求源码（c++、c#）实现稀疏矩阵和位矩阵佛洛依德算法要求将矩阵的顶点放在文件中，结果也放在文件中（急用

稀疏矩阵代码如下
#include
#include
using namespace std;

template
//三元组
struct Trituple
{
int row;
int col;
T val;
};
//稀疏矩阵声明
template
class SparseMatrix
{
public:
SparseMatrix(int maxt=100);
~SparseMatrix();
bool TransposeTo(SparseMatrix &);
bool AddTo(const SparseMatrix&);
bool TransposeTo_Faster(SparseMatrix&);
void Input();
void Output();
private:
Trituple* data;
int rows,cols,terms;
int maxterms;
};
template
SparseMatrix::SparseMatrix(int maxt)
{
maxterms=maxt;
data=new Trituple[maxterms];
terms=rows=cols=0;
}
template
SparseMatrix::~SparseMatrix()
{
if (data!=NULL)
{
delete[] data;
}
}
//普通转置
template
bool SparseMatrix::TransposeTo(SparseMatrix &B)
{
if (terms>B.maxterms)
{
return false;
}
B.rows=cols;
B.cols=rows;
B.terms=terms;
if (terms>0)
{
int p=0;
for (int j=1;j<=cols;j++)
{
for (int k=0;k {
if (data[k].col==j)
{
B.data[p].row=j;
B.data[p].col=data[k].row;
B.data[p].val=data[k].val;
p++;
}
}
}
}
return true;
}
//快速转置
template
bool SparseMatrix::TransposeTo_Faster(SparseMatrix& B)
{
if (terms>B.maxterms)
{
return false;
}
B.rows=cols;
B.cols=rows;
B.terms=terms;
if (terms>0)
{
int *num,*cpot;
num=new int[cols];
cpot=new int[cols];
for (int j=0;j {
num[j]=0;
}
for (int k=0;k {
num[data[k].col-1]++;
}
//求出B中每一行的起始下标cpot[]
cpot[0]=0;
for (int j=1;j {
cpot[j]=cpot[j-1]+num[j-1];
}
//执行转置操作
for (int p,k=0;k {
p=cpot[data[k].col-1]++;
B.data[p].row=data[k].col;
B.data[p].col=data[k].row;
B.data[p].val=data[k].val;
}
delete[] num;
delete[] cpot;
}
return true;
}
template
void SparseMatrix::Input()
{
cout<<"intput the matrix' row:";
int row1;
cin>>row1;
cout<<"intput the matrix' col:";
int col1;
cin>>col1;
cout<<"input "< int number;
rows=row1;
cols=col1;
for (int i=0;i {
for (int j=0;j {
cin>>number;
if (number!=0)
{
data[terms].row=i+1;
data[terms].col=j+1;
data[terms].val=number;
terms++;
}
}
}
}
template //输出好看，但是违背了最初的原则
void SparseMatrix::Output()
{
T **tempArray=new T*[rows];
for (int i1=0;i1 {
tempArray[i1]=new int[cols];
}
for (int j=0;j {
for (int k=0;k {
tempArray[j][k]=0;
}
}
for (int i=0;i {
tempArray[data[i].row-1][data[i].col-1]=data[i].val;
}
for (int j=0;j {
for (int k=0;k {
cout< }
cout< }
for (int l=0;l {
delete[] tempArray[l];
}
delete tempArray;
cout<}
template
bool SparseMatrix::AddTo(const SparseMatrix& B)
{
if (rows!=B.rows||cols!=B.cols)
{
return false;
}
bool flag=false;
int tempTerms=terms;
for (int i=0;i {
flag=false;
for (int j=0;j {
if (data[j].col==B.data[i].col&&data[j].row==B.data[i].row)
{
data[j].val+=B.data[i].val;
flag=true;
}
}
if (flag==false)
{
data[++terms-1].col=B.data[i].col; //数组下标操作注意事项
data[terms-1].row=B.data[i].row;
data[terms-1].val=B.data[i].val;
}
}
return true;
}
int main()
{
cout<<"此程序演示稀疏矩阵的普通转置和快速转置操作"< SparseMatrix sm(50);
SparseMatrix sm1(50);
SparseMatrix sm2(50);
sm.Input();
cout<<"sm is"< sm.Output();
sm.TransposeTo(sm1);
cout<<"Transposition of sm is "< sm1.Output();
sm.TransposeTo_Faster(sm2);
cout<<"Transposition of sm is "< sm2.Output();
SparseMatrix sm3;
cout<<"input a new matrix"< sm3.Input();
cout<<"sm3 is"< sm3.Output();
if(sm.AddTo(sm3))
{
cout<<"after adding sm3 ,sm is"< sm.Output();
}
else
cout<<"the two matrix can't add"< cout<<"Good job!"< system("pause");
return 0;
}

这个这个，稀疏矩阵我就记得我学过，但是什么我早还老师了