type j = 0; j < col_indices.size(); ++j)
      this->block(i, j).reinit(row_indices.block_size(i),
                               col_indices.block_size(j));
  this->collect_sizes();
}


#ifdef DEAL_II_WITH_TRILINOS
namespace TrilinosWrappers
{
  BlockSparsityPattern::BlockSparsityPattern(const size_type n_rows,
                                             const size_type n_columns)
    : ::BlockSparsityPatternBase<SparsityPattern>(n_rows, n_columns)
  {}



  BlockSparsityPattern::BlockSparsityPattern(
    const std::vector<size_type> &row_indices,
    const std::vector<size_type> &col_indices)
    : BlockSparsityPatternBase<SparsityPattern>(row_indices.size(),
                                                col_indices.size())
  {
    for (size_type i = 0; i < row_indices.size(); ++i)
      for (size_type j = 0; j < col_indices.size(); ++j)
        this->block(i, j).reinit(row_indices[i], col_indices[j]);
    this->collect_sizes();
  }



  BlockSparsityPattern::BlockSparsityPattern(
    const std::vector<IndexSet> &parallel_partitioning,
    const MPI_Comm &             communicator)
    : BlockSparsityPatternBase<SparsityPattern>(parallel_partitioning.size(),
                                                parallel_partitioning.size())
  {
    for (size_type i = 0; i < parallel_partitioning.size(); ++i)
      for (size_type j = 0; j < parallel_partitioning.size(); ++j)
        this->block(i, j).reinit(parallel_partitioning[i],
                                 parallel_partitioning[j],
                                 communicator);
    this->collect_sizes();
  }



  BlockSparsityPattern::BlockSparsityPattern(
    const std::vector<IndexSet> &row_parallel_partitioning,
    const std::vector<IndexSet> &col_parallel_partitioning,
    const std::vector<IndexSet> &writable_rows,
    const MPI_Comm &             communicator)
    : BlockSparsityPatternBase<SparsityPattern>(
        row_parallel_partitioning.size(),
        col_parallel_partitioning.size())
  {
    for (size_type i = 0; i < row_parallel_partitioning.size(); ++i)
      for (size_type j = 0; j < col_parallel_partitioning.size(); ++j)
        this->block(i, j).reinit(row_parallel_partitioning[i],
                                 col_parallel_partitioning[j],
                                 writable_rows[i],
                                 communicator);
    this->collect_sizes();
  }



  void
  BlockSparsityPattern::reinit(const std::vector<size_type> &row_block_sizes,
                               const std::vector<size_type> &col_block_sizes)
  {
    ::BlockSparsityPatternBase<SparsityPattern>::reinit(
      row_block_sizes.size(), col_block_sizes.size());
    for (size_type i = 0; i < row_block_sizes.size(); ++i)
      for (size_type j = 0; j < col_block_sizes.size(); ++j)
        this->block(i, j).reinit(row_block_sizes[i], col_block_sizes[j]);
    this->collect_sizes();
  }



  void
  BlockSparsityPattern::reinit(
    const std::vector<IndexSet> &parallel_partitioning,
    const MPI_Comm &             communicator)
  {
    ::BlockSparsityPatternBase<SparsityPattern>::reinit(
      parallel_partitioning.size(), parallel_partitioning.size());
    for (size_type i = 0; i < parallel_partitioning.size(); ++i)
      for (size_type j = 0; j < parallel_partitioning.size(); ++j)
        this->block(i, j).reinit(parallel_partitioning[i],
                                 parallel_partitioning[j],
                                 communicator);
    this->collect_sizes();
  }



  void
  BlockSparsityPattern::reinit(
    const std::vector<IndexSet> &row_parallel_partitioning,
    const std::vector<IndexSet> &col_parallel_partitioning,
    const MPI_Comm &             communicator)
  {
    ::BlockSparsityPatternBase<SparsityPattern>::reinit(
      row_parallel_partitioning.size(), col_parallel_partitioning.size());
    for (size_type i = 0; i < row_parallel_partitioning.size(); ++i)
      for (size_type j = 0; j < col_parallel_partitioning.size(); ++j)
        this->block(i, j).reinit(row_parallel_partitioning[i],
                                 col_parallel_partitioning[j],
                                 communicator);
    this->collect_sizes();
  }



  void
  BlockSparsityPattern::reinit(
    const std::vector<IndexSet> &row_parallel_partitioning,
    const std::vector<IndexSet> &col_parallel_partitioning,
    const std::vector<IndexSet> &writable_rows,
    const MPI_Comm &             communicator)
  {
    AssertDimension(writable_rows.size(), row_parallel_partitioning.size());
    ::BlockSparsityPatternBase<SparsityPattern>::reinit(
      row_parallel_partitioning.size(), col_parallel_partitioning.size());
    for (size_type i = 0; i < row_parallel_partitioning.size(); ++i)
      for (size_type j = 0; j < col_parallel_partitioning.size(); ++j)
        this->block(i, j).reinit(row_parallel_partitioning[i],
                                 col_parallel_partitioning[j],
                                 writable_rows[i],
                                 communicator);
    this->collect_sizes();
  }

} // namespace TrilinosWrappers

#endif

template class BlockSparsityPatternBase<SparsityPattern>;
template class BlockSparsityPatternBase<DynamicSparsityPattern>;
#ifdef DEAL_II_WITH_TRILINOS
template class BlockSparsityPatternBase<TrilinosWrappers::SparsityPattern>;
#endif

DEAL_II_NAMESPACE_CLOSE