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fix binary_search_tree code

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pull/711/head
krahets 1 year ago
parent f7ab4797bf
commit 628d8a516b
14 changed files with 195 additions and 227 deletions
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6
codes/c/chapter_tree/binary_search_tree.c
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@ -70,9 +70,11 @@ TreeNode *search(binarySearchTree *bst, int num) {
/* 插入节点 */
void insert(binarySearchTree *bst, int num) {
// 若树为空，直接提前返回
if (bst->root == NULL)
// 若树为空，则初始化根节点
if (bst->root == NULL) {
bst->root = newTreeNode(num);
return;
}
TreeNode *cur = bst->root, *pre = NULL;
// 循环查找，越过叶节点后跳出
while (cur != NULL) {

35
codes/cpp/chapter_tree/binary_search_tree.cpp
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@ -12,11 +12,13 @@ class BinarySearchTree {
TreeNode *root;
public:
BinarySearchTree(vector<int> nums) {
sort(nums.begin(), nums.end()); // 排序数组
root = buildTree(nums, 0, nums.size() - 1); // 构建二叉搜索树
/* 构造方法 */
BinarySearchTree() {
// 初始化空树
root = nullptr;
}
/* 析构方法 */
~BinarySearchTree() {
freeMemoryTree(root);
}
@ -26,19 +28,6 @@ class BinarySearchTree {
return root;
}
/* 构建二叉搜索树 */
TreeNode *buildTree(vector<int> nums, int i, int j) {
if (i > j)
return nullptr;
// 将数组中间节点作为根节点
int mid = (i + j) / 2;
TreeNode *root = new TreeNode(nums[mid]);
// 递归建立左子树和右子树
root->left = buildTree(nums, i, mid - 1);
root->right = buildTree(nums, mid + 1, j);
return root;
}
/* 查找节点 */
TreeNode *search(int num) {
TreeNode *cur = root;
@ -60,9 +49,11 @@ class BinarySearchTree {
/* 插入节点 */
void insert(int num) {
// 若树为空，直接提前返回
if (root == nullptr)
// 若树为空，则初始化根节点
if (root == nullptr) {
root = new TreeNode(num);
return;
}
TreeNode *cur = root, *pre = nullptr;
// 循环查找，越过叶节点后跳出
while (cur != nullptr) {
@ -143,8 +134,12 @@ class BinarySearchTree {
/* Driver Code */
int main() {
/* 初始化二叉搜索树 */
vector<int> nums = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};
BinarySearchTree *bst = new BinarySearchTree(nums);
BinarySearchTree *bst = new BinarySearchTree();
// 请注意，不同的插入顺序会生成不同的二叉树，该序列可以生成一个完美二叉树
vector<int> nums = {8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15};
for (int num : nums) {
bst->insert(num);
}
cout << endl << "初始化的二叉树为\n" << endl;
printTree(bst->getRoot());

6
codes/csharp/chapter_tree/binary_search_tree.cs
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@ -54,9 +54,11 @@ class BinarySearchTree {
/* 插入节点 */
public void insert(int num) {
// 若树为空，直接提前返回
if (root == null)
// 若树为空，则初始化根节点
if (root == null) {
root = new TreeNode(num);
return;
}
TreeNode? cur = root, pre = null;
// 循环查找，越过叶节点后跳出
while (cur != null) {

7
codes/dart/chapter_tree/binary_search_tree.dart
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@ -56,8 +56,11 @@ class BinarySearchTree {
/* 插入节点 */
void insert(int num) {
// 若树为空，直接提前返回
if (_root == null) return;
// 若树为空，则初始化根节点
if (_root == null) {
_root = TreeNode(num);
return;
}
TreeNode? cur = _root;
TreeNode? pre = null;
// 循环查找，越过叶节点后跳出

27
codes/go/chapter_tree/binary_search_tree.go
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@ -5,8 +5,6 @@
package chapter_tree
import (
"sort"
. "github.com/krahets/hello-algo/pkg"
)
@ -14,29 +12,13 @@ type binarySearchTree struct {
root *TreeNode
}
func newBinarySearchTree(nums []int) *binarySearchTree {
// 排序数组
sort.Ints(nums)
// 构建二叉搜索树
func newBinarySearchTree() *binarySearchTree {
bst := &binarySearchTree{}
bst.root = bst.buildTree(nums, 0, len(nums)-1)
// 初始化空树
bst.root = nil
return bst
}
/* 构建二叉搜索树 */
func (bst *binarySearchTree) buildTree(nums []int, left, right int) *TreeNode {
if left > right {
return nil
}
// 将数组中间节点作为根节点
middle := left + (right-left)>>1
root := NewTreeNode(nums[middle])
// 递归构建左子树和右子树
root.Left = bst.buildTree(nums, left, middle-1)
root.Right = bst.buildTree(nums, middle+1, right)
return root
}
/* 获取根节点 */
func (bst *binarySearchTree) getRoot() *TreeNode {
return bst.root
@ -65,8 +47,9 @@ func (bst *binarySearchTree) search(num int) *TreeNode {
/* 插入节点 */
func (bst *binarySearchTree) insert(num int) {
cur := bst.root
// 若树为空，直接提前返回
// 若树为空，则初始化根节点
if cur == nil {
bst.root = NewTreeNode(num)
return
}
// 待插入节点之前的节点位置

8
codes/go/chapter_tree/binary_search_tree_test.go
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@ -10,8 +10,12 @@ import (
)
func TestBinarySearchTree(t *testing.T) {
nums := []int{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}
bst := newBinarySearchTree(nums)
bst := newBinarySearchTree()
nums := []int{8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15}
// 请注意，不同的插入顺序会生成不同的二叉树，该序列可以生成一个完美二叉树
for _, num := range nums {
bst.insert(num)
}
fmt.Println("\n初始化的二叉树为:")
bst.print()

35
codes/java/chapter_tree/binary_search_tree.java
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@ -6,16 +6,16 @@
package chapter_tree;
import java.util.*;
import utils.*;
/* 二叉搜索树 */
class BinarySearchTree {
private TreeNode root;
public BinarySearchTree(int[] nums) {
Arrays.sort(nums); // 排序数组
root = buildTree(nums, 0, nums.length - 1); // 构建二叉搜索树
/* 构造方法 */
public BinarySearchTree() {
// 初始化空树
root = null;
}
/* 获取二叉树根节点 */
@ -23,19 +23,6 @@ class BinarySearchTree {
return root;
}
/* 构建二叉搜索树 */
public TreeNode buildTree(int[] nums, int i, int j) {
if (i > j)
return null;
// 将数组中间节点作为根节点
int mid = (i + j) / 2;
TreeNode root = new TreeNode(nums[mid]);
// 递归建立左子树和右子树
root.left = buildTree(nums, i, mid - 1);
root.right = buildTree(nums, mid + 1, j);
return root;
}
/* 查找节点 */
public TreeNode search(int num) {
TreeNode cur = root;
@ -57,9 +44,11 @@ class BinarySearchTree {
/* 插入节点 */
public void insert(int num) {
// 若树为空，直接提前返回
if (root == null)
// 若树为空，则初始化根节点
if (root == null) {
root = new TreeNode(num);
return;
}
TreeNode cur = root, pre = null;
// 循环查找，越过叶节点后跳出
while (cur != null) {
@ -137,8 +126,12 @@ class BinarySearchTree {
public class binary_search_tree {
public static void main(String[] args) {
/* 初始化二叉搜索树 */
int[] nums = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 };
BinarySearchTree bst = new BinarySearchTree(nums);
BinarySearchTree bst = new BinarySearchTree();
// 请注意，不同的插入顺序会生成不同的二叉树，该序列可以生成一个完美二叉树
int[] nums = { 8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15 };
for (int num : nums) {
bst.insert(num);
}
System.out.println("\n初始化的二叉树为\n");
PrintUtil.printTree(bst.getRoot());

2
codes/javascript/chapter_tree/avl_tree.js
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@ -9,7 +9,7 @@ const { printTree } = require('../modules/PrintUtil');
/* AVL 树*/
class AVLTree {
/*构造方法*/
/* 构造方法 */
constructor() {
this.root = null; //根节点
}

100
codes/javascript/chapter_tree/binary_search_tree.js
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@ -8,35 +8,21 @@ const { TreeNode } = require('../modules/TreeNode');
const { printTree } = require('../modules/PrintUtil');
/* 二叉搜索树 */
let root;
function BinarySearchTree(nums) {
nums.sort((a, b) => {
return a - b;
}); // 排序数组
root = buildTree(nums, 0, nums.length - 1); // 构建二叉搜索树
}
/* 获取二叉树根节点 */
function getRoot() {
return root;
}
class BinarySearchTree {
/* 构造方法 */
constructor() {
// 初始化空树
this.root = null;
}
/* 构建二叉搜索树 */
function buildTree(nums, i, j) {
if (i > j) return null;
// 将数组中间节点作为根节点
let mid = Math.floor((i + j) / 2);
let root = new TreeNode(nums[mid]);
// 递归建立左子树和右子树
root.left = buildTree(nums, i, mid - 1);
root.right = buildTree(nums, mid + 1, j);
return root;
}
/* 获取二叉树根节点 */
getRoot() {
return this.root;
}
/* 查找节点 */
function search(num) {
let cur = root;
/* 查找节点 */
search(num) {
let cur = this.root;
// 循环查找，越过叶节点后跳出
while (cur !== null) {
// 目标节点在 cur 的右子树中
@ -48,13 +34,16 @@ function search(num) {
}
// 返回目标节点
return cur;
}
}
/* 插入节点 */
function insert(num) {
// 若树为空，直接提前返回
if (root === null) return;
let cur = root,
/* 插入节点 */
insert(num) {
// 若树为空，则初始化根节点
if (this.root === null) {
this.root = new TreeNode(num);
return;
}
let cur = this.root,
pre = null;
// 循环查找，越过叶节点后跳出
while (cur !== null) {
@ -70,13 +59,13 @@ function insert(num) {
let node = new TreeNode(num);
if (pre.val < num) pre.right = node;
else pre.left = node;
}
}
/* 删除节点 */
function remove(num) {
/* 删除节点 */
remove(num) {
// 若树为空，直接提前返回
if (root === null) return;
let cur = root,
if (this.root === null) return;
let cur = this.root,
pre = null;
// 循环查找，越过叶节点后跳出
while (cur !== null) {
@ -95,12 +84,12 @@ function remove(num) {
// 当子节点数量 = 0 / 1 时， child = null / 该子节点
let child = cur.left !== null ? cur.left : cur.right;
// 删除节点 cur
if (cur != root) {
if (cur !== this.root) {
if (pre.left === cur) pre.left = child;
else pre.right = child;
} else {
// 若删除节点为根节点，则重新指定根节点
root = child;
this.root = child;
}
}
// 子节点数量 = 2
@ -111,35 +100,40 @@ function remove(num) {
tmp = tmp.left;
}
// 递归删除节点 tmp
remove(tmp.val);
this.remove(tmp.val);
// 用 tmp 覆盖 cur
cur.val = tmp.val;
}
}
}
/* Driver Code */
/* 初始化二叉搜索树 */
const nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15];
BinarySearchTree(nums);
const bst = new BinarySearchTree();
// 请注意，不同的插入顺序会生成不同的二叉树，该序列可以生成一个完美二叉树
const nums = [8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15];
for (const num of nums) {
bst.insert(num);
}
console.log('\n初始化的二叉树为\n');
printTree(getRoot());
printTree(bst.getRoot());
/* 查找节点 */
let node = search(7);
let node = bst.search(7);
console.log('\n查找到的节点对象为 ' + node + '，节点值 = ' + node.val);
/* 插入节点 */
insert(16);
bst.insert(16);
console.log('\n插入节点 16 后，二叉树为\n');
printTree(getRoot());
printTree(bst.getRoot());
/* 删除节点 */
remove(1);
bst.remove(1);
console.log('\n删除节点 1 后，二叉树为\n');
printTree(getRoot());
remove(2);
printTree(bst.getRoot());
bst.remove(2);
console.log('\n删除节点 2 后，二叉树为\n');
printTree(getRoot());
remove(4);
printTree(bst.getRoot());
bst.remove(4);
console.log('\n删除节点 4 后，二叉树为\n');
printTree(getRoot());
printTree(bst.getRoot());

66
codes/python/chapter_tree/binary_search_tree.py
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@ -13,33 +13,18 @@ from modules import *
class BinarySearchTree:
"""二叉搜索树"""
def __init__(self, nums: list[int]):
def __init__(self):
"""构造方法"""
nums.sort()
self.root = self.build_tree(nums, 0, len(nums) - 1)
def build_tree(
self, nums: list[int], start_index: int, end_index: int
) -> TreeNode | None:
"""构建二叉搜索树"""
if start_index > end_index:
return None
# 将数组中间节点作为根节点
mid = (start_index + end_index) // 2
root = TreeNode(nums[mid])
# 递归建立左子树和右子树
root.left = self.build_tree(
nums=nums, start_index=start_index, end_index=mid - 1
)
root.right = self.build_tree(
nums=nums, start_index=mid + 1, end_index=end_index
)
return root
# 初始化空树
self.__root = None
def get_root(self) -> TreeNode | None:
"""获取二叉树根节点"""
return self.__root
def search(self, num: int) -> TreeNode | None:
"""查找节点"""
cur: TreeNode | None = self.root
cur = self.__root
# 循环查找，越过叶节点后跳出
while cur is not None:
# 目标节点在 cur 的右子树中
@ -55,12 +40,12 @@ class BinarySearchTree:
def insert(self, num: int):
"""插入节点"""
# 若树为空，直接提前返回
if self.root is None:
# 若树为空，则初始化根节点
if self.__root is None:
self.__root = TreeNode(num)
return
# 循环查找，越过叶节点后跳出
cur, pre = self.root, None
cur, pre = self.__root, None
while cur is not None:
# 找到重复节点，直接返回
if cur.val == num:
@ -72,7 +57,6 @@ class BinarySearchTree:
# 插入位置在 cur 的左子树中
else:
cur = cur.left
# 插入节点
node = TreeNode(num)
if pre.val < num:
@ -83,11 +67,10 @@ class BinarySearchTree:
def remove(self, num: int):
"""删除节点"""
# 若树为空，直接提前返回
if self.root is None:
if self.__root is None:
return
# 循环查找，越过叶节点后跳出
cur, pre = self.root, None
cur, pre = self.__root, None
while cur is not None:
# 找到待删除节点，跳出循环
if cur.val == num:
@ -108,14 +91,14 @@ class BinarySearchTree:
# 当子节点数量 = 0 / 1 时， child = null / 该子节点
child = cur.left or cur.right
# 删除节点 cur
if cur != self.root:
if cur != self.__root:
if pre.left == cur:
pre.left = child
else:
pre.right = child
else:
# 若删除节点为根节点，则重新指定根节点
self.root = child
self.__root = child
# 子节点数量 = 2
else:
# 获取中序遍历中 cur 的下一个节点
@ -131,10 +114,13 @@ class BinarySearchTree:
"""Driver Code"""
if __name__ == "__main__":
# 初始化二叉搜索树
nums = list(range(1, 16)) # [1, 2, ..., 15]
bst = BinarySearchTree(nums=nums)
bst = BinarySearchTree()
nums = [8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15]
# 请注意，不同的插入顺序会生成不同的二叉树，该序列可以生成一个完美二叉树
for num in nums:
bst.insert(num)
print("\n初始化的二叉树为\n")
print_tree(bst.root)
print_tree(bst.get_root())
# 查找节点
node = bst.search(7)
@ -143,17 +129,17 @@ if __name__ == "__main__":
# 插入节点
bst.insert(16)
print("\n插入节点 16 后，二叉树为\n")
print_tree(bst.root)
print_tree(bst.get_root())
# 删除节点
bst.remove(1)
print("\n删除节点 1 后，二叉树为\n")
print_tree(bst.root)
print_tree(bst.get_root())
bst.remove(2)
print("\n删除节点 2 后，二叉树为\n")
print_tree(bst.root)
print_tree(bst.get_root())
bst.remove(4)
print("\n删除节点 4 后，二叉树为\n")
print_tree(bst.root)
print_tree(bst.get_root())

3
codes/rust/chapter_tree/binary_search_tree.rs
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@ -74,8 +74,9 @@ impl BinarySearchTree {
/* 插入节点 */
pub fn insert(&mut self, num: i32) {
// 若树为空，直接提前返回
// 若树为空，则初始化根节点
if self.root.is_none() {
self.root = TreeNode::new(num);
return;
}
let mut cur = self.root.clone();

3
codes/swift/chapter_tree/binary_search_tree.swift
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@ -58,8 +58,9 @@ class BinarySearchTree {
/* 插入节点 */
func insert(num: Int) {
// 若树为空，直接提前返回
// 若树为空，则初始化根节点
if root == nil {
root = TreeNode(x: num)
return
}
var cur = root

3
codes/typescript/chapter_tree/binary_search_tree.ts
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@ -53,8 +53,9 @@ function search(num: number): TreeNode | null {
/* 插入节点 */
function insert(num: number): void {
// 若树为空，直接提前返回
// 若树为空，则初始化根节点
if (root === null) {
root = new TreeNode(num);
return;
}
let cur = root,

7
codes/zig/chapter_tree/binary_search_tree.zig
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@ -70,8 +70,11 @@ pub fn BinarySearchTree(comptime T: type) type {
// 插入节点
fn insert(self: *Self, num: T) !void {
// 若树为空，直接提前返回
if (self.root == null) return;
// 若树为空，则初始化根节点
if (self.root == null) {
self.root = try self.mem_allocator.create(inc.TreeNode(T));
return;
}
var cur = self.root;
var pre: ?*inc.TreeNode(T) = null;
// 循环查找，越过叶节点后跳出

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