Compression storage of symmetric matrices and symmetric matrices

Set a n*n square a,a any element a[i][j], when and only if a[i][j] = = A[j][i](0 <= i <= N-1 && 0 <= J <= n-1< /c10>), then matrix A is a symmetric matrix. Separated by the diagonal of the matrix, it is divided into upper and lower triangles.

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For example, symmetric matrix compression storage storage only need to store the upper triangle/lower triangle of data, under normal circumstances with the lower triangle storage, so up to N (n+1)/2 data.

The correspondence between symmetric matrices and compressed storage:

Lower triangle storage i>=j, Symmetricmatrix[i][j] = = array[i* (i+1)/2+j]

#define  _CRT_SECURE_NO_WARNINGS 1#include<iostream> #include <assert.h>using  Namespace std;template<class t>class symmetricmatrix{public:symmetricmatrix (T* array ,  size_t n) {_arraysize = n* (n + 1)  / 2;_size = n;_array  = new t[_arraysize];assert (Array);for  (size_t i = 0; i <  n; i++) {for  (size_t j = 0; j < n; j++) {_array[i* (i  + 1)  / 2 + j] = array[i*n + j];}} T& getpos (size_t row, size_t col)     //  get node {       //If the position is the upper triangle, using the symmetry principle, the row and column of the position can be exchanged if  (Row < col)    {swap (Row, col);} return _array[row* (row + 1)  / 2 + col];}  void display ()      //print {for  (int i = 0; i < _size; i++) {for  (int j = 0; j <  _size; j++) {if  (i >= j) {cout << _array[i* (i + 1)  /  2 + j] <<  " ";} else if  (i<j) {cout << _array[j* (j + 1)  / 2 + i]  <<  " ";}} Cout << endl;} Cout << endl;} private:t *_array;      //compression Matrix size_t _size;   //Phalanx Size _ size*_sizesize_t _arraysize;   //The total size of the compression matrix};int main () {int matrix[][5] =     {{ 0, 1, 2, 3, 4 },{ 1, 0, 1, 2,  3 },{ 2, 1, 0, 1, 2 },{ 3, 2, 1, 0, 1 } ,{ 4, 3, 2, 1, 0 },}; Symmetricmatrix<int> mat (int *) Matrix,  5);   //establishes a compression matrix and initializes the Mat.display () Cout << mat with matrix matrices. GetPos (1, 2)  << endl;system ("pause"); return 0;}

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This article from "Yan Anyang" blog, declined reproduced!

Compression storage of symmetric matrices and symmetric matrices