adding general tree code

This commit is contained in:
Jidong Xiao
2025-03-20 23:34:12 -04:00
committed by JamesFlare
parent bed6b5cbc1
commit 09817c3736
3 changed files with 243 additions and 2 deletions

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@@ -10,7 +10,6 @@
## Todays Lecture ## Todays Lecture
- Warmup / Review: destroy_tree - Warmup / Review: destroy_tree
- A very important ds set operation insert
- In-order, pre-order, and post-order traversal - In-order, pre-order, and post-order traversal
- Finding the in-order successor of a binary tree node, tree iterator increment - Finding the in-order successor of a binary tree node, tree iterator increment
@@ -113,7 +112,7 @@ Exercise: What are the advantages & disadvantages of each method?
- The efficiency of the main insert, find and erase algorithms depends on the height of the tree. - The efficiency of the main insert, find and erase algorithms depends on the height of the tree.
- The best-case and average-case heights of a binary search tree storing n nodes are both O(log n). The worstcase, which often can happen in practice, is O(n). - The best-case and average-case heights of a binary search tree storing n nodes are both O(log n). The worstcase, which often can happen in practice, is O(n).
- Developing more sophisticated algorithms to avoid the worst-case behavior will be covered in Introduction to - Developing more sophisticated algorithms to avoid the worst-case behavior will be covered in Introduction to
Algorithms. One elegant extension to the binary search tree is described below... Algorithms. <!-- One elegant extension to the binary search tree is described below...
## 19.6 B+ Trees ## 19.6 B+ Trees
@@ -134,3 +133,92 @@ child must be < key0, the next child must have keys such that they are ≥key0 a
the rightmost child which has only keys ≥keyk1. the rightmost child which has only keys ≥keyk1.
A B+ tree visualization can be seen at: https://www.cs.usfca.edu/~galles/visualization/BPlusTree.html A B+ tree visualization can be seen at: https://www.cs.usfca.edu/~galles/visualization/BPlusTree.html
-->
## 19.6 N-ary tree and General Tree
- A tree where each node can have many children (not limited to two) is generally called an n-ary tree, where n refers to the maximum number of children each node can have.
- If there is no fixed limit on the number of children, it's often simply referred to as a general tree or multi-way tree.
- We can define the tree nodes for a general tree like this:
```cpp
class Node {
public:
int val;
std::vector<Node*> children;
Node() {}
Node(int _val) {
val = _val;
}
Node(int _val, std::vector<Node*> _children) {
val = _val;
children = _children;
}
};
```
## 19.7 General Tree Pre-order Traversal
The following code implements the pre-order traversal of a general tree.
```cpp
// make a helper function, since the original one doesn't take the vector as a parameter.
void preorder(Node* root, std::vector<int>& result){
if(root == NULL){
return;
}
// visit the parent
result.push_back(root->val);
int size = root->children.size();
for(int i=0; i<size; ++i){
// traverse each subtree
preorder(root->children[i], result);
}
}
std::vector<int> preorder(Node* root) {
std::vector<int> result;
preorder(root, result);
return result;
}
```
You can run [this program](general_tree_pre_order.cpp) to test the above functions.
## 19.8 General Tree Post-order Traversal
The following code implements the post-order traversal of a general tree.
```cpp
// make a helper function, since the original one doesn't take the vector as a parameter.
void postorder(Node* root, std::vector<int>& result){
// base case
if(root==NULL){
return;
}
// children first
int size = (root->children).size();
for(int i=0; i<size; ++i){
// call the same function to traverse children[i]
postorder(root->children[i], result);
}
// then parent
result.push_back(root->val);
}
std::vector<int> postorder(Node* root) {
std::vector<int> result;
postorder(root, result);
return result;
}
```
You can run [this program](general_tree_post_order.cpp) to test the above functions.

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@@ -0,0 +1,79 @@
#include <iostream>
#include <vector>
class Node {
public:
int val;
std::vector<Node*> children;
Node() {}
Node(int _val) {
val = _val;
}
Node(int _val, std::vector<Node*> _children) {
val = _val;
children = _children;
}
};
// make a helper function, since the original one doesn't take the vector as a parameter.
void postorder(Node* root, std::vector<int>& result){
// base case
if(root==NULL){
return;
}
// children first
int size = (root->children).size();
for(int i=0; i<size; ++i){
// call the same function to traverse children[i]
postorder(root->children[i], result);
}
// then parent
result.push_back(root->val);
}
std::vector<int> postorder(Node* root) {
std::vector<int> result;
postorder(root, result);
return result;
}
int main() {
// create tree nodes
// 1
// / | \
// 2 3 4
// / \
// 5 6
Node* node5 = new Node(5);
Node* node6 = new Node(6);
Node* node2 = new Node(2);
Node* node3 = new Node(3, {node5, node6});
Node* node4 = new Node(4);
Node* root = new Node(1, {node2, node3, node4});
// call preorder traversal
std::vector<int> result = postorder(root);
// print result
std::cout << "Post-order traversal: ";
for (int val : result) {
std::cout << val << " ";
}
std::cout << std::endl;
// free memory (optional but good practice)
delete node5;
delete node6;
delete node2;
delete node3;
delete node4;
delete root;
return 0;
}

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@@ -0,0 +1,74 @@
#include <iostream>
#include <vector>
class Node {
public:
int val;
std::vector<Node*> children;
Node() {}
Node(int _val) {
val = _val;
}
Node(int _val, std::vector<Node*> _children) {
val = _val;
children = _children;
}
};
// make a helper function, since the original one doesn't take the vector as a parameter.
void preorder(Node* root, std::vector<int>& result){
if(root == NULL){
return;
}
result.push_back(root->val);
for(auto child : root->children){
preorder(child, result);
}
}
std::vector<int> preorder(Node* root) {
std::vector<int> result;
preorder(root, result);
return result;
}
int main() {
// create tree nodes
// 1
// / | \
// 2 3 4
// / \
// 5 6
Node* node5 = new Node(5);
Node* node6 = new Node(6);
Node* node2 = new Node(2);
Node* node3 = new Node(3, {node5, node6});
Node* node4 = new Node(4);
Node* root = new Node(1, {node2, node3, node4});
// call preorder traversal
std::vector<int> result = preorder(root);
// print result
std::cout << "Pre-order traversal: ";
for (int val : result) {
std::cout << val << " ";
}
std::cout << std::endl;
// free memory
// FIXME: here we delete node one by one, which is really bad, we should write a function to delete the tree.
delete node5;
delete node6;
delete node2;
delete node3;
delete node4;
delete root;
return 0;
}