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Merge pull request mgechev#10 from AndreyGeonya/first-docs
add first docs, fix readme
2 parents 023167c + 5dda0d1 commit 3371243

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‎.gitignore‎

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node_modules
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npm-debug.log

‎gulpfile.js‎

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gulp = require('gulp');
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gulp.task('jsdoc', function () {
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gulp.src('./src/**/*.js')
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gulp.src(['./src/**/*.js', "readme.md"])
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.pipe(jsdoc('../javascript-algorithms-docs'));
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});

‎readme.md‎

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## Note
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## About
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Note that not all algorithms are well tested so bugs are quite possible.
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This repository contains JavaScript implementations of different famous Computer Science algorithms.
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## About
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API reference with usage examples available <a href="https://mgechev.github.io/javascript-algorithms/" target="_blank">here</a>.
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*Note: not all algorithms are well tested so bugs are quite possible.*
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## Development
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To install all dev dependencies use:
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```Bash
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npm install
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```
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To setup documentation repository:
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* go to the parent directory of the root of `javascript-algorithms`;
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* clone `javascript-algorithms` to directory called `javascript-algorithms-docs` (`git clone git@github.com:mgechev/javascript-algorithms.git javascript-algorithms-docs`);
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* change current branch in `javascript-algorithms-docs` to `gh-pages` (`git checkout gh-pages`).
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To generate documentation call:
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`gulp jsdocs` inside `javascript-algorithms` folder. Content of the `javascript-algorithms-docs` will be updated and you will be able to look it in your browser.
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This repository contains different famous Computer Science algorithms implemented in JavaScript
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In order to run the tests use:
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To run tests use:
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```Bash
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jasmine-node test/
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./node_modules/jasmine-node/bin/jasmine-node test/
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```
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and all `*.spec.js` files will be executed.
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## License
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The code in this repository is distributed under the terms of the MIT license.
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The code in this repository is distributed under the terms of the MIT license.

‎src/graphs/others/topological-sort.js‎

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(function (exports) {
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'use strict';
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/**
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* Complexity O(|E|), where E is the set
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* which contains all edges and |E| is their count.
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*/
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var topologicalSort = (function () {
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function topologicalSortHelper(node, visited, temp, graph, result) {
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}
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/**
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* Implements the topological sort algorithm.
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* Topological sort algorithm of a directed acyclic graph.<br><br>
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* Time complexity: O(|E|) where E is a number of edges.
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*
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* @public
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* @param {object} graph A graph represented with list of neighbors
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* @return {array} The list containing all nodes in topological sorted order
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* @module graphs/others/topological-sort
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* @param {Array} graph Adjacency list, which represents the graph.
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* @returns {Array} Ordered vertices.
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*
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* @example
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* var topsort = require('path-to-algorithms/src/graphs/others/topological-sort').topologicalSort;
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* var graph = {
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* v1: ['v2', 'v5'],
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* v2: [],
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* v3: ['v1', 'v2', 'v4', 'v5'],
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* v4: [],
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* v5: []
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* };
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* var vertices = topsort(graph); // ['v3', 'v4', 'v1', 'v5', 'v2']
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*/
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return function (graph) {
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var result = [],
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exports.topologicalSort = topologicalSort;
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}(typeof exports === 'undefined' ? window : exports));
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}(typeof exports === 'undefined' ? window : exports));

‎src/graphs/searching/bfs.js‎

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/**
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* Breath-First graph searching algorithm.
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* Returns the shortest path between startNode and targetNode.
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* Time complexity O(|V|*|V|).
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* Returns the shortest path between startNode and targetNode.<br><br>
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* Time complexity: O(|V|^2).
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*
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* @module graphs/searching
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* @public
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* @param {array} graph The adjust matrix, which represents the graph
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* @param {number} startNode The start node
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* @param {number} targetNode The target, which should be reached
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* @module graphs/searching/bfs
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* @param {Array} graph Adjacency matrix, which represents the graph.
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* @returns {array} The shortest path from startNode to targetNode
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* @param {Number} startNode Start node.
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* @param {Number} targetNode Target, which should be reached.
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* @returns {Array} Shortest path from startNode to targetNode.
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exports.bfs = bfs;
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}((typeof window === 'undefined') ? module.exports : window));
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}((typeof window === 'undefined') ? module.exports : window));

‎src/graphs/searching/dfs.js‎

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/**
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* Depth-First Search graph searching algorithm.
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* Finds out whether there's a path between
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* two nodes - start node and a target.
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*/
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(function (exports) {
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'use strict';
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var dfs = (function () {
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/**
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* Implements an iterative DFS.
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* Complexity O(|V|^2), since it uses adjust matrix.
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*/
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function hasPath(graph, current, goal) {
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var stack = [],
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visited = [],
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}
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/**
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* Returns whether there's a path between two nodes
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* in a graph represented with adjust matrix.
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* Depth-First graph searching algorithm.
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* Returns whether there's a path between two nodes in a graph.<br><br>
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* Time complexity: O(|V|^2).
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*
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* @module graphs/searching/dfs
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* @public
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* @param {array} graph Adjust matrix representation of a graph
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* @param {number} start A start node
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* @param {number} goal The target node
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* @return {boolean} Returns whether there's a path between start and goal
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* @param {Array} graph Adjacency matrix, which represents the graph.
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* @param {Number} start Start node.
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* @param {Number} goal Target node.
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* @return {Boolean} Returns true if path between two nodes exists.
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*
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* @example
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* var dfs = require('../src/graphs/searching/dfs').dfs;
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* var graph = [[1, 1, 0, 0, 1, 0],
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* [1, 0, 1, 0, 1, 0],
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* [0, 1, 0, 1, 0, 0],
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* [0, 0, 1, 0, 1, 1],
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* [1, 1, 0, 1, 0, 0],
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* [0, 0, 0, 1, 0, 0]];
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* var pathExists = dfs(graph, 1, 5); // true
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*/
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return function (graph, start, goal) {
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return hasPath(graph, start, goal);
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exports.dfs = dfs;
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}(typeof exports === 'undefined' ? window : exports));
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}(typeof exports === 'undefined' ? window : exports));

‎src/graphs/shortest-path/bellman-ford.js‎

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this.weight = weight;
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}
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// Complexity O(|V||E|)
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/**
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* Bellman–Ford algorithm computes shortest paths from a single source
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* vertex to all of the other vertices in a weighted digraph (negative weights allowed).<br><br>
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* Time complexity: O(|V||E|) where V and E are the number of vertices and edges respectively.
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*
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* @public
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* @module graphs/shortest-path/bellman-ford
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* @param {Array} vertexes Vertices of the graph.
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* @param {Array} edges Edges of the graph.
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* @param {Number} source Start vertex.
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* @returns {Object} Object with two arrays (parents and distances) with shortest-path information.
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*
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* @example
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* require('path-to-algorithms/src/graphs/shortest-path/bellman-ford');
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*
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* var glob = (typeof window === 'undefined') ? global : window;
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* var Edge = glob.Edge;
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* var bellmanFord = glob.bellmanFord;
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* var edges = [];
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* var vertexes = [0, 1, 2, 3, 4];
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*
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* edges.push(new Edge(0, 1, -1));
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* edges.push(new Edge(0, 2, 4));
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* edges.push(new Edge(1, 2, 3));
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* edges.push(new Edge(1, 3, 2));
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* edges.push(new Edge(3, 1, 1));
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* edges.push(new Edge(4, 3, -3));
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* edges.push(new Edge(1, 4, 2));
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* edges.push(new Edge(3, 2, 5));
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*
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* // {
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* // parents: { '0': null, '1': 0, '2': 1, '3': 4, '4': 1 },
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* // distances: { '0': 0, '1': -1, '2': 2, '3': -2, '4': 1 }
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* // }
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* var pathInfo = bellmanFord(vertexes, edges, 0);
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*/
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function bellmanFord(vertexes, edges, source) {
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var distances = {}, parents = {}, c;
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for (var i = 0; i < vertexes.length; i += 1) {
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global.Edge = Edge;
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global.bellmanFord = bellmanFord;
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}((typeof window === 'undefined') ? global : window));
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// var glob = (typeof window === 'undefined') ? global : window;
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// var Edge = glob.Edge;
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// var bellmanFord = glob.bellmanFord;
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// var edges = [];
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// var vertexes = [0, 1, 2, 3, 4];
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// edges.push(new Edge(0, 1, -1));
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// edges.push(new Edge(0, 2, 4));
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// edges.push(new Edge(1, 2, 3));
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// edges.push(new Edge(1, 3, 2));
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// edges.push(new Edge(3, 1, 1));
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// edges.push(new Edge(4, 3, -3));
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// edges.push(new Edge(1, 4, 2));
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// edges.push(new Edge(3, 2, 5));
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//
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// console.log(bellmanFord(vertexes, edges, 0));
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}((typeof window === 'undefined') ? global : window));

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