mirror of
https://github.com/krahets/hello-algo.git
synced 2024-12-25 00:36:27 +08:00
Add C++ code for the chapter binary tree.
This commit is contained in:
parent
980eaf65e0
commit
d2db8b8d60
14 changed files with 613 additions and 17 deletions
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@ -40,7 +40,7 @@ int main() {
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cout << "目标元素 3 的索引 = " << index << endl;
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/* 哈希查找(链表) */
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ListNode* head = vectorToLinkedList(nums);
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ListNode* head = vecToLinkedList(nums);
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// 初始化哈希表
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unordered_map<int, ListNode*> map1;
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while (head != nullptr) {
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@ -42,7 +42,7 @@ int main() {
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cout << "目标元素 3 的索引 = " << index << endl;
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/* 在链表中执行线性查找 */
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ListNode* head = vectorToLinkedList(nums);
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ListNode* head = vecToLinkedList(nums);
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ListNode* node = linearSearch(head, target);
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cout << "目标结点值 3 的对应结点对象为 " << node << endl;
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@ -6,6 +6,8 @@
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#include "../include/include.hpp"
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/* Driver Code */
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int main(){
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/* 初始化队列 */
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queue<int> queue;
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@ -6,7 +6,9 @@
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#include "../include/include.hpp"
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int main(){
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/* Driver Code */
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int main() {
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/* 初始化栈 */
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stack<int> stack;
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@ -25,15 +27,15 @@ int main(){
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/* 元素出栈 */
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stack.pop();
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cout<< "出栈元素 pop = " << top << ",出栈后 stack = ";
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cout << "出栈元素 pop = " << top << ",出栈后 stack = ";
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PrintUtil::printStack(stack);
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/* 获取栈的长度 */
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int size = stack.size();
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cout<< "栈的长度 size = " << size << endl;
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cout << "栈的长度 size = " << size << endl;
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/* 判断是否为空 */
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bool empty = stack.empty();
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return 0;
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}
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@ -6,3 +6,149 @@
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#include "../include/include.hpp"
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/* 二叉搜索树 */
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class BinarySearchTree {
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private:
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TreeNode* root;
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public:
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BinarySearchTree(vector<int> nums) {
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sort(nums.begin(), nums.end()); // 排序数组
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root = buildTree(nums, 0, nums.size() - 1); // 构建二叉搜索树
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}
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/* 获取二叉树根结点 */
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TreeNode* getRoot() {
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return root;
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}
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/* 构建二叉搜索树 */
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TreeNode* buildTree(vector<int> nums, int i, int j) {
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if (i > j) return nullptr;
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// 将数组中间结点作为根结点
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int mid = (i + j) / 2;
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TreeNode* root = new TreeNode(nums[mid]);
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// 递归建立左子树和右子树
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root->left = buildTree(nums, i, mid - 1);
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root->right = buildTree(nums, mid + 1, j);
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return root;
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}
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/* 查找结点 */
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TreeNode* search(int num) {
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TreeNode* cur = root;
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// 循环查找,越过叶结点后跳出
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while (cur != nullptr) {
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// 目标结点在 root 的右子树中
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if (cur->val < num) cur = cur->right;
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// 目标结点在 root 的左子树中
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else if (cur->val > num) cur = cur->left;
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// 找到目标结点,跳出循环
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else break;
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}
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// 返回目标结点
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return cur;
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}
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/* 插入结点 */
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TreeNode* insert(int num) {
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// 若树为空,直接提前返回
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if (root == nullptr) return nullptr;
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TreeNode *cur = root, *pre = nullptr;
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// 循环查找,越过叶结点后跳出
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while (cur != nullptr) {
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// 找到重复结点,直接返回
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if (cur->val == num) return nullptr;
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pre = cur;
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// 插入位置在 root 的右子树中
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if (cur->val < num) cur = cur->right;
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// 插入位置在 root 的左子树中
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else cur = cur->left;
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}
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// 插入结点 val
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TreeNode* node = new TreeNode(num);
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if (pre->val < num) pre->right = node;
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else pre->left = node;
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return node;
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}
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/* 删除结点 */
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TreeNode* remove(int num) {
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// 若树为空,直接提前返回
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if (root == nullptr) return nullptr;
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TreeNode *cur = root, *pre = nullptr;
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// 循环查找,越过叶结点后跳出
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while (cur != nullptr) {
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// 找到待删除结点,跳出循环
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if (cur->val == num) break;
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pre = cur;
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// 待删除结点在 root 的右子树中
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if (cur->val < num) cur = cur->right;
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// 待删除结点在 root 的左子树中
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else cur = cur->left;
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}
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// 若无待删除结点,则直接返回
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if (cur == nullptr) return nullptr;
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// 子结点数量 = 0 or 1
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if (cur->left == nullptr || cur->right == nullptr) {
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// 当子结点数量 = 0 / 1 时, child = nullptr / 该子结点
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TreeNode* child = cur->left != nullptr ? cur->left : cur->right;
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// 删除结点 cur
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if (pre->left == cur) pre->left = child;
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else pre->right = child;
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}
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// 子结点数量 = 2
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else {
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// 获取中序遍历中 cur 的下一个结点
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TreeNode* nex = min(cur->right);
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int tmp = nex->val;
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// 递归删除结点 nex
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remove(nex->val);
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// 将 nex 的值复制给 cur
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cur->val = tmp;
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}
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return cur;
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}
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/* 获取最小结点 */
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TreeNode* min(TreeNode* root) {
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if (root == nullptr) return root;
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// 循环访问左子结点,直到叶结点时为最小结点,跳出
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while (root->left != nullptr) {
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root = root->left;
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}
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return root;
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}
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};
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/* Driver Code */
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int main() {
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/* 初始化二叉搜索树 */
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vector<int> nums = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 };
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BinarySearchTree* bst = new BinarySearchTree(nums);
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cout << endl << "初始化的二叉树为\n" << endl;
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PrintUtil::printTree(bst->getRoot());
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/* 查找结点 */
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TreeNode* node = bst->search(5);
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cout << endl << "查找到的结点对象为 " << node << ",结点值 = " << node->val << endl;
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/* 插入结点 */
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node = bst->insert(16);
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cout << endl << "插入结点 16 后,二叉树为\n" << endl;
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PrintUtil::printTree(bst->getRoot());
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/* 删除结点 */
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bst->remove(1);
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cout << endl << "删除结点 1 后,二叉树为\n" << endl;
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PrintUtil::printTree(bst->getRoot());
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bst->remove(2);
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cout << endl << "删除结点 2 后,二叉树为\n" << endl;
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PrintUtil::printTree(bst->getRoot());
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bst->remove(4);
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cout << endl << "删除结点 4 后,二叉树为\n" << endl;
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PrintUtil::printTree(bst->getRoot());
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return 0;
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}
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@ -6,3 +6,35 @@
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#include "../include/include.hpp"
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/* Driver Code */
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int main() {
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/* 初始化二叉树 */
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// 初始化结点
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TreeNode* n1 = new TreeNode(1);
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TreeNode* n2 = new TreeNode(2);
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TreeNode* n3 = new TreeNode(3);
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TreeNode* n4 = new TreeNode(4);
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TreeNode* n5 = new TreeNode(5);
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// 构建引用指向(即指针)
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n1->left = n2;
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n1->right = n3;
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n2->left = n4;
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n2->right = n5;
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cout << endl << "初始化二叉树\n" << endl;
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PrintUtil::printTree(n1);
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/* 插入与删除结点 */
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TreeNode* P = new TreeNode(0);
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// 在 n1 -> n2 中间插入结点 P
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n1->left = P;
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P->left = n2;
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cout << endl << "插入结点 P 后\n" << endl;
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PrintUtil::printTree(n1);
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// 删除结点 P
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n1->left = n2;
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cout << endl << "删除结点 P 后\n" << endl;
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PrintUtil::printTree(n1);
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return 0;
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}
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@ -6,3 +6,39 @@
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#include "../include/include.hpp"
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/* 层序遍历 */
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vector<int> hierOrder(TreeNode* root) {
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// 初始化队列,加入根结点
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queue<TreeNode*> queue;
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queue.push(root);
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// 初始化一个列表,用于保存遍历序列
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vector<int> vec;
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while (!queue.empty()) {
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TreeNode* node = queue.front();
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queue.pop(); // 队列出队
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vec.push_back(node->val); // 保存结点
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if (node->left != NULL)
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queue.push(node->left); // 左子结点入队
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if (node->right != NULL)
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queue.push(node->right); // 右子结点入队
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}
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return vec;
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}
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/* Driver Code */
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int main() {
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/* 初始化二叉树 */
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// 这里借助了一个从数组直接生成二叉树的函数
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TreeNode* root = vecToTree(vector<int>
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{ 1, 2, 3, 4, 5, 6, 7, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX });
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cout << endl << "初始化二叉树\n" << endl;
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PrintUtil::printTree(root);
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/* 层序遍历 */
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vector<int> vec = hierOrder(root);
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cout << endl << "层序遍历的结点打印序列 = ";
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PrintUtil::printVector(vec);
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return 0;
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}
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@ -6,3 +6,63 @@
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#include "../include/include.hpp"
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// 初始化列表,用于存储遍历序列
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vector<int> vec;
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/* 前序遍历 */
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void preOrder(TreeNode* root) {
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if (root == nullptr) return;
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// 访问优先级:根结点 -> 左子树 -> 右子树
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vec.push_back(root->val);
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preOrder(root->left);
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preOrder(root->right);
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}
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/* 中序遍历 */
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void inOrder(TreeNode* root) {
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if (root == nullptr) return;
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(root->left);
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vec.push_back(root->val);
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inOrder(root->right);
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}
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/* 后序遍历 */
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void postOrder(TreeNode* root) {
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if (root == nullptr) return;
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(root->left);
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postOrder(root->right);
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vec.push_back(root->val);
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}
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/* Driver Code */
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int main() {
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/* 初始化二叉树 */
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// 这里借助了一个从数组直接生成二叉树的函数
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TreeNode* root = vecToTree(vector<int>
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{ 1, 2, 3, 4, 5, 6, 7, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX});
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cout << endl << "初始化二叉树\n" << endl;
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PrintUtil::printTree(root);
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/* 前序遍历 */
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vec.clear();
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preOrder(root);
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cout << endl << "前序遍历的结点打印序列 = ";
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PrintUtil::printVector(vec);
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/* 中序遍历 */
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vec.clear();
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inOrder(root);
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cout << endl << "中序遍历的结点打印序列 = ";
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PrintUtil::printVector(vec);
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/* 后序遍历 */
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vec.clear();
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postOrder(root);
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cout << endl << "后序遍历的结点打印序列 = ";
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PrintUtil::printVector(vec);
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return 0;
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}
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* @param list
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* @return ListNode*
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*/
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ListNode* vectorToLinkedList(vector<int>& list) {
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ListNode* vecToLinkedList(vector<int> list) {
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ListNode *dum = new ListNode(0);
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ListNode *head = dum;
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for (int val : list) {
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@ -238,4 +238,27 @@ class PrintUtil {
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}
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cout << "[" + s.str() + "]" << '\n';
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}
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/**
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* @brief
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*
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* @tparam T
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* @param queue
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*/
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template <typename T>
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static void printQueue(queue<T> &queue)
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{
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// Generate the string to print
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ostringstream s;
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bool flag = true;
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while(!queue.empty()) {
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if (flag) {
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s << queue.front();
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flag = false;
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}
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else s << ", " << queue.front();
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queue.pop();
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}
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cout << "[" + s.str() + "]" << '\n';
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}
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};
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* @param list
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* @return TreeNode*
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*/
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TreeNode* vectorToTree(vector<int>& list) {
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TreeNode* vecToTree(vector<int> list) {
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TreeNode *root = new TreeNode(list[0]);
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queue<TreeNode*> que;
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que.emplace(root);
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@ -9,6 +9,7 @@ package chapter_tree;
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import java.util.*;
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import include.*;
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/* 二叉搜索树 */
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class BinarySearchTree {
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private TreeNode root;
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@ -59,12 +59,43 @@ comments: true
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}
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```
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=== "C++"
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```cpp title="binary_search_tree.cpp"
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/* 查找结点 */
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TreeNode* search(int num) {
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TreeNode* cur = root;
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// 循环查找,越过叶结点后跳出
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while (cur != nullptr) {
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// 目标结点在 root 的右子树中
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if (cur->val < num) cur = cur->right;
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// 目标结点在 root 的左子树中
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else if (cur->val > num) cur = cur->left;
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// 找到目标结点,跳出循环
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else break;
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}
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// 返回目标结点
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return cur;
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}
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```
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=== "Python"
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```python title="binary_search_tree.py"
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```
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=== "Go"
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```go title="binary_search_tree.go"
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```
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### 插入结点
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给定一个待插入元素 `num` ,为了保持二叉搜索树 “左子树 < 根结点 < 右子树” 的性质,插入操作分为两步:
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1. **查找插入位置:** 与查找操作类似,我们从根结点出发,根据当前结点值和 `num` 的大小关系循环向下搜索,直到越过叶结点(遍历到 $\text{null}$ )时跳出循环;
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2. **在该位置插入结点:** 初始化结点 `num` ,将该结点放到 $\text{null}$ 的位置 ;
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二叉搜索树不允许存在重复结点,否则将会违背其定义。因此若待插入结点在树中已经存在,则不执行插入,直接返回即可。
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@ -97,6 +128,44 @@ comments: true
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}
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```
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=== "C++"
|
||||
|
||||
```cpp title="binary_search_tree.cpp"
|
||||
/* 插入结点 */
|
||||
TreeNode* insert(int num) {
|
||||
// 若树为空,直接提前返回
|
||||
if (root == nullptr) return nullptr;
|
||||
TreeNode *cur = root, *pre = nullptr;
|
||||
// 循环查找,越过叶结点后跳出
|
||||
while (cur != nullptr) {
|
||||
// 找到重复结点,直接返回
|
||||
if (cur->val == num) return nullptr;
|
||||
pre = cur;
|
||||
// 插入位置在 root 的右子树中
|
||||
if (cur->val < num) cur = cur->right;
|
||||
// 插入位置在 root 的左子树中
|
||||
else cur = cur->left;
|
||||
}
|
||||
// 插入结点 val
|
||||
TreeNode* node = new TreeNode(num);
|
||||
if (pre->val < num) pre->right = node;
|
||||
else pre->left = node;
|
||||
return node;
|
||||
}
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python title="binary_search_tree.py"
|
||||
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="binary_search_tree.go"
|
||||
|
||||
```
|
||||
|
||||
为了插入结点,需要借助 **辅助结点 `prev`** 保存上一轮循环的结点,这样在遍历到 $\text{null}$ 时,我们也可以获取到其父结点,从而完成结点插入操作。
|
||||
|
||||
与查找结点相同,插入结点使用 $O(\log n)$ 时间。
|
||||
|
@ -188,6 +257,69 @@ comments: true
|
|||
}
|
||||
```
|
||||
|
||||
=== "C++"
|
||||
|
||||
```cpp title="binary_search_tree.cpp"
|
||||
/* 删除结点 */
|
||||
TreeNode* remove(int num) {
|
||||
// 若树为空,直接提前返回
|
||||
if (root == nullptr) return nullptr;
|
||||
TreeNode *cur = root, *pre = nullptr;
|
||||
// 循环查找,越过叶结点后跳出
|
||||
while (cur != nullptr) {
|
||||
// 找到待删除结点,跳出循环
|
||||
if (cur->val == num) break;
|
||||
pre = cur;
|
||||
// 待删除结点在 root 的右子树中
|
||||
if (cur->val < num) cur = cur->right;
|
||||
// 待删除结点在 root 的左子树中
|
||||
else cur = cur->left;
|
||||
}
|
||||
// 若无待删除结点,则直接返回
|
||||
if (cur == nullptr) return nullptr;
|
||||
// 子结点数量 = 0 or 1
|
||||
if (cur->left == nullptr || cur->right == nullptr) {
|
||||
// 当子结点数量 = 0 / 1 时, child = nullptr / 该子结点
|
||||
TreeNode* child = cur->left != nullptr ? cur->left : cur->right;
|
||||
// 删除结点 cur
|
||||
if (pre->left == cur) pre->left = child;
|
||||
else pre->right = child;
|
||||
}
|
||||
// 子结点数量 = 2
|
||||
else {
|
||||
// 获取中序遍历中 cur 的下一个结点
|
||||
TreeNode* nex = min(cur->right);
|
||||
int tmp = nex->val;
|
||||
// 递归删除结点 nex
|
||||
remove(nex->val);
|
||||
// 将 nex 的值复制给 cur
|
||||
cur->val = tmp;
|
||||
}
|
||||
return cur;
|
||||
}
|
||||
/* 获取最小结点 */
|
||||
TreeNode* min(TreeNode* root) {
|
||||
if (root == nullptr) return root;
|
||||
// 循环访问左子结点,直到叶结点时为最小结点,跳出
|
||||
while (root->left != nullptr) {
|
||||
root = root->left;
|
||||
}
|
||||
return root;
|
||||
}
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python title="binary_search_tree.py"
|
||||
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="binary_search_tree.go"
|
||||
|
||||
```
|
||||
|
||||
## 二叉搜索树的优势
|
||||
|
||||
假设给定 $n$ 个数字,最常用的存储方式是「数组」,那么对于这串乱序的数字,常见操作的效率为:
|
||||
|
|
|
@ -18,6 +18,35 @@ comments: true
|
|||
}
|
||||
```
|
||||
|
||||
=== "C++"
|
||||
|
||||
```cpp
|
||||
/* 链表结点结构体 */
|
||||
struct TreeNode {
|
||||
int val; // 结点值
|
||||
TreeNode *left; // 左子结点指针
|
||||
TreeNode *right; // 右子结点指针
|
||||
TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
|
||||
};
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
""" 链表结点类 """
|
||||
class TreeNode:
|
||||
def __init__(self, val=0, left=None, right=None):
|
||||
self.val = val # 结点值
|
||||
self.left = left # 左子结点指针
|
||||
self.right = right # 右子结点指针
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go
|
||||
|
||||
```
|
||||
|
||||
结点的两个指针分别指向「左子结点 Left Child Node」和「右子结点 Right Child Node」,并且称该结点为两个子结点的「父结点 Parent Node」。给定二叉树某结点,将左子结点以下的树称为该结点的「左子树 Left Subtree」,右子树同理。
|
||||
|
||||
![binary_tree_definition](binary_tree.assets/binary_tree_definition.png)
|
||||
|
@ -84,20 +113,75 @@ comments: true
|
|||
n2.right = n5;
|
||||
```
|
||||
|
||||
=== "C++"
|
||||
|
||||
```cpp title="binary_tree.cpp"
|
||||
/* 初始化二叉树 */
|
||||
// 初始化结点
|
||||
TreeNode* n1 = new TreeNode(1);
|
||||
TreeNode* n2 = new TreeNode(2);
|
||||
TreeNode* n3 = new TreeNode(3);
|
||||
TreeNode* n4 = new TreeNode(4);
|
||||
TreeNode* n5 = new TreeNode(5);
|
||||
// 构建引用指向(即指针)
|
||||
n1->left = n2;
|
||||
n1->right = n3;
|
||||
n2->left = n4;
|
||||
n2->right = n5;
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python title="binary_tree.py"
|
||||
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="binary_tree.go"
|
||||
|
||||
```
|
||||
|
||||
**插入与删除结点。** 与链表类似,插入与删除结点都可以通过修改指针实现。
|
||||
|
||||
![binary_tree_add_remove](binary_tree.assets/binary_tree_add_remove.png)
|
||||
|
||||
<p align="center"> Fig. 在二叉树中插入与删除结点 </p>
|
||||
|
||||
```java title="binary_tree.java"
|
||||
TreeNode P = new TreeNode(0);
|
||||
// 在 n1 -> n2 中间插入结点 P
|
||||
n1.left = P;
|
||||
P.left = n2;
|
||||
// 删除结点 P
|
||||
n1.left = n2;
|
||||
```
|
||||
=== "Java"
|
||||
|
||||
```java title="binary_tree.java"
|
||||
TreeNode P = new TreeNode(0);
|
||||
// 在 n1 -> n2 中间插入结点 P
|
||||
n1.left = P;
|
||||
P.left = n2;
|
||||
// 删除结点 P
|
||||
n1.left = n2;
|
||||
```
|
||||
|
||||
=== "C++"
|
||||
|
||||
```cpp title="binary_tree.cpp"
|
||||
/* 插入与删除结点 */
|
||||
TreeNode* P = new TreeNode(0);
|
||||
// 在 n1 -> n2 中间插入结点 P
|
||||
n1->left = P;
|
||||
P->left = n2;
|
||||
// 删除结点 P
|
||||
n1->left = n2;
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python title="binary_tree.py"
|
||||
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="binary_tree.go"
|
||||
|
||||
```
|
||||
|
||||
!!! note
|
||||
|
||||
|
@ -140,6 +224,41 @@ n1.left = n2;
|
|||
}
|
||||
```
|
||||
|
||||
=== "C++"
|
||||
|
||||
```cpp title="binary_tree_bfs.cpp"
|
||||
/* 层序遍历 */
|
||||
vector<int> hierOrder(TreeNode* root) {
|
||||
// 初始化队列,加入根结点
|
||||
queue<TreeNode*> queue;
|
||||
queue.push(root);
|
||||
// 初始化一个列表,用于保存遍历序列
|
||||
vector<int> vec;
|
||||
while (!queue.empty()) {
|
||||
TreeNode* node = queue.front();
|
||||
queue.pop(); // 队列出队
|
||||
vec.push_back(node->val); // 保存结点
|
||||
if (node->left != NULL)
|
||||
queue.push(node->left); // 左子结点入队
|
||||
if (node->right != NULL)
|
||||
queue.push(node->right); // 右子结点入队
|
||||
}
|
||||
return vec;
|
||||
}
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python title="binary_tree_bfs.py"
|
||||
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="binary_tree_bfs.go"
|
||||
|
||||
```
|
||||
|
||||
### 前序、中序、后序遍历
|
||||
|
||||
相对地,前、中、后序遍历皆属于「深度优先遍历 Depth-First Traversal」,其体现着一种 “先走到尽头,再回头继续” 的回溯遍历方式。
|
||||
|
@ -191,6 +310,49 @@ n1.left = n2;
|
|||
}
|
||||
```
|
||||
|
||||
=== "C++"
|
||||
|
||||
```cpp title="binary_tree_dfs.cpp"
|
||||
/* 前序遍历 */
|
||||
void preOrder(TreeNode* root) {
|
||||
if (root == nullptr) return;
|
||||
// 访问优先级:根结点 -> 左子树 -> 右子树
|
||||
vec.push_back(root->val);
|
||||
preOrder(root->left);
|
||||
preOrder(root->right);
|
||||
}
|
||||
|
||||
/* 中序遍历 */
|
||||
void inOrder(TreeNode* root) {
|
||||
if (root == nullptr) return;
|
||||
// 访问优先级:左子树 -> 根结点 -> 右子树
|
||||
inOrder(root->left);
|
||||
vec.push_back(root->val);
|
||||
inOrder(root->right);
|
||||
}
|
||||
|
||||
/* 后序遍历 */
|
||||
void postOrder(TreeNode* root) {
|
||||
if (root == nullptr) return;
|
||||
// 访问优先级:左子树 -> 右子树 -> 根结点
|
||||
postOrder(root->left);
|
||||
postOrder(root->right);
|
||||
vec.push_back(root->val);
|
||||
}
|
||||
```
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python title="binary_tree_dfs.py"
|
||||
|
||||
```
|
||||
|
||||
=== "Go"
|
||||
|
||||
```go title="binary_tree_dfs.go"
|
||||
|
||||
```
|
||||
|
||||
!!! note
|
||||
|
||||
使用循环一样可以实现前、中、后序遍历,但代码相对繁琐,有兴趣的同学可以自行实现。
|
||||
|
|
Loading…
Reference in a new issue