本文整理汇总了C++中graph::num_of_vertices方法的典型用法代码示例。如果您正苦于以下问题：C++ graph::num_of_vertices方法的具体用法？C++ graph::num_of_vertices怎么用？C++ graph::num_of_vertices使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类graph的用法示例。
在下文中一共展示了graph::num_of_vertices方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: prim
void mst::prim(graph g) {
int num = g.num_of_vertices();
minheap* candidates = new minheap(num);
reset();
// find the starting point and initialize the heap
int start_node = 0;
while(candidates->size() == 0) {
for(int i=0; i<num; ++i) {
float c = g.cost(start_node, i);
if (c != 0) candidates->update(c, i);
}
++start_node;
}
closed_set.insert(start_node-1);
while (candidates->size()!=0) {
heapitem t = candidates->pop();
int node = t.get_node();
// not record the duplicated probed nodes
if (closed_set.find(node)!=closed_set.end())
continue;
closed_set.insert(node);
path_cost += t.get_key();
vector<int> n = g.neighbors(node);
// update the heap with newly found nodes and edges
for(vector<int>::iterator i=n.begin(); i!=n.end(); ++i) {
candidates->update(g.cost(node,*i), *i);
}
}
// ckeck if there are isolated nodes
if (closed_set.size() < num-1) path_cost=-1;
}示例2: kruskal
void mst::kruskal(graph g) {
int num = g.num_of_vertices();
vector< vector<float> > edges;
union_find explored;
reset();
// put all connected vertices in "edges"
for(int i=0; i<num; ++i) {
for(int j=0; j<num; ++j) {
float c = g.cost(i, j);
if (c!=0) {
vector<float> temp;
temp.push_back(i);
temp.push_back(j);
temp.push_back(c);
edges.push_back(temp);
}
}
}
sort(edges.begin(), edges.end(), kruskal_compare);
for(vector<vector<float> >::iterator p=edges.begin(); p!=edges.end(); ++p) {
// both nodes in the closed set ==> detecting a cycle
vector<float> temp = *p;
int f1 = explored.find(temp[0]);
int f2 = explored.find(temp[1]);
if(f1!=-1 && f2!=-1 && f1==f2) continue;
path_cost += temp[2];
explored.insert(temp[0], temp[1]);
//cout <<"From "<<temp[0]<<" To "<<temp[1]<<" -- Cost "<<temp[2]<<endl;
}
// ckeck if there are isolated nodes
if (explored.num_of_unions() != 1) path_cost=-1;
}示例3: path
// calculate the path using dijkstra's algo.
void dijkstra::path(graph g, int u, int v) {
int num = g.num_of_vertices();
minheap* candidates = new minheap(num);
// reset the path_cost and clear the closed_set
reset();
// initialize the heap
// the nodes in the heap are those of "open set"
for (int i=0; i<num; ++i) {
float c = g.cost(u, i);
if (c!=0)
candidates->update(c, i);
}
while (candidates->size()!=0) {
heapitem t = candidates->pop();
int node = t.get_node();
// not record the duplicated probed nodes
if (closed_set.find(node)!=closed_set.end())
continue;
closed_set.insert(node);
path_cost = t.get_key();
// terminated if arrives at the destination
if (node == v)
return;
vector<int> n = g.neighbors(node);
// update the heap with newly found nodes
for(vector<int>::iterator i=n.begin(); i!=n.end(); ++i) {
candidates->update(path_cost+g.cost(node,*i), *i);
}
}
// after iteration, the v is not found
path_cost = -1;
}