avl-tree-typed
Version:
Standard AVL tree
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Markdown
This is a standalone AVL Tree data structure from the data-structure-typed collection. If you wish to access more data
structures or advanced features, you can transition to directly installing the
complete [data-structure-typed](https://www.npmjs.com/package/data-structure-typed) package
```bash
npm i avl-tree-typed --save
```
```bash
yarn add avl-tree-typed
```
```typescript
import {AVLTree, AVLTreeNode} from 'data-structure-typed';
// /* or if you prefer */ import {AVLTree} from 'avl-tree-typed';
const avlTree = new AVLTree<AVLTreeNode<number>>();
const idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];
avlTree.addMany(idsOrVals, idsOrVals);
const node6 = avlTree.get(6);
node6 && avlTree.getHeight(node6) // 3
node6 && avlTree.getDepth(node6) // 1
const getNodeById = avlTree.get(10, 'id');
getNodeById?.id // 10
const getMinNodeByRoot = avlTree.getLeftMost();
getMinNodeByRoot?.id // 1
const node15 = avlTree.get(15);
const getMinNodeBySpecificNode = node15 && avlTree.getLeftMost(node15);
getMinNodeBySpecificNode?.id // 12
const subTreeSum = node15 && avlTree.subTreeSum(node15);
subTreeSum // 70
const lesserSum = avlTree.lesserSum(10);
lesserSum // 45
const node11 = avlTree.get(11);
node11?.id // 11
const dfs = avlTree.DFS('in', 'node');
dfs[0].id // 1
avlTree.perfectlyBalance();
const bfs = avlTree.BFS('node');
avlTree.isPerfectlyBalanced() && bfs[0].id // 8
avlTree.remove(11, true)[0].deleted?.id // 11
avlTree.isAVLBalanced(); // true
node15 && avlTree.getHeight(node15) // 2
avlTree.remove(1, true)[0].deleted?.id // 1
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 4
avlTree.remove(4, true)[0].deleted?.id // 4
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 4
avlTree.remove(10, true)[0].deleted?.id // 10
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(15, true)[0].deleted?.id // 15
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(5, true)[0].deleted?.id // 5
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(13, true)[0].deleted?.id // 13
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(3, true)[0].deleted?.id // 3
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(8, true)[0].deleted?.id // 8
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(6, true)[0].deleted?.id // 6
avlTree.remove(6, true).length // 0
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 2
avlTree.remove(7, true)[0].deleted?.id // 7
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 2
avlTree.remove(9, true)[0].deleted?.id // 9
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 2
avlTree.remove(14, true)[0].deleted?.id // 14
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 1
avlTree.isAVLBalanced(); // true
const lastBFSIds = avlTree.BFS();
lastBFSIds[0] // 12
const lastBFSNodes = avlTree.BFS('node');
lastBFSNodes[0].id // 12
```
```javascript
const {AVLTree} = require('data-structure-typed');
// /* or if you prefer */ const {AVLTree} = require('avl-tree-typed');
const avlTree = new AVLTree();
const idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];
avlTree.addMany(idsOrVals, idsOrVals);
const node6 = avlTree.get(6);
node6 && avlTree.getHeight(node6) // 3
node6 && avlTree.getDepth(node6) // 1
const getNodeById = avlTree.get(10, 'id');
getNodeById?.id // 10
const getMinNodeByRoot = avlTree.getLeftMost();
getMinNodeByRoot?.id // 1
const node15 = avlTree.get(15);
const getMinNodeBySpecificNode = node15 && avlTree.getLeftMost(node15);
getMinNodeBySpecificNode?.id // 12
const subTreeSum = node15 && avlTree.subTreeSum(node15);
subTreeSum // 70
const lesserSum = avlTree.lesserSum(10);
lesserSum // 45
const node11 = avlTree.get(11);
node11?.id // 11
const dfs = avlTree.DFS('in', 'node');
dfs[0].id // 1
avlTree.perfectlyBalance();
const bfs = avlTree.BFS('node');
avlTree.isPerfectlyBalanced() && bfs[0].id // 8
avlTree.remove(11, true)[0].deleted?.id // 11
avlTree.isAVLBalanced(); // true
node15 && avlTree.getHeight(node15) // 2
avlTree.remove(1, true)[0].deleted?.id // 1
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 4
avlTree.remove(4, true)[0].deleted?.id // 4
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 4
avlTree.remove(10, true)[0].deleted?.id // 10
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(15, true)[0].deleted?.id // 15
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(5, true)[0].deleted?.id // 5
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(13, true)[0].deleted?.id // 13
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(3, true)[0].deleted?.id // 3
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(8, true)[0].deleted?.id // 8
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 3
avlTree.remove(6, true)[0].deleted?.id // 6
avlTree.remove(6, true).length // 0
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 2
avlTree.remove(7, true)[0].deleted?.id // 7
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 2
avlTree.remove(9, true)[0].deleted?.id // 9
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 2
avlTree.remove(14, true)[0].deleted?.id // 14
avlTree.isAVLBalanced(); // true
avlTree.getHeight() // 1
avlTree.isAVLBalanced(); // true
const lastBFSIds = avlTree.BFS();
lastBFSIds[0] // 12
const lastBFSNodes = avlTree.BFS('node');
lastBFSNodes[0].id // 12
```
[//]: # (No deletion!!! Start of Example Replace Section)
```typescript
type Datum = { timestamp: Date; temperature: number };
// Fixed dataset of CPU temperature readings
const cpuData: Datum[] = [
{ timestamp: new Date('2024-12-02T00:00:00'), temperature: 55.1 },
{ timestamp: new Date('2024-12-02T00:01:00'), temperature: 56.3 },
{ timestamp: new Date('2024-12-02T00:02:00'), temperature: 54.8 },
{ timestamp: new Date('2024-12-02T00:03:00'), temperature: 57.2 },
{ timestamp: new Date('2024-12-02T00:04:00'), temperature: 58.0 },
{ timestamp: new Date('2024-12-02T00:05:00'), temperature: 59.4 },
{ timestamp: new Date('2024-12-02T00:06:00'), temperature: 60.1 },
{ timestamp: new Date('2024-12-02T00:07:00'), temperature: 61.3 },
{ timestamp: new Date('2024-12-02T00:08:00'), temperature: 62.0 },
{ timestamp: new Date('2024-12-02T00:09:00'), temperature: 63.5 },
{ timestamp: new Date('2024-12-02T00:10:00'), temperature: 64.0 },
{ timestamp: new Date('2024-12-02T00:11:00'), temperature: 62.8 },
{ timestamp: new Date('2024-12-02T00:12:00'), temperature: 61.5 },
{ timestamp: new Date('2024-12-02T00:13:00'), temperature: 60.2 },
{ timestamp: new Date('2024-12-02T00:14:00'), temperature: 59.8 },
{ timestamp: new Date('2024-12-02T00:15:00'), temperature: 58.6 },
{ timestamp: new Date('2024-12-02T00:16:00'), temperature: 57.4 },
{ timestamp: new Date('2024-12-02T00:17:00'), temperature: 56.2 },
{ timestamp: new Date('2024-12-02T00:18:00'), temperature: 55.7 },
{ timestamp: new Date('2024-12-02T00:19:00'), temperature: 54.5 },
{ timestamp: new Date('2024-12-02T00:20:00'), temperature: 53.2 },
{ timestamp: new Date('2024-12-02T00:21:00'), temperature: 52.8 },
{ timestamp: new Date('2024-12-02T00:22:00'), temperature: 51.9 },
{ timestamp: new Date('2024-12-02T00:23:00'), temperature: 50.5 },
{ timestamp: new Date('2024-12-02T00:24:00'), temperature: 49.8 },
{ timestamp: new Date('2024-12-02T00:25:00'), temperature: 48.7 },
{ timestamp: new Date('2024-12-02T00:26:00'), temperature: 47.5 },
{ timestamp: new Date('2024-12-02T00:27:00'), temperature: 46.3 },
{ timestamp: new Date('2024-12-02T00:28:00'), temperature: 45.9 },
{ timestamp: new Date('2024-12-02T00:29:00'), temperature: 45.0 }
];
// Create an AVL tree to store CPU temperature data
const cpuTemperatureTree = new AVLTree<Date, number, Datum>(cpuData, {
toEntryFn: ({ timestamp, temperature }) => [timestamp, temperature]
});
// Query a specific time range (e.g., from 00:05 to 00:15)
const rangeStart = new Date('2024-12-02T00:05:00');
const rangeEnd = new Date('2024-12-02T00:15:00');
const rangeResults = cpuTemperatureTree.rangeSearch([rangeStart, rangeEnd], node => ({
minute: node ? node.key.getMinutes() : 0,
temperature: cpuTemperatureTree.get(node ? node.key : undefined)
}));
console.log(rangeResults); // [
// { minute: 5, temperature: 59.4 },
// { minute: 6, temperature: 60.1 },
// { minute: 7, temperature: 61.3 },
// { minute: 8, temperature: 62 },
// { minute: 9, temperature: 63.5 },
// { minute: 10, temperature: 64 },
// { minute: 11, temperature: 62.8 },
// { minute: 12, temperature: 61.5 },
// { minute: 13, temperature: 60.2 },
// { minute: 14, temperature: 59.8 },
// { minute: 15, temperature: 58.6 }
// ]
```
[//]: # (No deletion!!! End of Example Replace Section)
[](https://data-structure-typed-docs.vercel.app)
[](https://vivid-algorithm.vercel.app)
<a href="https://github.com/zrwusa/vivid-algorithm" target="_blank">Examples Repository</a>
<table>
<thead>
<tr>
<th>Data Structure</th>
<th>Unit Test</th>
<th>Performance Test</th>
<th>API Docs</th>
</tr>
</thead>
<tbody>
<tr>
<td>AVL Tree</td>
<td><img src="https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg" alt=""></td>
<td><img src="https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg" alt=""></td>
<td><a href="https://data-structure-typed-docs.vercel.app/classes/AVLTree.html"><span>AVLTree</span></a></td>
</tr>
</tbody>
</table>
<table>
<thead>
<tr>
<th>Data Structure Typed</th>
<th>C++ STL</th>
<th>java.util</th>
<th>Python collections</th>
</tr>
</thead>
<tbody>
<tr>
<td>AVLTree<K, V></td>
<td>-</td>
<td>-</td>
<td>-</td>
</tr>
</tbody>
</table>
[//]: # (No deletion!!! Start of Replace Section)
<div class="json-to-html-collapse clearfix 0">
<div class='collapsible level0' ><span class='json-to-html-label'>avl-tree</span></div>
<div class="content"><table style="display: table; width:100%; table-layout: fixed;"><tr><th>test name</th><th>time taken (ms)</th><th>executions per sec</th><th>sample deviation</th></tr><tr><td>10,000 add randomly</td><td>31.32</td><td>31.93</td><td>3.67e-4</td></tr><tr><td>10,000 add & delete randomly</td><td>70.90</td><td>14.10</td><td>0.00</td></tr><tr><td>10,000 addMany</td><td>40.58</td><td>24.64</td><td>4.87e-4</td></tr><tr><td>10,000 get</td><td>27.31</td><td>36.62</td><td>2.00e-4</td></tr></table></div>
</div>
[//]: # (No deletion!!! End of Replace Section)
## Built-in classic algorithms
<table>
<thead>
<tr>
<th>Algorithm</th>
<th>Function Description</th>
<th>Iteration Type</th>
</tr>
</thead>
<tbody>
<tr>
<td>Binary Tree DFS</td>
<td>Traverse a binary tree in a depth-first manner, starting from the root node, first visiting the left subtree,
and then the right subtree, using recursion.
</td>
<td>Recursion + Iteration</td>
</tr>
<tr>
<td>Binary Tree BFS</td>
<td>Traverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level
from left to right.
</td>
<td>Iteration</td>
</tr>
<tr>
<td>Binary Tree Morris</td>
<td>Morris traversal is an in-order traversal algorithm for binary trees with O(1) space complexity. It allows tree
traversal without additional stack or recursion.
</td>
<td>Iteration</td>
</tr>
</tbody>
</table>
## Software Engineering Design Standards
<table>
<tr>
<th>Principle</th>
<th>Description</th>
</tr>
<tr>
<td>Practicality</td>
<td>Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.</td>
</tr>
<tr>
<td>Extensibility</td>
<td>Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.</td>
</tr>
<tr>
<td>Modularization</td>
<td>Includes data structure modularization and independent NPM packages.</td>
</tr>
<tr>
<td>Efficiency</td>
<td>All methods provide time and space complexity, comparable to native JS performance.</td>
</tr>
<tr>
<td>Maintainability</td>
<td>Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.</td>
</tr>
<tr>
<td>Testability</td>
<td>Automated and customized unit testing, performance testing, and integration testing.</td>
</tr>
<tr>
<td>Portability</td>
<td>Plans for porting to Java, Python, and C++, currently achieved to 80%.</td>
</tr>
<tr>
<td>Reusability</td>
<td>Fully decoupled, minimized side effects, and adheres to OOP.</td>
</tr>
<tr>
<td>Security</td>
<td>Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.</td>
</tr>
<tr>
<td>Scalability</td>
<td>Data structure software does not involve load issues.</td>
</tr>
</table>