• 图的遍历总结


    概念
      图的遍历有两种遍历方式:深度优先遍历(depth-first search)和广度优先遍历(breadth-first search)。
    1.深度优先遍历
      基本思路:首先从图中某个顶点V0出发,然后依次从V0相邻的顶点出发深度优先遍历,直至图中所有与V0路径相通的顶点都被访问了;若此时尚有顶点未被访问,则从中选一个顶点作为起始点,重复上述过程,直到所有的顶点都被访问。可以看出深度优先遍历是一个递归的过程。
        如下图中的一个无向图:
        
        其深度优先遍历得到的序列为:
        0->1->3->7->4->2->5->6
    2.广度优先遍历
        基本思路:首先,从图的某个顶点V0之后,访问了V0之后,依次访问与V0相邻的未被访问的顶点,然后分别从这些顶点出发,广度优先遍历,直至所有的顶点都被访问完。也是递归的问题。
        如上面图中
        其广度优先遍历得到的序列:
        0->1->2->3->4->2->5->6->7
    3.深度优先遍历和广度优先遍历区别
    • 广度优先搜索与深度优先搜索的时间复杂度相同,只是遍历顺序不同。

    深度优先搜索案例


    (Leetcode 173)
    * Implement an iterator over a binary search tree (BST). Your iterator will be initialized with the root node of a BST.
    * Calling next() will return the next smallest number in the BST.
    * Note: next() and hasNext() should run in average O(1) time and uses O(h) memory, where h is the height of the tree.
    public class BSTIterator {
    
        private List<Integer> list = new ArrayList<Integer>();
        int cursor = -1;
    
        public static class TreeNode{
            int val;
            TreeNode left;
            TreeNode right;
    
            public TreeNode(int val) {
                this.val = val;
            }
        }
    
        /**
         * Your BSTIterator will be called like this:
         * BSTIterator i = new BSTIterator(root);
         * while (i.hasNext()) v[f()] = i.next();
         */
    
        public BSTIterator(TreeNode root) {
            helper(root);
        }
      
        private void helper(TreeNode root) {
            if (root == null){
                return;
            }
            helper(root.left);
            list.add(root.val);
            helper(root.right);
        }
    
        /** @return whether we have a next smallest number */
        public boolean hasNext() {
            if (cursor < list.size()-1) return true;
            else return false;
        }
    
        /** @return the next smallest number */
        public int next() {
            cursor++;
            return list.get(cursor);
        }
    
    }

    广度搜索举例


    Leetcode 199
    Given a binary tree, return the level order traversal of its nodes' values. (ie, from left to right, level by level).
    For example:
    Given binary tree {3,9,20,#,#,15,7},
    3
    /
    9 20
    /
    15 7
    return its level order traversal as:
    [
    [3],
    [9,20],
    [15,7]
    ]
    树节点的定义:
    private class TreeNode{
            int val;
            TreeNode left;
            TreeNode right;
    
            public TreeNode(int val) {
                this.val = val;
            }
        }

    广度优先搜索遍历:

    public List<List<Integer>> levelOrder(TreeNode root) {
            List<List<Integer>> result = new ArrayList<List<Integer>>();
            List<TreeNode> layer = new ArrayList<TreeNode>();
    
            if (root != null){
                layer.add(root);
            }
    
            while (!layer.isEmpty()){
                List<Integer> vals = new ArrayList<Integer>();
                List<TreeNode> temp = new ArrayList<TreeNode>();
                for (int i = 0; i < layer.size(); i++) {
                    vals.add(layer.get(i).val);
                    TreeNode left = layer.get(i).left;
                    TreeNode right = layer.get(i).right;
                    if (left != null){
                        temp.add(left);
                    }
                    if (right != null){
                        temp.add(right);
                    }
                }
                result.add(vals);
                layer = temp;
            }
    
           return result;
        }

     



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  • 原文地址:https://www.cnblogs.com/chuji1988/p/4790117.html
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