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  • Binary Tree
    • 107. Binary Tree Level Order Traversal II
    • Lowest Common Ancestor of a Binary Tree
    • Lowest Common Ancestor of a Binary Tree II
    • Lowest Common Ancestor III
    • preorder Traversal
    • Inorder traversal
    • Binary Tree Path
    • post Order traversal
    • Level Traversal
    • Serialize and Deserialize Binary Tree 07/25
    • Find Leaves of Binary Tree 07/25
    • Sum of Left Leaves 07/25
    • Recover Binary Search Tree 07/26
    • Check Full Binary Tree 07/26
    • Binary Tree Longest Consecutive Sequence07/26
    • Equal Tree Partition 07/27
    • Same Tree 07/27
    • Sum Root to Leaf Numbers 07/26
    • Binary Search Tree Iterator 07/28
    • Preorder morris traversal 07/29
    • inorder traversal morris 07/29
  • BFS
    • Search Graph Nodes 07/30
    • Is Graph Bipartite? 07/30
    • Walls and Gates 07/30
    • Clone Graph 07/30
    • Word Ladder 07/30
    • Topological Sorting 08/01
    • Course Schedule 08/03
    • Course Schedule II 08/04
  • DFS
    • Target Sum 08/06
    • Minimum Subtree 08/07
    • Word Search 08/07
    • Pacific Atlantic Water Flow 08/08
    • Matrix Water Injection 08/10
    • Maximum Subtree 08/10
  • Dynamic Programming
    • 931. Minimum Falling Path Sum
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    • Partition List
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    • Linked List Cycle II
    • Delete Node in a Linked List
    • Reverse Nodes in k-Group
    • Rotate List
    • Reverse Linked List II
  • Arrays
    • 189. Rotate Array
    • 80. Remove Duplicates from Sorted Array II
    • 26. Remove Duplicates from Sorted Array
    • 628. Maximum Product of Three Numbers
    • 48. Rotate Image
    • 289. Game of Life
    • 334. Increasing Triplet Subsequence
    • 11. Container With Most Water
    • 122.Best Time to Buy and Sell Stock II
    • 274. H-Index
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    • 118. Pascal's Triangle
    • Sort Colors
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    • First Missing Positive
  • Strings
    • 93. Restore IP Addresses
    • 71. Simplify Path
    • 43. Multiply Strings
    • 606. Construct String from Binary Tree
    • 917. Reverse Only Letters
    • 929.Unique Email Addresses
    • Valid Anagram
    • Compare Strings
    • Anagrams
    • Longest Common Prefix
    • Implement strStr()
    • String to Integer (atoi)
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  1. BFS

Clone Graph 07/30

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

How we serialize an undirected graph:

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
     / \
     \_/

Have you met this question in a real interview? Yes

Example

return a deep copied graph.

先把图里的所有node,用宽度有限搜索存起来,然后用hashmap建立旧node和新node的一一对应,然后遍历每一个node的邻居,根据这个邻居,来找到对应的信建立的node,也就是map的value,然后把找到的对应的旧邻居的新邻居,加到对应的点的邻居队列里

/**
 * Definition for undirected graph.
 * class UndirectedGraphNode {
 *     int label;
 *     ArrayList<UndirectedGraphNode> neighbors;
 *     UndirectedGraphNode(int x) { label = x; neighbors = new ArrayList<UndirectedGraphNode>(); }
 * };
 */


public class Solution {
    /*
     * @param node: A undirected graph node
     * @return: A undirected graph node
     */
    public UndirectedGraphNode cloneGraph(UndirectedGraphNode node) {
        // write your code here
        
        if(node == null){
            return node;
        }
        
        List<UndirectedGraphNode> list = getNodeList(node);
        
        
        HashMap<UndirectedGraphNode,UndirectedGraphNode> map = new HashMap<>();
        
        
        for(UndirectedGraphNode n : list){
            map.put(n,new UndirectedGraphNode(n.label));
        }
        
        
        for(UndirectedGraphNode n : list){
            ArrayList<UndirectedGraphNode> nei = n.neighbors;
             UndirectedGraphNode newNode = map.get(n);
            for(UndirectedGraphNode m : nei){
               UndirectedGraphNode newNeib = map.get(m);
               newNode.neighbors.add(newNeib);
                
            }
        }
        
        return map.get(node);
    }
    
    public List<UndirectedGraphNode> getNodeList(UndirectedGraphNode node){
        
        Queue<UndirectedGraphNode> queue = new LinkedList<>();
        Set<UndirectedGraphNode> set = new HashSet<>();
        
        queue.offer(node);
        set.add(node);
        
        while(!queue.isEmpty()){
            UndirectedGraphNode top = queue.poll();
            
            for(UndirectedGraphNode n : top.neighbors){
                if(!set.contains(n)){
                    set.add(n);
                    queue.offer(n);
                }
            }
            
            
        }
        
        return new ArrayList<UndirectedGraphNode>(set);
    }
}
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Last updated 6 years ago