在游戏中,常常遇到路径规划问题,用到图的相关算法,我们以简单图来学习。
图通常有两种表示方式,矩阵和邻接表。矩阵表示简单,运算快,但当矩阵是稀疏矩阵的时候就存在空间浪费的问题,并且效率也会下降,而邻接表节约空间,并且由于边是连续访问,时间效率也比较高。在本文中,我们将以邻接表来表示图。
#include<queue>
#include<stack>
using namespace std;
struct SE{
int vIndex;
int tag;
SE* next;
};
struct SMap{
SE* pE;
int nnode;
};
void visit(SE *se){
printf("%d\n", se->vIndex);
}
SMap* create_map(int matrix[][6], int n){
SMap* pMap = new SMap();
pMap->nnode = n;
pMap->pE = new SE[n];
memset(pMap->pE, 0, n*sizeof(SE));
for (int i = 0; i<n; i++){
pMap->pE[i].vIndex = i;
pMap->pE[i].tag = 0;
SE* p = &pMap->pE[i];
for (int j = 0; j<n; j++){
if (matrix[i][j] != 0){
p->next = new SE();
p->next->vIndex = j;
p->next->tag = 0;
p->next->next = NULL;
p = p->next;
}
}
}
return pMap;
}
int BFS(SMap* pMap, int n){
queue<SE*> q;
for (int i = 0; i < n; i++){
if (pMap->pE[i].tag == 0){
q.push(&pMap->pE[i]);
while (!q.empty()){
SE *se = q.front();
q.pop();
if (pMap->pE[se->vIndex].tag == 1){
continue;
}
visit(se);
pMap->pE[se->vIndex].tag = 1;
SE * p = se;
while (p->next){
p = p->next;
if (pMap->pE[p->vIndex].tag == 0){
q.push(p);
}
}
}
}
}
return 0;
}
int DFS(SMap* pMap, int n){
stack<SE*> s;
for (int i = 0; i < n; i++){
if (pMap->pE[i].tag == 0){
s.push(&pMap->pE[i]);
while (!s.empty()){
SE *se = s.top();
s.pop();
if (pMap->pE[se->vIndex].tag == 1){
continue;
}
visit(se);
pMap->pE[se->vIndex].tag = 1;
SE * p = &pMap->pE[se->vIndex];
stack<SE*> tmp;
while (p->next){
p = p->next;
if (pMap->pE[p->vIndex].tag == 0){
tmp.push(p);
}
}
while (!tmp.empty()){
s.push(tmp.top());
tmp.pop();
}
}
}
}
return 0;
}
int main(){
int map[6][6] = {
{ 0, 1, 0, 1, 0, 0 },
{ 1, 0, 1, 1, 1, 0 },
{ 0, 1, 0, 1, 0, 0 },
{ 1, 1, 1, 0, 1, 0 },
{ 0, 1, 0, 1, 0, 1 },
{ 0, 0, 0, 0, 1, 0 }
};
SMap* smap = create_map(map, 6);
// BFS(smap, 6);
DFS(smap, 6);
return 0;
}