Clone Graph

06/28/2016 Graph Depth First Search Breadth First Search

Question

Question Description Clone an undirected graph. Each node in the graph contains a label and a list of its neighbors.

OJ’s undirected graph serialization: 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 #.

  1. First node is labeled as 0. Connect node 0 to both nodes 1 and 2.
  2. Second node is labeled as 1. Connect node 1 to node 2.
  3. Third node is labeled as 2. Connect node 2 to node 2 (itself), thus forming a self-cycle.

Visually, the graph looks like the following:

       1
      / \
     /   \
    0 --- 2
         / \
         \_/

Solution

Result: Accepted Time: 78 ms

Here should be some explanations.

class Solution {
public:
    UndirectedGraphNode *cloneGraph(UndirectedGraphNode *node) {
        unordered_map<int,UndirectedGraphNode *> mp;
        queue<UndirectedGraphNode *> que;
        UndirectedGraphNode * root = NULL;
        if(node)
        {
            root = new UndirectedGraphNode(node->label);
            que.push(node); que.push(root);
            mp[root->label] = root;
        }
        while(!que.empty())
        {
            UndirectedGraphNode * old_node = que.front();que.pop();
            UndirectedGraphNode * new_node = que.front();que.pop();
            for(const auto & x:old_node->neighbors)
                if(mp.count(x->label))
                    new_node->neighbors.push_back(mp[x->label]);
                else
                {
                    UndirectedGraphNode * tmp = new UndirectedGraphNode(x->label);
                    new_node->neighbors.push_back(tmp);
                    mp[x->label] = tmp;
                    que.push(x);que.push(tmp);
                }
        }
        return root;
    }
};

Complexity Analytics

  • Time Complexity:
  • Space Complexity: