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Package detail

undirected-graph-typed

zrwusa599MIT2.2.7TypeScript support: included

Undirected Graph

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readme

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What

Brief

This is a standalone Undirected Graph 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 package

How

install

npm

npm i undirected-graph-typed --save

yarn

yarn add undirected-graph-typed

snippet

basic UndirectedGraph vertex and edge creation

 // Create a simple undirected graph
    const graph = new UndirectedGraph<string>();

    // Add vertices
    graph.addVertex('A');
    graph.addVertex('B');
    graph.addVertex('C');
    graph.addVertex('D');

    // Verify vertices exist
    console.log(graph.hasVertex('A')); // true;
    console.log(graph.hasVertex('B')); // true;
    console.log(graph.hasVertex('E')); // false;

    // Check vertex count
    console.log(graph.size); // 4;

UndirectedGraph edge operations (bidirectional)

 const graph = new UndirectedGraph<string>();

    // Add vertices
    graph.addVertex('A');
    graph.addVertex('B');
    graph.addVertex('C');

    // Add undirected edges (both directions automatically)
    graph.addEdge('A', 'B', 1);
    graph.addEdge('B', 'C', 2);
    graph.addEdge('A', 'C', 3);

    // Verify edges exist in both directions
    console.log(graph.hasEdge('A', 'B')); // true;
    console.log(graph.hasEdge('B', 'A')); // true; // Bidirectional!

    console.log(graph.hasEdge('C', 'B')); // true;
    console.log(graph.hasEdge('B', 'C')); // true; // Bidirectional!

    // Get neighbors of A
    const neighborsA = graph.getNeighbors('A');
    console.log(neighborsA[0].key); // 'B';
    console.log(neighborsA[1].key); // 'C';

UndirectedGraph deleteEdge and vertex operations

 const graph = new UndirectedGraph<string>();

    // Build a simple undirected graph
    graph.addVertex('X');
    graph.addVertex('Y');
    graph.addVertex('Z');
    graph.addEdge('X', 'Y', 1);
    graph.addEdge('Y', 'Z', 2);
    graph.addEdge('X', 'Z', 3);

    // Delete an edge
    graph.deleteEdge('X', 'Y');
    console.log(graph.hasEdge('X', 'Y')); // false;

    // Bidirectional deletion confirmed
    console.log(graph.hasEdge('Y', 'X')); // false;

    // Other edges should remain
    console.log(graph.hasEdge('Y', 'Z')); // true;
    console.log(graph.hasEdge('Z', 'Y')); // true;

    // Delete a vertex
    graph.deleteVertex('Y');
    console.log(graph.hasVertex('Y')); // false;
    console.log(graph.size); // 2;

UndirectedGraph connectivity and neighbors

 const graph = new UndirectedGraph<string>();

    // Build a friendship network
    const people = ['Alice', 'Bob', 'Charlie', 'Diana', 'Eve'];
    for (const person of people) {
      graph.addVertex(person);
    }

    // Add friendships (undirected edges)
    graph.addEdge('Alice', 'Bob', 1);
    graph.addEdge('Alice', 'Charlie', 1);
    graph.addEdge('Bob', 'Diana', 1);
    graph.addEdge('Charlie', 'Eve', 1);
    graph.addEdge('Diana', 'Eve', 1);

    // Get friends of each person
    const aliceFriends = graph.getNeighbors('Alice');
    console.log(aliceFriends[0].key); // 'Bob';
    console.log(aliceFriends[1].key); // 'Charlie';
    console.log(aliceFriends.length); // 2;

    const dianaFriends = graph.getNeighbors('Diana');
    console.log(dianaFriends[0].key); // 'Bob';
    console.log(dianaFriends[1].key); // 'Eve';
    console.log(dianaFriends.length); // 2;

    // Verify bidirectional friendship
    const bobFriends = graph.getNeighbors('Bob');
    console.log(bobFriends[0].key); // 'Alice'; // Alice -> Bob -> Alice ✓
    console.log(bobFriends[1].key); // 'Diana';

UndirectedGraph for social network connectivity analysis

 interface Person {
      id: number;
      name: string;
      location: string;
    }

    // UndirectedGraph is perfect for modeling symmetric relationships
    // (friendships, collaborations, partnerships)
    const socialNetwork = new UndirectedGraph<number, Person>();

    // Add people as vertices
    const people: [number, Person][] = [
      [1, { id: 1, name: 'Alice', location: 'New York' }],
      [2, { id: 2, name: 'Bob', location: 'San Francisco' }],
      [3, { id: 3, name: 'Charlie', location: 'Boston' }],
      [4, { id: 4, name: 'Diana', location: 'New York' }],
      [5, { id: 5, name: 'Eve', location: 'Seattle' }]
    ];

    for (const [id] of people) {
      socialNetwork.addVertex(id);
    }

    // Add friendships (automatically bidirectional)
    socialNetwork.addEdge(1, 2, 1); // Alice <-> Bob
    socialNetwork.addEdge(1, 3, 1); // Alice <-> Charlie
    socialNetwork.addEdge(2, 4, 1); // Bob <-> Diana
    socialNetwork.addEdge(3, 5, 1); // Charlie <-> Eve
    socialNetwork.addEdge(4, 5, 1); // Diana <-> Eve

    console.log(socialNetwork.size); // 5;

    // Find direct connections for Alice
    const aliceConnections = socialNetwork.getNeighbors(1);
    console.log(aliceConnections[0].key); // 2;
    console.log(aliceConnections[1].key); // 3;
    console.log(aliceConnections.length); // 2;

    // Verify bidirectional connections
    console.log(socialNetwork.hasEdge(1, 2)); // true;
    console.log(socialNetwork.hasEdge(2, 1)); // true; // Friendship works both ways!

    // Remove a person from network
    socialNetwork.deleteVertex(2); // Bob leaves
    console.log(socialNetwork.hasVertex(2)); // false;
    console.log(socialNetwork.size); // 4;

    // Alice loses Bob as a friend
    const updatedAliceConnections = socialNetwork.getNeighbors(1);
    console.log(updatedAliceConnections[0].key); // 3;
    console.log(updatedAliceConnections[1]); // undefined;

    // Diana loses Bob as a friend
    const dianaConnections = socialNetwork.getNeighbors(4);
    console.log(dianaConnections[0].key); // 5;
    console.log(dianaConnections[1]); // undefined;

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure Unit Test Performance Test API Docs
Undirected Graph UndirectedGraph

Standard library data structure comparison

Data Structure Typed C++ STL java.util Python collections
UndirectedGraph<V, E> - - -

Benchmark

Built-in classic algorithms

Algorithm Function Description Iteration Type
Graph DFS Traverse a graph in a depth-first manner, starting from a given node, exploring along one path as deeply as possible, and backtracking to explore other paths. Used for finding connected components, paths, etc. Recursion + Iteration
Graph BFS Traverse a graph in a breadth-first manner, starting from a given node, first visiting nodes directly connected to the starting node, and then expanding level by level. Used for finding shortest paths, etc. Recursion + Iteration
Graph Tarjan's Algorithm Find strongly connected components in a graph, typically implemented using depth-first search. Recursion
Graph Bellman-Ford Algorithm Finding the shortest paths from a single source, can handle negative weight edges Iteration
Graph Dijkstra's Algorithm Finding the shortest paths from a single source, cannot handle negative weight edges Iteration
Graph Floyd-Warshall Algorithm Finding the shortest paths between all pairs of nodes Iteration
Graph getCycles Find all cycles in a graph or detect the presence of cycles. Recursion
Graph getCutVertexes Find cut vertices in a graph, which are nodes that, when removed, increase the number of connected components in the graph. Recursion
Graph getSCCs Find strongly connected components in a graph, which are subgraphs where any two nodes can reach each other. Recursion
Graph getBridges Find bridges in a graph, which are edges that, when removed, increase the number of connected components in the graph. Recursion
Graph topologicalSort Perform topological sorting on a directed acyclic graph (DAG) to find a linear order of nodes such that all directed edges go from earlier nodes to later nodes. Recursion

Software Engineering Design Standards

Principle Description
Practicality Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.
Extensibility Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.
Modularization Includes data structure modularization and independent NPM packages.
Efficiency All methods provide time and space complexity, comparable to native JS performance.
Maintainability Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.
Testability Automated and customized unit testing, performance testing, and integration testing.
Portability Plans for porting to Java, Python, and C++, currently achieved to 80%.
Reusability Fully decoupled, minimized side effects, and adheres to OOP.
Security Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.
Scalability Data structure software does not involve load issues.