玩转数据结构:第6章 二分搜索树
二分搜索树
6-1 为什么要研究树结构
树结构
为什么要有树结构?
- 树结构本身是一种天然的组织结构
- 高效
将数据使用树结构存储后,出奇的高效。
- 二分搜索树(Binary Search Tree)
- 平衡二叉树:AVL;红黑树
- 堆;并查集
- 线段树;Trie(字典树,前缀树)
6-2 二分搜索树基础
和链表一样,动态数据结构。
二叉树,具有天然递归结构。
- 每个节点的左子树也是二叉树
- 每个节点的右子树也是二叉树
- 二叉树每个节点最多有一个父亲
二分搜索树 Binary Search Tree
二分搜索树是二叉树
二分搜索树,存储的元素必须有可比较性。
BST.java
public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } }
6-3 向二分搜索树中添加元素
03-Add-Elements-in-BST
BST.java
public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ if(root == null){ root = new Node(e); size ++; } else add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 private void add(Node node, E e){ if(e.equals(node.e)) return; else if(e.compareTo(node.e) < 0 && node.left == null){ node.left = new Node(e); size ++; return; } else if(e.compareTo(node.e) > 0 && node.right == null){ node.right = new Node(e); size ++; return; } if(e.compareTo(node.e) < 0) add(node.left, e); else //e.compareTo(node.e) > 0 add(node.right, e); } }
6-4 改进添加操作:深入理解递归终止条件
04-Improved-Add-Elements-in-BST
public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } }
6-5 二分搜索树的查询操作
05-Search-in-BST
public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } }
6-6 二分搜索树的前序遍历
06-PreOrder-Traverse-in-BST
public class Main { public static void main(String[] args) { BST<Integer> bst = new BST<>(); int[] nums = {5, 3, 6, 8, 4, 2}; for(int num: nums) bst.add(num); ///////////////// // 5 // // / \ // // 3 6 // // / \ \ // // 2 4 8 // ///////////////// bst.preOrder(); System.out.println(); System.out.println(bst); } }
BST.java
public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } // 二分搜索树的前序遍历 public void preOrder(){ preOrder(root); } // 前序遍历以node为根的二分搜索树, 递归算法 private void preOrder(Node node){ if(node == null) return; System.out.println(node.e); preOrder(node.left); preOrder(node.right); } @Override public String toString(){ StringBuilder res = new StringBuilder(); generateBSTString(root, 0, res); return res.toString(); } // 生成以node为根节点,深度为depth的描述二叉树的字符串 private void generateBSTString(Node node, int depth, StringBuilder res){ if(node == null){ res.append(generateDepthString(depth) + "null\n"); return; } res.append(generateDepthString(depth) + node.e + "\n"); generateBSTString(node.left, depth + 1, res); generateBSTString(node.right, depth + 1, res); } private String generateDepthString(int depth){ StringBuilder res = new StringBuilder(); for(int i = 0 ; i < depth ; i ++) res.append("--"); return res.toString(); } }
6-7 二分搜索树的中序遍历和后序遍历
07-InOrder-and-PostOrder-Traverse-in-BST
public class Main { public static void main(String[] args) { BST<Integer> bst = new BST<>(); int[] nums = {5, 3, 6, 8, 4, 2}; for(int num: nums) bst.add(num); ///////////////// // 5 // // / \ // // 3 6 // // / \ \ // // 2 4 8 // ///////////////// bst.preOrder(); System.out.println(); bst.inOrder(); System.out.println(); bst.postOrder(); System.out.println(); } }
BST.java
import java.util.Stack; public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } // 二分搜索树的前序遍历 public void preOrder(){ preOrder(root); } // 前序遍历以node为根的二分搜索树, 递归算法 private void preOrder(Node node){ if(node == null) return; System.out.println(node.e); preOrder(node.left); preOrder(node.right); } // 二分搜索树的中序遍历 public void inOrder(){ inOrder(root); } // 中序遍历以node为根的二分搜索树, 递归算法 private void inOrder(Node node){ if(node == null) return; inOrder(node.left); System.out.println(node.e); inOrder(node.right); } // 二分搜索树的后序遍历 public void postOrder(){ postOrder(root); } // 后序遍历以node为根的二分搜索树, 递归算法 private void postOrder(Node node){ if(node == null) return; postOrder(node.left); postOrder(node.right); System.out.println(node.e); } @Override public String toString(){ StringBuilder res = new StringBuilder(); generateString(root, 0, res); return res.toString(); } // 生成以node为根节点,深度为depth的描述二叉树的字符串 private void generateString(Node node, int depth, StringBuilder res){ if(node == null){ res.append(generateDepthString(depth) + "null\n"); return; } res.append(generateDepthString(depth) + node.e + "\n"); generateString(node.left, depth + 1, res); generateString(node.right, depth + 1, res); } private String generateDepthString(int depth){ StringBuilder res = new StringBuilder(); for(int i = 0 ; i < depth ; i ++) res.append("--"); return res.toString(); } }
6-8 深入理解二分搜索树的前中后序遍历
6-9 二分搜索树前序遍历的非递归实现
/// Leetcode 144. Binary Tree Preorder Traversal
/// https://leetcode.com/problems/binary-tree-preorder-traversal/description/
09-Non-Recursion-Preorder-Traverse-in-BST
public class Main { public static void main(String[] args) { BST<Integer> bst = new BST<>(); int[] nums = {5, 3, 6, 8, 4, 2}; for(int num: nums) bst.add(num); ///////////////// // 5 // // / \ // // 3 6 // // / \ \ // // 2 4 8 // ///////////////// bst.preOrder(); System.out.println(); bst.preOrderNR(); System.out.println(); } }
BST.java
import java.util.Stack; public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } // 二分搜索树的前序遍历 public void preOrder(){ preOrder(root); } // 前序遍历以node为根的二分搜索树, 递归算法 private void preOrder(Node node){ if(node == null) return; System.out.println(node.e); preOrder(node.left); preOrder(node.right); } // 二分搜索树的非递归前序遍历 public void preOrderNR(){ if(root == null) return; Stack<Node> stack = new Stack<>(); stack.push(root); while(!stack.isEmpty()){ Node cur = stack.pop(); System.out.println(cur.e); if(cur.right != null) stack.push(cur.right); if(cur.left != null) stack.push(cur.left); } } @Override public String toString(){ StringBuilder res = new StringBuilder(); generateString(root, 0, res); return res.toString(); } // 生成以node为根节点,深度为depth的描述二叉树的字符串 private void generateString(Node node, int depth, StringBuilder res){ if(node == null){ res.append(generateDepthString(depth) + "null\n"); return; } res.append(generateDepthString(depth) + node.e + "\n"); generateString(node.left, depth + 1, res); generateString(node.right, depth + 1, res); } private String generateDepthString(int depth){ StringBuilder res = new StringBuilder(); for(int i = 0 ; i < depth ; i ++) res.append("--"); return res.toString(); } }
Solution
/// Leetcode 144. Binary Tree Preorder Traversal /// https://leetcode.com/problems/binary-tree-preorder-traversal/description/ /// /// 课程中在这里暂时没有介绍这个问题 /// 该代码主要用于使用Leetcode上的问题测试我们的BST类 /// 该测试主要测试前序遍历的非递归写法 import java.util.List; import java.util.LinkedList; import java.util.Stack; public class Solution { // Definition for a binary tree node. public class TreeNode { int val; TreeNode left; TreeNode right; TreeNode(int x) { val = x; } } public List<Integer> preorderTraversal(TreeNode root) { List<Integer> res = new LinkedList<>(); if(root == null) return res; Stack<TreeNode> stack = new Stack<>(); stack.push(root); while(!stack.isEmpty()){ TreeNode cur = stack.pop(); res.add(cur.val); if(cur.right != null) stack.push(cur.right); if(cur.left != null) stack.push(cur.left); } return res; } }
遍历过程中一扎到底,就是所谓的“深度优先遍历”
6-10 二分搜索树的层序遍历
10-Level-Traverse-in-BST
public class Main { public static void main(String[] args) { BST<Integer> bst = new BST<>(); int[] nums = {5, 3, 6, 8, 4, 2}; for(int num: nums) bst.add(num); ///////////////// // 5 // // / \ // // 3 6 // // / \ \ // // 2 4 8 // ///////////////// bst.preOrder(); System.out.println(); bst.inOrder(); System.out.println(); bst.postOrder(); System.out.println(); bst.levelOrder(); System.out.println(); } }
BST.java
import java.util.Stack; import java.util.Queue; import java.util.LinkedList; public class BST<E extends Comparable<E>> { private class Node { public E e; public Node left, right; public Node(E e) { this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } // 二分搜索树的前序遍历 public void preOrder(){ preOrder(root); } // 前序遍历以node为根的二分搜索树, 递归算法 private void preOrder(Node node){ if(node == null) return; System.out.println(node.e); preOrder(node.left); preOrder(node.right); } // 二分搜索树的非递归前序遍历 public void preOrderNR(){ Stack<Node> stack = new Stack<>(); stack.push(root); while(!stack.isEmpty()){ Node cur = stack.pop(); System.out.println(cur.e); if(cur.right != null) stack.push(cur.right); if(cur.left != null) stack.push(cur.left); } } // 二分搜索树的中序遍历 public void inOrder(){ inOrder(root); } // 中序遍历以node为根的二分搜索树, 递归算法 private void inOrder(Node node){ if(node == null) return; inOrder(node.left); System.out.println(node.e); inOrder(node.right); } // 二分搜索树的后序遍历 public void postOrder(){ postOrder(root); } // 后序遍历以node为根的二分搜索树, 递归算法 private void postOrder(Node node){ if(node == null) return; postOrder(node.left); postOrder(node.right); System.out.println(node.e); } // 二分搜索树的层序遍历 public void levelOrder(){ if(root == null) return; Queue<Node> q = new LinkedList<>(); q.add(root); while(!q.isEmpty()){ Node cur = q.remove(); System.out.println(cur.e); if(cur.left != null) q.add(cur.left); if(cur.right != null) q.add(cur.right); } } @Override public String toString(){ StringBuilder res = new StringBuilder(); generateString(root, 0, res); return res.toString(); } // 生成以node为根节点,深度为depth的描述二叉树的字符串 private void generateString(Node node, int depth, StringBuilder res){ if(node == null){ res.append(generateDepthString(depth) + "null\n"); return; } res.append(generateDepthString(depth) + node.e + "\n"); generateString(node.left, depth + 1, res); generateString(node.right, depth + 1, res); } private String generateDepthString(int depth){ StringBuilder res = new StringBuilder(); for(int i = 0 ; i < depth ; i ++) res.append("--"); return res.toString(); } }
广度优先遍历的意义
常用于算法设计中——最短路径,更快的找到问题的解
6-11 删除二分搜索树的最大元素和最小元素
11-Remove-Min-and-Max-in-BST
import java.util.ArrayList; import java.util.Random; public class Main { public static void main(String[] args) { BST<Integer> bst = new BST<>(); Random random = new Random(); int n = 1000; // test removeMin for(int i = 0 ; i < n ; i ++) bst.add(random.nextInt(10000)); ArrayList<Integer> nums = new ArrayList<>(); while(!bst.isEmpty()) nums.add(bst.removeMin()); System.out.println(nums); for(int i = 1 ; i < nums.size() ; i ++) if(nums.get(i - 1) > nums.get(i)) throw new IllegalArgumentException("Error!"); System.out.println("removeMin test completed."); // test removeMax for(int i = 0 ; i < n ; i ++) bst.add(random.nextInt(10000)); nums = new ArrayList<>(); while(!bst.isEmpty()) nums.add(bst.removeMax()); System.out.println(nums); for(int i = 1 ; i < nums.size() ; i ++) if(nums.get(i - 1) < nums.get(i)) throw new IllegalArgumentException("Error!"); System.out.println("removeMax test completed."); } }
BST.java
import java.util.LinkedList; import java.util.Queue; import java.util.Stack; public class BST<E extends Comparable<E>> { private class Node{ public E e; public Node left, right; public Node(E e){ this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } // 二分搜索树的前序遍历 public void preOrder(){ preOrder(root); } // 前序遍历以node为根的二分搜索树, 递归算法 private void preOrder(Node node){ if(node == null) return; System.out.println(node.e); preOrder(node.left); preOrder(node.right); } // 二分搜索树的非递归前序遍历 public void preOrderNR(){ Stack<Node> stack = new Stack<>(); stack.push(root); while(!stack.isEmpty()){ Node cur = stack.pop(); System.out.println(cur.e); if(cur.right != null) stack.push(cur.right); if(cur.left != null) stack.push(cur.left); } } // 二分搜索树的中序遍历 public void inOrder(){ inOrder(root); } // 中序遍历以node为根的二分搜索树, 递归算法 private void inOrder(Node node){ if(node == null) return; inOrder(node.left); System.out.println(node.e); inOrder(node.right); } // 二分搜索树的后序遍历 public void postOrder(){ postOrder(root); } // 后序遍历以node为根的二分搜索树, 递归算法 private void postOrder(Node node){ if(node == null) return; postOrder(node.left); postOrder(node.right); System.out.println(node.e); } // 二分搜索树的层序遍历 public void levelOrder(){ Queue<Node> q = new LinkedList<>(); q.add(root); while(!q.isEmpty()){ Node cur = q.remove(); System.out.println(cur.e); if(cur.left != null) q.add(cur.left); if(cur.right != null) q.add(cur.right); } } // 寻找二分搜索树的最小元素 public E minimum(){ if(size == 0) throw new IllegalArgumentException("BST is empty"); Node minNode = minimum(root); return minNode.e; } // 返回以node为根的二分搜索树的最小值所在的节点 private Node minimum(Node node){ if( node.left == null ) return node; return minimum(node.left); } // 寻找二分搜索树的最大元素 public E maximum(){ if(size == 0) throw new IllegalArgumentException("BST is empty"); return maximum(root).e; } // 返回以node为根的二分搜索树的最大值所在的节点 private Node maximum(Node node){ if( node.right == null ) return node; return maximum(node.right); } // 从二分搜索树中删除最小值所在节点, 返回最小值 public E removeMin(){ E ret = minimum(); root = removeMin(root); return ret; } // 删除掉以node为根的二分搜索树中的最小节点 // 返回删除节点后新的二分搜索树的根 private Node removeMin(Node node){ if(node.left == null){ Node rightNode = node.right; node.right = null; size --; return rightNode; } node.left = removeMin(node.left); return node; } // 从二分搜索树中删除最大值所在节点 public E removeMax(){ E ret = maximum(); root = removeMax(root); return ret; } // 删除掉以node为根的二分搜索树中的最大节点 // 返回删除节点后新的二分搜索树的根 private Node removeMax(Node node){ if(node.right == null){ Node leftNode = node.left; node.left = null; size --; return leftNode; } node.right = removeMax(node.right); return node; } @Override public String toString(){ StringBuilder res = new StringBuilder(); generateBSTString(root, 0, res); return res.toString(); } // 生成以node为根节点,深度为depth的描述二叉树的字符串 private void generateBSTString(Node node, int depth, StringBuilder res){ if(node == null){ res.append(generateDepthString(depth) + "null\n"); return; } res.append(generateDepthString(depth) + node.e +"\n"); generateBSTString(node.left, depth + 1, res); generateBSTString(node.right, depth + 1, res); } private String generateDepthString(int depth){ StringBuilder res = new StringBuilder(); for(int i = 0 ; i < depth ; i ++) res.append("--"); return res.toString(); } }
6-12 删除二分搜索树的任意元素
12-Remove-Elements-in-BST
import java.util.ArrayList; import java.util.Random; public class Main { // 打乱数组顺序 private static void shuffle(Object[] arr){ for(int i = arr.length - 1 ; i >= 0 ; i --){ int pos = (int) (Math.random() * (i + 1)); Object t = arr[pos]; arr[pos] = arr[i]; arr[i] = t; } } public static void main(String[] args) { BST<Integer> bst = new BST<>(); Random random = new Random(); int n = 10000; for(int i = 0 ; i < n ; i ++) bst.add(random.nextInt(n)); // 注意, 由于随机生成的数据有重复, 所以bst中的数据数量大概率是小于n的 // order数组中存放[0...n)的所有元素 Integer[] order = new Integer[n]; for( int i = 0 ; i < n ; i ++ ) order[i] = i; // 打乱order数组的顺序 shuffle(order); // 乱序删除[0...n)范围里的所有元素 for( int i = 0 ; i < n ; i ++ ) if(bst.contains(order[i])){ bst.remove(order[i]); System.out.println("After remove " + order[i] + ", size = " + bst.size() ); } // 最终整个二分搜索树应该为空 System.out.println(bst.size()); } }
BST.java
import java.util.LinkedList; import java.util.Queue; import java.util.Stack; public class BST<E extends Comparable<E>> { private class Node{ public E e; public Node left, right; public Node(E e){ this.e = e; left = null; right = null; } } private Node root; private int size; public BST(){ root = null; size = 0; } public int size(){ return size; } public boolean isEmpty(){ return size == 0; } // 向二分搜索树中添加新的元素e public void add(E e){ root = add(root, e); } // 向以node为根的二分搜索树中插入元素e,递归算法 // 返回插入新节点后二分搜索树的根 private Node add(Node node, E e){ if(node == null){ size ++; return new Node(e); } if(e.compareTo(node.e) < 0) node.left = add(node.left, e); else if(e.compareTo(node.e) > 0) node.right = add(node.right, e); return node; } // 看二分搜索树中是否包含元素e public boolean contains(E e){ return contains(root, e); } // 看以node为根的二分搜索树中是否包含元素e, 递归算法 private boolean contains(Node node, E e){ if(node == null) return false; if(e.compareTo(node.e) == 0) return true; else if(e.compareTo(node.e) < 0) return contains(node.left, e); else // e.compareTo(node.e) > 0 return contains(node.right, e); } // 二分搜索树的前序遍历 public void preOrder(){ preOrder(root); } // 前序遍历以node为根的二分搜索树, 递归算法 private void preOrder(Node node){ if(node == null) return; System.out.println(node.e); preOrder(node.left); preOrder(node.right); } // 二分搜索树的非递归前序遍历 public void preOrderNR(){ Stack<Node> stack = new Stack<>(); stack.push(root); while(!stack.isEmpty()){ Node cur = stack.pop(); System.out.println(cur.e); if(cur.right != null) stack.push(cur.right); if(cur.left != null) stack.push(cur.left); } } // 二分搜索树的中序遍历 public void inOrder(){ inOrder(root); } // 中序遍历以node为根的二分搜索树, 递归算法 private void inOrder(Node node){ if(node == null) return; inOrder(node.left); System.out.println(node.e); inOrder(node.right); } // 二分搜索树的后序遍历 public void postOrder(){ postOrder(root); } // 后序遍历以node为根的二分搜索树, 递归算法 private void postOrder(Node node){ if(node == null) return; postOrder(node.left); postOrder(node.right); System.out.println(node.e); } // 二分搜索树的层序遍历 public void levelOrder(){ Queue<Node> q = new LinkedList<>(); q.add(root); while(!q.isEmpty()){ Node cur = q.remove(); System.out.println(cur.e); if(cur.left != null) q.add(cur.left); if(cur.right != null) q.add(cur.right); } } // 寻找二分搜索树的最小元素 public E minimum(){ if(size == 0) throw new IllegalArgumentException("BST is empty!"); return minimum(root).e; } // 返回以node为根的二分搜索树的最小值所在的节点 private Node minimum(Node node){ if(node.left == null) return node; return minimum(node.left); } // 寻找二分搜索树的最大元素 public E maximum(){ if(size == 0) throw new IllegalArgumentException("BST is empty"); return maximum(root).e; } // 返回以node为根的二分搜索树的最大值所在的节点 private Node maximum(Node node){ if(node.right == null) return node; return maximum(node.right); } // 从二分搜索树中删除最小值所在节点, 返回最小值 public E removeMin(){ E ret = minimum(); root = removeMin(root); return ret; } // 删除掉以node为根的二分搜索树中的最小节点 // 返回删除节点后新的二分搜索树的根 private Node removeMin(Node node){ if(node.left == null){ Node rightNode = node.right; node.right = null; size --; return rightNode; } node.left = removeMin(node.left); return node; } // 从二分搜索树中删除最大值所在节点 public E removeMax(){ E ret = maximum(); root = removeMax(root); return ret; } // 删除掉以node为根的二分搜索树中的最大节点 // 返回删除节点后新的二分搜索树的根 private Node removeMax(Node node){ if(node.right == null){ Node leftNode = node.left; node.left = null; size --; return leftNode; } node.right = removeMax(node.right); return node; } // 从二分搜索树中删除元素为e的节点 public void remove(E e){ root = remove(root, e); } // 删除掉以node为根的二分搜索树中值为e的节点, 递归算法 // 返回删除节点后新的二分搜索树的根 private Node remove(Node node, E e){ if( node == null ) return null; if( e.compareTo(node.e) < 0 ){ node.left = remove(node.left , e); return node; } else if(e.compareTo(node.e) > 0 ){ node.right = remove(node.right, e); return node; } else{ // e.compareTo(node.e) == 0 // 待删除节点左子树为空的情况 if(node.left == null){ Node rightNode = node.right; node.right = null; size --; return rightNode; } // 待删除节点右子树为空的情况 if(node.right == null){ Node leftNode = node.left; node.left = null; size --; return leftNode; } // 待删除节点左右子树均不为空的情况 // 找到比待删除节点大的最小节点, 即待删除节点右子树的最小节点 // 用这个节点顶替待删除节点的位置 Node successor = minimum(node.right); successor.right = removeMin(node.right); successor.left = node.left; node.left = node.right = null; return successor; } } @Override public String toString(){ StringBuilder res = new StringBuilder(); generateBSTString(root, 0, res); return res.toString(); } // 生成以node为根节点,深度为depth的描述二叉树的字符串 private void generateBSTString(Node node, int depth, StringBuilder res){ if(node == null){ res.append(generateDepthString(depth) + "null\n"); return; } res.append(generateDepthString(depth) + node.e +"\n"); generateBSTString(node.left, depth + 1, res); generateBSTString(node.right, depth + 1, res); } private String generateDepthString(int depth){ StringBuilder res = new StringBuilder(); for(int i = 0 ; i < depth ; i ++) res.append("--"); return res.toString(); } }