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Clone an undirected graph. Each node in the graph contains a label and a list of its neighbors.
Nodes are labeled uniquely.
We use# as a separator for each node, and , as a separator for node label and each neighbor of the node.
As an example, consider the serialized graph {0,1,2#1,2#2,2}.
The graph has a total of three nodes, and therefore contains three parts as separated by #.
0. Connect node 0 to both nodes 1 and 2.1. Connect node 1 to node 2.2. Connect node 2 to node 2 (itself), thus forming a self-cycle.
Visually, the graph looks like the following:
1
/ / 0 --- 2
/ \_/
Depth-first Search Breadth-first Search Graph
这里我们使用Map来进行区分，Map的key值为原来的node，value为新clone的node，当发现一个node未在map中时说明这个node还未被clone，
将它clone后放入queue中处理neighbors。
使用Map的主要意义在于充当BFS中Visited数组，它也可以去环问题，例如A--B有条边，当处理完A的邻居node，然后处理B节点邻居node时发现A已经处理过了
处理就结束，不会出现死循环！
/** * Definition for undirected graph. * struct UndirectedGraphNode { * int label; * vector<UndirectedGraphNode *> neighbors; * UndirectedGraphNode(int x) : label(x) {}; * }; */ class Solution { public: UndirectedGraphNode *cloneGraph(UndirectedGraphNode *node) { if(node == NULL) return NULL; map <UndirectedGraphNode*, UndirectedGraphNode*> old2New; queue <UndirectedGraphNode*> q; UndirectedGraphNode* oldNode = NULL; // each node in queue is already copied itself // but neighbors are not copied yet old2New[node] = new UndirectedGraphNode(node->label); q.push(node); while(!q.empty()) { oldNode = q.front(); q.pop(); for(int i = 0; i < oldNode->neighbors.size(); i++) { if(oldNode->neighbors[i] != NULL) { if(old2New.count(oldNode->neighbors[i]) != 0) { old2New[oldNode]->neighbors.push_back(old2New[oldNode->neighbors[i]]); } else { UndirectedGraphNode* tmp = new UndirectedGraphNode(oldNode->neighbors[i]->label); old2New[oldNode->neighbors[i]] = tmp;//build the mapping old2New[oldNode]->neighbors.push_back(tmp); // add it to queue after copy it if the node doesn‘t the map q.push(oldNode->neighbors[i]); } } } } return old2New[node]; } };
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原文地址：http://www.cnblogs.com/diegodu/p/4554189.html
