在这个例程中我们用类实现了节点、（无向图）连边、无向图，实现了节点度的计算、无向图聚类系数计算、度分布统计、无向图的Dijkstra算法（已知起止点计算最短路的算法）

#include <iostream>
#include<vector>
#include<set>
#include<unordered_map>
using namespace std;class Edge
{
public:int v1;int v2;int weight;Edge(int v1, int v2, int w){this->v1 = v1;this->v2 = v2;this->weight = w;}
};class DJPathInfo // 存放已知最短路
{
public:vector<vector<int>> shortest_path;vector<int> shortest_path_len;DJPathInfo(int n){vector<int> empty;this->shortest_path=vector<vector<int>>(n, empty);this->shortest_path_len= vector<int>(n, 0);}
};class Node
{
public:std::vector<Edge> edges;int id;Node(int i){this->id = i;}int degree(){return this->edges.size();}vector<int> neighbors(){vector<int> res;if (this->edges.size() > 0){for (auto edge : this->edges){if (edge.v1 == this->id) res.push_back(edge.v2);else res.push_back(edge.v1);}return res;}else return res;}float cluster_coeff(vector<vector<bool>> adj_mat){int num_neighbor = this->edges.size() - 1;if (num_neighbor < 2) return 0;vector<int> neighbors = this->neighbors();float E = 0; //邻居之间的边数for (auto i : neighbors){for (auto j : neighbors){if (i >= j) continue;if (adj_mat[i][j] == true) E++;}}cout << 2 * E / (neighbors.size() * (neighbors.size() - 1)) << endl;return 2 * E / (neighbors.size() * (neighbors.size() - 1));}
};class Graph
{
public:vector<vector<bool>> adj_mat;vector<vector<float>> w_mat;int node_num;vector<Edge> edges;vector<Node> nodes;Graph(vector<vector<bool>> A, vector<vector<float>> W){this->adj_mat = A;this->w_mat = W;this->node_num = A.size();for (int i = 0; i < node_num; i++) this->nodes.push_back(Node(i));for (int i = 0; i < node_num; i++)for (int j = 0; j < i; j++){if (A[i][j] == true) this->add_edge(i, j, W[i][j]);}}Graph(int n){vector<float> zero(n, 0);vector<bool> all_false(n, false);vector<vector<bool>> A(n, all_false);vector<vector<float>> W(n, zero);this->adj_mat = A;this->w_mat = W;this->node_num = A.size();for (int i = 0; i < node_num; i++) this->nodes.push_back(Node(i));for (int i = 0; i < node_num; i++)for (int j = 0; j < i; j++){if (A[i][j] == true) this->add_edge(i, j, W[i][j]);}}void add_edge(int id1, int id2, int weight){Edge e = Edge(id1, id2, weight);this->adj_mat[id1][id2] = true;this->adj_mat[id2][id1] = true;this->w_mat[id1][id2] = weight;this->w_mat[id2][id1] = weight;this->edges.push_back(e);this->nodes[id1].edges.push_back(e);this->nodes[id2].edges.push_back(e);}void tell_info(){for (auto v : this->nodes){std::cout << "Node ID:" << v.id << std::endl;std::cout << "Neighbor/Weight:";for (auto i : v.neighbors()) cout <<'(' << i<<','<< this->w_mat[v.id][i] << ')' << ',';std::cout<<std::endl;}}vector<int> DJ(int s, int dest) // Dijkstra算法{DJPathInfo info(this->nodes.size());vector<int> res = {s};set<int> S;S.insert(s);set<int> U;for (auto v : this->nodes[s].neighbors()) U.insert(v);if (U.size() == 0) return res;for (auto v : U){info.shortest_path[v].push_back(v);info.shortest_path_len[v] = this->w_mat[s][v];}info.shortest_path_len[s] = 0;while (U.size() != 0){int n = *U.begin();int n_len = info.shortest_path_len[n];for (auto it = U.begin(); it != U.end(); it++){if (info.shortest_path_len[n] > info.shortest_path_len[*it]){n = *it;n_len = info.shortest_path_len[*it];}}S.insert(n);U.erase(n);for (auto v : this->nodes[n].neighbors()){if (S.find(v) != S.end()) continue;U.insert(v);if (info.shortest_path[v].size() == 0){info.shortest_path[v] = info.shortest_path[n];info.shortest_path[v].push_back(v);info.shortest_path_len[v] = info.shortest_path_len[n] + this->w_mat[n][v];continue;}if (info.shortest_path_len[n] + this->w_mat[n][v] < info.shortest_path_len[v]){info.shortest_path[v] = info.shortest_path[n];info.shortest_path[v].push_back(v);info.shortest_path_len[v] = info.shortest_path_len[n] + this->w_mat[n][v];}}}if (S.find(dest) != S.end()){for (auto v : info.shortest_path[dest]) res.push_back(v);info.shortest_path_len[dest];}return res;}float cluster_coeff(){float res=0;for (auto node : this->nodes) res += node.cluster_coeff(this->adj_mat);return res / float(this->nodes.size());}void degree_distribution() // 度分布{vector<float> res;unordered_map<int, int> degree_count;for (auto v : this->nodes){degree_count.emplace(v.degree(), 0);}for (auto v : this->nodes){degree_count[v.degree()]++;}for (auto it : degree_count){std::cout << "degree =" << it.first << ', '<<" prob=" << float(it.second) / this->nodes.size() << endl;}}
};int main()
{Graph G = Graph(11);G.add_edge(0, 1, 2);G.add_edge(0, 2, 9);G.add_edge(0, 3, 1);G.add_edge(1, 4, 1);G.add_edge(1, 2, 6);G.add_edge(2, 4, 5);G.add_edge(2, 5, 1);G.add_edge(2, 6, 2);G.add_edge(2, 3, 7);G.add_edge(3, 6, 9);G.add_edge(4, 7, 2);G.add_edge(4, 8, 9);G.add_edge(4, 5, 3);G.add_edge(5, 8, 6);G.add_edge(5, 6, 4);G.add_edge(6, 8, 3);G.add_edge(6, 9, 1);G.add_edge(7, 8, 7);G.add_edge(7, 10, 9);G.add_edge(8, 10, 2);G.add_edge(8, 9, 1);G.add_edge(9, 10, 4);G.tell_info();cout << "Djkstra Test: shortest 0 -> 10: ";for (const auto& p : G.DJ(0, 10)) cout << p << ',';cout<<endl;cout << "clustring coefficient=" << G.cluster_coeff() << endl;cout << "degree distribution:"  << endl;G.degree_distribution();return 0;
}