Compact storage and fast transpose of sparse matrices

When a matrix is a sparse matrix, the number of valid data is much less than the invalid data, so if a matrix all storage will waste space, you can only store valid data, invalid data as a marker

The code is as follows:

#include  <iostream> #include  <vector>using namespace std;// You can use a ternary group to store the information for valid data template<class t>struct triple{ size_t _row; size_t _col;  t _value;};/ /coefficient Matrix class  template<class T> class SparseMatrix { public:   Sparsematrix (t* arr, size_t rowsize, size_t colsize, const t&  Invaild);   void display ();   sparsematrix<t>& transpose ();   Sparsematrix<t> fasttranspose ();  protected:  vector<triple<t>> _ array;  size_t _rowsize;  size_t _colsize;  t _invaild; }; The   //can be used sequentially to store valid data  template<class t> sparsematrix<t>::sparsematrix (T*  arr, size_t rowsize, size_t colsize, const t& invaild)    :_invaild (Invaild)   , _rowsize (rowsize)   ,_colsize (colsize)  {  size_t rpos = 0;   for (rpos = 0; rpos < rowsize; rpos++)   {   size_t  cpos = 0;   for (Cpos = 0; cpos < colsize; cpos + +)    {    if (arr[(rpos * colsize)  + cpos] !=  invaild)     {     Triple<T> t;      t._row = rpos;     t._col = cpos;      t._value = arr[(rpos * colsize)  + cpos];      _array.push_back (t);         }   }   } }  //print matrix  template <class t> void sparsematrix<t>: :D isplay ()  {   Size_t rpos = 0;  size_t index = 0;  for (rpos = 0 ;  rpos < _rowsize; rpos++)   {   size_t cpos = 0 ;       for (cpos = 0; cpos < _colsize; cpos++)    {    if ((Index < _array.size ())  &&  (RpoS  == _array[index]._row)  &&  (cpos == _array[index]._col)      {     cout<<_array[index]._value<< " ";      index++;    }    else     cout <<_invaild<< " ";   }   cout<<endl;  }   cout<<endl; }  //Transpose  template<class T>SparseMatrix<T>&  sparsematrix<t>:: Transpose () { size_t i = 0; size_t j = 0; for (i = 0;  i < _array.size ();  i++)  {  for (j = i+1; j <  _array.size ();  j++)   {   if (_array[i]._col > _array[j]._col)     swap (_array[i],_array[j]);   }  swap (_array[i]._row,_array[i]._col) ;  }  swap (_rowsize,_colsize);  return *this;} Quick Transpose Template<class t>sparsematrix<t> sparsematrix<t>::fasttranspose () { size _t* rowcounts = new size_t[_colsize]; size_t index = 0; for (Index  = 0; index < _array.size ();  index++)  {  rowcounts[_array[ index]._col]++;   //statistics The number of valid data for each row of the matrix after transpose  } size_t* rowstart = new  Size_t[_colsize]; rowstart[0] = 0; for (INDEX&Nbsp;= 1; index < _colsize; index++)  {  rowstart[index] =  rowcounts[index-1] + rowstart[index-1]; }   //the starting position of each row in the matrix in the compression matrix after the transpose of the statistics  vector <triple<t>> arr; size_t count = 0; for (size_t i = 0;  i < _colsize; i++)  {  for (index = 0; index <  _array.size ();  index++)   {   if (rowcounts[i] != 0)     {    if (_array[index]._col == rowstart[i])     {      triple<t> t;     t._col = _array[index]. _row;     t._row = _array[index]._col;     t._ Value = _array[index]._value;     arr.push_back (t);     }   }&nBsp;  else    break;  } } swap (_array,arr);  swap (_ rowsize,_colsize);  return *this;}

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Compact storage and fast transpose of sparse matrices