fix binary_search_tree code

This commit is contained in:
krahets 2023-08-31 02:31:31 +08:00
parent f7ab4797bf
commit 628d8a516b
14 changed files with 195 additions and 227 deletions

View file

@ -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) {

View file

@ -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());

View file

@ -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) {

View file

@ -56,8 +56,11 @@ class BinarySearchTree {
/* 插入节点 */
void insert(int num) {
//
if (_root == null) return;
//
if (_root == null) {
_root = TreeNode(num);
return;
}
TreeNode? cur = _root;
TreeNode? pre = null;
//

View file

@ -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

View file

@ -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()

View file

@ -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());

View file

@ -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
}

View file

@ -8,138 +8,132 @@ 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;
}
/* 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;
}
/* 查找节点 */
function search(num) {
let cur = 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
if (cur.val < num) cur = cur.right;
// 目标节点在 cur 的左子树中
else if (cur.val > num) cur = cur.left;
// 找到目标节点,跳出循环
else break;
class BinarySearchTree {
/* 构造方法 */
constructor() {
// 初始化空树
this.root = null;
}
// 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,
pre = null;
// 循环查找,越过叶节点后跳出
while (cur !== null) {
// 找到重复节点,直接返回
if (cur.val === num) return;
pre = cur;
// 插入位置在 cur 的右子树中
if (cur.val < num) cur = cur.right;
// 插入位置在 cur 的左子树中
else cur = cur.left;
/* 获取二叉树根节点 */
getRoot() {
return this.root;
}
// 插入节点
let node = new TreeNode(num);
if (pre.val < num) pre.right = node;
else pre.left = node;
}
/* 删除节点 */
function remove(num) {
// 若树为空,直接提前返回
if (root === null) return;
let cur = root,
pre = null;
// 循环查找,越过叶节点后跳出
while (cur !== null) {
// 找到待删除节点,跳出循环
if (cur.val === num) break;
pre = cur;
// 待删除节点在 cur 的右子树中
if (cur.val < num) cur = cur.right;
// 待删除节点在 cur 的左子树中
else cur = cur.left;
}
// 若无待删除节点,则直接返回
if (cur === null) return;
// 子节点数量 = 0 or 1
if (cur.left === null || cur.right === null) {
// 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 (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;
/* 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
if (cur.val < num) cur = cur.right;
// 目标节点在 cur 的左子树中
else if (cur.val > num) cur = cur.left;
// 找到目标节点,跳出循环
else break;
}
// 返回目标节点
return cur;
}
// 子节点数量 = 2
else {
// 获取中序遍历中 cur 的下一个节点
let tmp = cur.right;
while (tmp.left !== null) {
tmp = tmp.left;
/* 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) {
// 找到重复节点,直接返回
if (cur.val === num) return;
pre = cur;
// 插入位置在 cur 的右子树中
if (cur.val < num) cur = cur.right;
// 插入位置在 cur 的左子树中
else cur = cur.left;
}
// 插入节点
let node = new TreeNode(num);
if (pre.val < num) pre.right = node;
else pre.left = node;
}
/* 删除节点 */
remove(num) {
// 若树为空,直接提前返回
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) {
// 找到待删除节点,跳出循环
if (cur.val === num) break;
pre = cur;
// 待删除节点在 cur 的右子树中
if (cur.val < num) cur = cur.right;
// 待删除节点在 cur 的左子树中
else cur = cur.left;
}
// 若无待删除节点,则直接返回
if (cur === null) return;
// 子节点数量 = 0 or 1
if (cur.left === null || cur.right === null) {
// 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 !== 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
this.root = child;
}
}
// 子节点数量 = 2
else {
// 获取中序遍历中 cur 的下一个节点
let tmp = cur.right;
while (tmp.left !== null) {
tmp = tmp.left;
}
// 递归删除节点 tmp
this.remove(tmp.val);
// 用 tmp 覆盖 cur
cur.val = tmp.val;
}
// 递归删除节点 tmp
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());

View file

@ -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)
# 初始化空树
self.__root = None
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
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())

View file

@ -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();

View file

@ -58,8 +58,9 @@ class BinarySearchTree {
/* */
func insert(num: Int) {
//
//
if root == nil {
root = TreeNode(x: num)
return
}
var cur = root

View file

@ -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,

View file

@ -70,8 +70,11 @@ pub fn BinarySearchTree(comptime T: type) type {
//
fn insert(self: *Self, num: T) !void {
//
if (self.root == null) return;
//
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;
//