C++实现稀疏矩阵的压缩存储实例

 #include #include #include using namespace std; template class SparseMatrix { //三元组 template struct Trituple { Trituple()//给一个默认构造函数 {} Trituple(size_t row, size_t col, const T& data) :_row(row) ,_col(col) ,_data(data) {} size_t _row; size_t _col; T _data; }; public: //稀疏矩阵的压缩存储 SparseMatrix() {} SparseMatrix(int* arr, size_t row, size_t col, const T& invalid) :_row(row) ,_col(col) ,_invalid(invalid) { for(int i = 0; i (i,j,arr[i*col+j]));//将三元组的无名对象push进去 } } } //访问稀疏矩阵中row行col中的元素 T& Acess(int row, int col) { //1、 /*for(int idx = 0; idx <_sm.size(); idx++)//遍历一遍 { if(_sm[idx]._row == row && _sm[idx]._col == col)//当前行列与我们要访问那个元素行列相同时返回这个有效值 return _sm[idx]._data; } return _invalid;*/ //否则返回无效值 //2、 vector>::iterator it = _sm.begin();//定义一个迭代器,指向起始位置 while(it != _sm.end())//未到最后一个元素时 { if(it->_row == row && it->_col == col)//行列相等输出值 return it->_data; ++it;//迭代器向后移动 } return _invalid; } //还原稀疏矩阵 template friend ostream& operator<<(ostream& _cout, SparseMatrix& s)//重载<< { size_t idex = 0; for(size_t i = 0; i  Transport() { SparseMatrix sm; sm._row = _col; sm._col = _row; sm._invalid = _invalid; for(size_t i = 0; i <_col; i++) { vector>::iterator it = _sm.begin(); while(it != _sm.end()) { if(it->_col == i)//从原矩阵第0列开始，将每列中的有效值依次放入新的稀疏矩阵 sm._sm.push_back(Trituple (i, it->_row, it->_data)); ++it; } } return sm; } //实现稀疏矩阵的快速转置 时间复杂度O(N)+O(M) SparseMatrix FastTransport() { SparseMatrix sm; sm._col = _row; sm._row = _col; sm._invalid = _invalid; sm._sm.resize(_sm.size());//开辟空间 //1、统计原矩阵中每一列有多少个有效元素 int* pCount = new int[_col];//开辟原矩阵中列个数的空间 memset(pCount, 0, _col*sizeof(pCount[0])); for(int i = 0; i <_sm.size(); i++) pCount[_sm[i]._col]++; //2、原矩阵每一列在新矩阵中的起始位值 int* pAddr = new int[_col]; memset(pAddr, 0, _col*sizeof(pAddr[0])); for(int i = 1/*从1开始，第一个位置起始为0已经放入*/; i <_sm.size(); i++) { pAddr[i] = pAddr[i - 1] + pCount[i - 1];//前一个起始位值+前一列有效元素个数 } //3、放置元素到新空间 for(int i = 0; i <_sm.size(); i++) { int& addr = pAddr[_sm[i]._col]; sm._sm[addr] = Trituple(_sm[i]._col,_sm[i]._row,_sm[i]._data); addr++; } return sm; } //实现稀疏矩阵的加法操作1 /*SparseMatrix operator+(const SparseMatrix& sp) { int i = 0, j = 0, k = 0; T v; SparseMatrix s; if(this->_col != sp._col || this->_row != sp._row) exit(1); s._row = sp._row; s._col = sp._col; s._invalid = sp._invalid; while(i _sm.size() && j _sm[i]._row == sp._sm[j]._row) { if(this->_sm[i]._col (this->_sm[i]._row, this->_sm[i]._col, this->_sm[i]._data)); i++; k++; } else if(this->_sm[i]._col > sp._sm[j]._col) { s._sm.push_back(Trituple(sp._sm[j]._row, sp._sm[j]._col, sp._sm[j]._data)); j++; k++; } else { v = this->_sm[i]._data + sp._sm[j]._data; if(v) { s._sm.push_back(Trituple(sp._sm[j]._row, sp._sm[j]._col, v)); k++; } i++; j++; } } else if(this->_sm[i]._row (this->_sm[i]._row, this->_sm[i]._col, this->_sm[i]._data)); i++; k++; } else { s._sm.push_back(Trituple(sp._sm[j]._row, sp._sm[j]._col, sp._sm[j]._data)); j++; k++; } } return s; }*/ //实现稀疏矩阵的加法操作2 SparseMatrix operator+(const SparseMatrix& sp) { assert(_row == sp._row && _col == sp._col);//检测两个相加的矩阵行列是否相等 SparseMatrix ret; ret._row = _row; ret._col = _col; ret._invalid = _invalid; int iLidx = 0, iRidx = 0;//定义两个索引 while(iLidx <_sm.size() && iRidx (_sm[iLidx]._row, _sm[iLidx]._col, _sm[iLidx]._data)); iLidx++; } else if(AddrLeft > AddrRight) { ret._sm.push_back(Trituple(sp._sm[iRidx]._row, sp._sm[iRidx]._col, sp._sm[iRidx]._data)); iRidx++; } else//当左边等于右边判断相加后和是否为0，不为0放入 { Trituple temp(_sm[iLidx]); temp._data += sp._sm[iRidx]._data; if(temp._data) { ret._sm.push_back(temp); iLidx++; iRidx++; } } } while(iLidx <_sm.size())//左边还有剩余则放入剩余元素 { ret._sm.push_back(Trituple(_sm[iLidx]._row, _sm[iLidx]._col, _sm[iLidx]._data)); iLidx++; } while(iRidx (sp._sm[iRidx]._row, sp._sm[iRidx]._col, sp._sm[iRidx]._data)); iRidx++; } return ret; } private: size_t _row; size_t _col; vector> _sm; T _invalid;//无效值 }; int main() { int arr[6][5] = { {1,0,3,0,5}, {0,0,0,0,0}, {0,0,0,0,0}, {1,0,3,0,5}, {0,0,0,0,0}, {0,0,0,0,0}}; int arr1[6][5] = { {1,0,3,0,5}, {0,0,0,0,0}, {0,0,2,4,0}, {1,0,3,0,5}, {0,0,0,1,0}, {0,0,0,0,1}}; SparseMatrix s((int*)arr,6,5,0); SparseMatrix s1((int*)arr1,6,5,0); cout<<"访问三行四列元素"<