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structure","datastructure","data-structure","data structures","datastructures","data-structures","in data structures","in data structure","DataStructure","DataStructures","traversal","inorder","preorder","postorder","pre","in","post","order","pre-order","pre order","in-order","in order","post-order","post order","dfs","DFS","bfs","BFS","recursive","iterative","leaf","root","parent","child","node","depth","height","Node.js","CommonJS","ES6","UMD","esmodule","java.util","c++ stl","c++ std","Python collections","System.Collections.Generic","STL","stl","util","collection","Collection","collections","Collections"],"repository":{"type":"git","url":"git+https://github.com/zrwusa/data-structure-typed.git"},"description":"Standard AVL tree","maintainers":[{"name":"zrwusa.org","email":"zrwusa@gmail.com"}],"readme":"![NPM](https://img.shields.io/npm/l/avl-tree-typed)\n![GitHub top language](https://img.shields.io/github/languages/top/zrwusa/data-structure-typed)\n![npm](https://img.shields.io/npm/dw/avl-tree-typed)\n![eslint](https://aleen42.github.io/badges/src/eslint.svg)\n![npm bundle size](https://img.shields.io/bundlephobia/minzip/avl-tree-typed)\n![npm bundle size](https://img.shields.io/bundlephobia/min/avl-tree-typed)\n![npm](https://img.shields.io/npm/v/avl-tree-typed)\n\n# What\n\n## Brief\n\nThis is a standalone AVL Tree data structure from the data-structure-typed collection. If you wish to access more data\nstructures or advanced features, you can transition to directly installing the\ncomplete [data-structure-typed](https://www.npmjs.com/package/data-structure-typed) package\n\n# How\n\n## install\n\n### npm\n\n```bash\nnpm i avl-tree-typed --save\n```\n\n### yarn\n\n```bash\nyarn add avl-tree-typed\n```\n\n### snippet\n\n#### TS\n\n```typescript\nimport {AVLTree, AVLTreeNode} from 'data-structure-typed';\n// /* or if you prefer */ import {AVLTree} from 'avl-tree-typed';\n\nconst avlTree = new AVLTree<AVLTreeNode<number>>();\n\nconst idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];\navlTree.addMany(idsOrVals, idsOrVals);\n\nconst node6 = avlTree.get(6);\nnode6 && avlTree.getHeight(node6)           // 3\nnode6 && avlTree.getDepth(node6)            // 1\nconst getNodeById = avlTree.get(10, 'id');\ngetNodeById?.id                             // 10\n\nconst getMinNodeByRoot = avlTree.getLeftMost();\ngetMinNodeByRoot?.id                        // 1\n\nconst node15 = avlTree.get(15);\nconst getMinNodeBySpecificNode = node15 && avlTree.getLeftMost(node15);\ngetMinNodeBySpecificNode?.id                // 12\n\nconst subTreeSum = node15 && avlTree.subTreeSum(node15);\nsubTreeSum                                  // 70\n\nconst lesserSum = avlTree.lesserSum(10);\nlesserSum                                   // 45\n\nconst node11 = avlTree.get(11);\nnode11?.id                                  // 11\n\nconst dfs = avlTree.DFS('in', 'node');\ndfs[0].id                                   // 1 \navlTree.perfectlyBalance();\nconst bfs = avlTree.BFS('node');\navlTree.isPerfectlyBalanced() && bfs[0].id  // 8 \n\navlTree.remove(11, true)[0].deleted?.id     // 11\navlTree.isAVLBalanced();                    // true\nnode15 && avlTree.getHeight(node15)         // 2\navlTree.remove(1, true)[0].deleted?.id      // 1\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 4\n\navlTree.remove(4, true)[0].deleted?.id      // 4\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 4\n\navlTree.remove(10, true)[0].deleted?.id     // 10\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(15, true)[0].deleted?.id     // 15\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(5, true)[0].deleted?.id      // 5\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(13, true)[0].deleted?.id     // 13\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(3, true)[0].deleted?.id      // 3\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(8, true)[0].deleted?.id      // 8\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(6, true)[0].deleted?.id      // 6\navlTree.remove(6, true).length              // 0\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 2\n\navlTree.remove(7, true)[0].deleted?.id      // 7\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 2\n\navlTree.remove(9, true)[0].deleted?.id      // 9\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 2\n\navlTree.remove(14, true)[0].deleted?.id     // 14\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 1\n\navlTree.isAVLBalanced();                    // true\nconst lastBFSIds = avlTree.BFS();\nlastBFSIds[0]                               // 12 \n\nconst lastBFSNodes = avlTree.BFS('node');\nlastBFSNodes[0].id                          // 12\n```\n\n#### JS\n\n```javascript\nconst {AVLTree} = require('data-structure-typed');\n// /* or if you prefer */ const {AVLTree} = require('avl-tree-typed');\n\nconst avlTree = new AVLTree();\n\nconst idsOrVals = [11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];\navlTree.addMany(idsOrVals, idsOrVals);\n\nconst node6 = avlTree.get(6);\nnode6 && avlTree.getHeight(node6)           // 3\nnode6 && avlTree.getDepth(node6)            // 1\nconst getNodeById = avlTree.get(10, 'id');\ngetNodeById?.id                             // 10\n\nconst getMinNodeByRoot = avlTree.getLeftMost();\ngetMinNodeByRoot?.id                        // 1\n\nconst node15 = avlTree.get(15);\nconst getMinNodeBySpecificNode = node15 && avlTree.getLeftMost(node15);\ngetMinNodeBySpecificNode?.id                // 12\n\nconst subTreeSum = node15 && avlTree.subTreeSum(node15);\nsubTreeSum                                  // 70\n\nconst lesserSum = avlTree.lesserSum(10);\nlesserSum                                   // 45\n\nconst node11 = avlTree.get(11);\nnode11?.id                                  // 11\n\nconst dfs = avlTree.DFS('in', 'node');\ndfs[0].id                                   // 1 \navlTree.perfectlyBalance();\nconst bfs = avlTree.BFS('node');\navlTree.isPerfectlyBalanced() && bfs[0].id  // 8 \n\navlTree.remove(11, true)[0].deleted?.id     // 11\navlTree.isAVLBalanced();                    // true\nnode15 && avlTree.getHeight(node15)         // 2\navlTree.remove(1, true)[0].deleted?.id      // 1\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 4\n\navlTree.remove(4, true)[0].deleted?.id      // 4\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 4\n\navlTree.remove(10, true)[0].deleted?.id     // 10\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(15, true)[0].deleted?.id     // 15\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(5, true)[0].deleted?.id      // 5\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(13, true)[0].deleted?.id     // 13\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(3, true)[0].deleted?.id      // 3\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(8, true)[0].deleted?.id      // 8\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 3\n\navlTree.remove(6, true)[0].deleted?.id      // 6\navlTree.remove(6, true).length              // 0\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 2\n\navlTree.remove(7, true)[0].deleted?.id      // 7\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 2\n\navlTree.remove(9, true)[0].deleted?.id      // 9\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 2\n\navlTree.remove(14, true)[0].deleted?.id     // 14\navlTree.isAVLBalanced();                    // true\navlTree.getHeight()                         // 1\n\navlTree.isAVLBalanced();                    // true\nconst lastBFSIds = avlTree.BFS();\nlastBFSIds[0]                               // 12 \n\nconst lastBFSNodes = avlTree.BFS('node');\nlastBFSNodes[0].id                          // 12\n```\n\n[//]: # (No deletion!!! Start of Example Replace Section)\n\n### Find elements in a range\n```typescript\n    type Datum = { timestamp: Date; temperature: number };\n    // Fixed dataset of CPU temperature readings\n    const cpuData: Datum[] = [\n      { timestamp: new Date('2024-12-02T00:00:00'), temperature: 55.1 },\n      { timestamp: new Date('2024-12-02T00:01:00'), temperature: 56.3 },\n      { timestamp: new Date('2024-12-02T00:02:00'), temperature: 54.8 },\n      { timestamp: new Date('2024-12-02T00:03:00'), temperature: 57.2 },\n      { timestamp: new Date('2024-12-02T00:04:00'), temperature: 58.0 },\n      { timestamp: new Date('2024-12-02T00:05:00'), temperature: 59.4 },\n      { timestamp: new Date('2024-12-02T00:06:00'), temperature: 60.1 },\n      { timestamp: new Date('2024-12-02T00:07:00'), temperature: 61.3 },\n      { timestamp: new Date('2024-12-02T00:08:00'), temperature: 62.0 },\n      { timestamp: new Date('2024-12-02T00:09:00'), temperature: 63.5 },\n      { timestamp: new Date('2024-12-02T00:10:00'), temperature: 64.0 },\n      { timestamp: new Date('2024-12-02T00:11:00'), temperature: 62.8 },\n      { timestamp: new Date('2024-12-02T00:12:00'), temperature: 61.5 },\n      { timestamp: new Date('2024-12-02T00:13:00'), temperature: 60.2 },\n      { timestamp: new Date('2024-12-02T00:14:00'), temperature: 59.8 },\n      { timestamp: new Date('2024-12-02T00:15:00'), temperature: 58.6 },\n      { timestamp: new Date('2024-12-02T00:16:00'), temperature: 57.4 },\n      { timestamp: new Date('2024-12-02T00:17:00'), temperature: 56.2 },\n      { timestamp: new Date('2024-12-02T00:18:00'), temperature: 55.7 },\n      { timestamp: new Date('2024-12-02T00:19:00'), temperature: 54.5 },\n      { timestamp: new Date('2024-12-02T00:20:00'), temperature: 53.2 },\n      { timestamp: new Date('2024-12-02T00:21:00'), temperature: 52.8 },\n      { timestamp: new Date('2024-12-02T00:22:00'), temperature: 51.9 },\n      { timestamp: new Date('2024-12-02T00:23:00'), temperature: 50.5 },\n      { timestamp: new Date('2024-12-02T00:24:00'), temperature: 49.8 },\n      { timestamp: new Date('2024-12-02T00:25:00'), temperature: 48.7 },\n      { timestamp: new Date('2024-12-02T00:26:00'), temperature: 47.5 },\n      { timestamp: new Date('2024-12-02T00:27:00'), temperature: 46.3 },\n      { timestamp: new Date('2024-12-02T00:28:00'), temperature: 45.9 },\n      { timestamp: new Date('2024-12-02T00:29:00'), temperature: 45.0 }\n    ];\n\n    // Create an AVL tree to store CPU temperature data\n    const cpuTemperatureTree = new AVLTree<Date, number, Datum>(cpuData, {\n      toEntryFn: ({ timestamp, temperature }) => [timestamp, temperature]\n    });\n\n    // Query a specific time range (e.g., from 00:05 to 00:15)\n    const rangeStart = new Date('2024-12-02T00:05:00');\n    const rangeEnd = new Date('2024-12-02T00:15:00');\n    const rangeResults = cpuTemperatureTree.rangeSearch([rangeStart, rangeEnd], node => ({\n      minute: node ? node.key.getMinutes() : 0,\n      temperature: cpuTemperatureTree.get(node ? node.key : undefined)\n    }));\n\n    console.log(rangeResults); //  [\n //            { minute: 5, temperature: 59.4 },\n //            { minute: 6, temperature: 60.1 },\n //            { minute: 7, temperature: 61.3 },\n //            { minute: 8, temperature: 62 },\n //            { minute: 9, temperature: 63.5 },\n //            { minute: 10, temperature: 64 },\n //            { minute: 11, temperature: 62.8 },\n //            { minute: 12, temperature: 61.5 },\n //            { minute: 13, temperature: 60.2 },\n //            { minute: 14, temperature: 59.8 },\n //            { minute: 15, temperature: 58.6 }\n //          ]\n```\n\n[//]: # (No deletion!!! End of Example Replace Section)\n\n## API docs & Examples\n\n[API Docs](https://data-structure-typed-docs.vercel.app)\n\n[Live Examples](https://vivid-algorithm.vercel.app)\n\n<a href=\"https://github.com/zrwusa/vivid-algorithm\" target=\"_blank\">Examples Repository</a>\n\n## Data Structures\n\n<table>\n<thead>\n<tr>\n<th>Data Structure</th>\n<th>Unit Test</th>\n<th>Performance Test</th>\n<th>API Docs</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>AVL Tree</td>\n<td><img src=\"https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg\" alt=\"\"></td>\n<td><img src=\"https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg\" alt=\"\"></td>\n<td><a href=\"https://data-structure-typed-docs.vercel.app/classes/AVLTree.html\"><span>AVLTree</span></a></td>\n</tr>\n</tbody>\n</table>\n\n## Standard library data structure comparison\n\n<table>\n  <thead>\n  <tr>\n    <th>Data Structure Typed</th>\n    <th>C++ STL</th>\n    <th>java.util</th>\n    <th>Python collections</th>\n  </tr>\n  </thead>\n  <tbody>\n  \n  <tr>\n    <td>AVLTree&lt;K, V&gt;</td>\n    <td>-</td>\n    <td>-</td>\n    <td>-</td>\n  </tr>\n \n  </tbody>\n</table>\n\n## Benchmark\n\n[//]: # (No deletion!!! Start of Replace Section)\n<div class=\"json-to-html-collapse clearfix 0\">\n      <div class='collapsible level0' ><span class='json-to-html-label'>avl-tree</span></div>\n      <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>\n    </div>\n\n[//]: # (No deletion!!! End of Replace Section)\n\n## Built-in classic algorithms\n\n<table>\n  <thead>\n  <tr>\n    <th>Algorithm</th>\n    <th>Function Description</th>\n    <th>Iteration Type</th>\n  </tr>\n  </thead>\n  <tbody>\n  <tr>\n    <td>Binary Tree DFS</td>\n    <td>Traverse a binary tree in a depth-first manner, starting from the root node, first visiting the left subtree,\n      and then the right subtree, using recursion.\n    </td>\n    <td>Recursion + Iteration</td>\n  </tr>\n  <tr>\n    <td>Binary Tree BFS</td>\n    <td>Traverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level\n      from left to right.\n    </td>\n    <td>Iteration</td>\n  </tr>\n  <tr>\n    <td>Binary Tree Morris</td>\n    <td>Morris traversal is an in-order traversal algorithm for binary trees with O(1) space complexity. It allows tree\n      traversal without additional stack or recursion.\n    </td>\n    <td>Iteration</td>\n  </tr>\n  </tbody>\n</table>\n\n## Software Engineering Design Standards\n<table>\n    <tr>\n        <th>Principle</th>\n        <th>Description</th>\n    </tr>\n    <tr>\n        <td>Practicality</td>\n        <td>Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.</td>\n    </tr>\n    <tr>\n        <td>Extensibility</td>\n        <td>Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.</td>\n    </tr>\n    <tr>\n        <td>Modularization</td>\n        <td>Includes data structure modularization and independent NPM packages.</td>\n    </tr>\n    <tr>\n        <td>Efficiency</td>\n        <td>All methods provide time and space complexity, comparable to native JS performance.</td>\n    </tr>\n    <tr>\n        <td>Maintainability</td>\n        <td>Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.</td>\n    </tr>\n    <tr>\n        <td>Testability</td>\n        <td>Automated and customized unit testing, performance testing, and integration testing.</td>\n    </tr>\n    <tr>\n        <td>Portability</td>\n        <td>Plans for porting to Java, Python, and C++, currently achieved to 80%.</td>\n    </tr>\n    <tr>\n        <td>Reusability</td>\n        <td>Fully decoupled, minimized side effects, and adheres to OOP.</td>\n    </tr>\n    <tr>\n        <td>Security</td>\n        <td>Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.</td>\n    </tr>\n    <tr>\n        <td>Scalability</td>\n        <td>Data structure software does not involve load issues.</td>\n    </tr>\n</table>\n\n\n\n\n\n","readmeFilename":"README.md"}