Skip to content
/ js-graph-algorithms Public

Package provides javascript implementation of algorithms for graph processing

License

MIT license
147 stars 39 forks Branches Tags Activity
Star
Notifications You must be signed in to change notification settings

chen0040/js-graph-algorithms

BranchesTags

Repository files navigation

js-graph-algorithms

Package provides javascript implementation of algorithms for graph processing

Build Status Coverage Status

Features

  • Depth First Search (Link: HTML DEMO)
  • Breadth First Search
  • Connected Components for undirected graph (Link: HTML DEMO)
  • Topoloical Sort (Link: HTML DEMO)
  • Strongly Connected Components for directed graph (Link: HTML DEMO)
  • Minimum Spanning Tree for weighted graph (Kruskal, Prim Lazy, Prim Eager) (Link: HTML DEMO)
  • Shortest Paths (Dijkstra, Bellman-Ford, Topological Sort on DAG) (Link: HTML DEMO)
  • MaxFlow-MinCut (Ford-Fulkerson) (Link: HTML DEMO)

Install

npm install js-graph-algorithms

Usage

Create an undirected unweighted graph

The sample code below shows how to create a undirected and unweighted graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');

var g = new jsgraphs.Graph(6); // 6 is the number vertices in the graph
g.addEdge(0, 5); // add undirected edge connecting vertex 0 to vertex 5
g.addEdge(2, 4);
g.addEdge(2, 3);
g.addEdge(1, 2);
g.addEdge(0, 1);
g.addEdge(3, 4);
g.addEdge(3, 5);
g.addEdge(0, 2);

g.node(2).label = 'Hello'; // assigned 'Hello' as label for node 2
g.edge(0, 2).label = 'World'; // edge between 0 and 2

console.log(g.V); // display 6, which is the number of vertices in g
console.log(g.adj(0)); // display [5, 1, 2], which is the adjacent list to vertex 0

Create directed unweighted graph

The sample code below shows how to create a direted and unweighted graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');

var g = new jsgraphs.DiGraph(13); // 13 is the number vertices in the graph
g.addEdge(4,  2); // add directed edge from 4 to 2
g.addEdge(2,  3);
g.addEdge(3,  2);
g.addEdge(6,  0);
g.addEdge(0,  1);
g.addEdge(2,  0);
g.addEdge(11, 12);
g.addEdge(12,  9);
g.addEdge(9, 10);
g.addEdge(9, 11);
g.addEdge(7,  9);
g.addEdge(10, 12);
g.addEdge(11,  4);
g.addEdge(4,  3);
g.addEdge(3,  5);
g.addEdge(6,  8);
g.addEdge(8,  6);
g.addEdge(5,  4);
g.addEdge(0,  5);
g.addEdge(6,  4);
g.addEdge(6,  9);
g.addEdge(7,  6);

g.node(2).label = 'Hello'; // assign 'Hello' as label for node 2
g.edge(0, 5).label = 'World'; // edge from 0 to 5

console.log(g.V); // display 13, which is the number of vertices in g
console.log(g.adj(0)); // display the adjacency list which are vertices directed from vertex 0

Create undirected weighted graph

The sample code below shows show to create undirected weighted graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedGraph(8); // 8 is the number vertices in the graph
g.addEdge(new jsgraphs.Edge(0, 7, 0.16));
g.addEdge(new jsgraphs.Edge(2, 3, 0.17));
g.addEdge(new jsgraphs.Edge(1, 7, 0.19));
g.addEdge(new jsgraphs.Edge(0, 2, 0.26));
g.addEdge(new jsgraphs.Edge(5, 7, 0.28));
g.addEdge(new jsgraphs.Edge(1, 3, 0.29));
g.addEdge(new jsgraphs.Edge(1, 5, 0.32));
g.addEdge(new jsgraphs.Edge(2, 7, 0.34));
g.addEdge(new jsgraphs.Edge(4, 5, 0.35));
g.addEdge(new jsgraphs.Edge(1, 2, 0.36));
g.addEdge(new jsgraphs.Edge(4, 7, 0.37));
g.addEdge(new jsgraphs.Edge(0, 4, 0.38));
g.addEdge(new jsgraphs.Edge(6, 2, 0.4));
g.addEdge(new jsgraphs.Edge(3, 6, 0.52));
g.addEdge(new jsgraphs.Edge(6, 0, 0.58));
g.addEdge(new jsgraphs.Edge(6, 4, 0.93));

g.node(2).label = 'Hello'; // assign 'Hello' as label for node 2
g.edge(4, 5).label = 'World'; // edge between node 4 and 5

console.log(g.V); // display 13, which is the number of vertices in g
console.log(g.adj(0)); // display the adjacency list which are undirected edges connected to vertex 0

Create directed weighted graph

The sample code below shows show to create directed weighted graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedDiGraph(8); // 8 is the number vertices in the graph
g.addEdge(new jsgraphs.Edge(0, 7, 0.16));
g.addEdge(new jsgraphs.Edge(2, 3, 0.17));
g.addEdge(new jsgraphs.Edge(1, 7, 0.19));
g.addEdge(new jsgraphs.Edge(0, 2, 0.26));
g.addEdge(new jsgraphs.Edge(5, 7, 0.28));
g.addEdge(new jsgraphs.Edge(1, 3, 0.29));
g.addEdge(new jsgraphs.Edge(1, 5, 0.32));
g.addEdge(new jsgraphs.Edge(2, 7, 0.34));
g.addEdge(new jsgraphs.Edge(4, 5, 0.35));
g.addEdge(new jsgraphs.Edge(1, 2, 0.36));
g.addEdge(new jsgraphs.Edge(4, 7, 0.37));
g.addEdge(new jsgraphs.Edge(0, 4, 0.38));
g.addEdge(new jsgraphs.Edge(6, 2, 0.4));
g.addEdge(new jsgraphs.Edge(3, 6, 0.52));
g.addEdge(new jsgraphs.Edge(6, 0, 0.58));
g.addEdge(new jsgraphs.Edge(6, 4, 0.93));

g.node(2).label = 'Hello';
g.edge(4, 5).label = 'World'; // edge from node 4 to node 5

console.log(g.V); // display 13, which is the number of vertices in g
console.log(g.adj(0)); // display the adjacency list which are directed edges from vertex 0

Depth First Search

The sample code below show how to perform depth first search of an undirected graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');

var g = new jsgraphs.Graph(6);
g.addEdge(0, 5);
g.addEdge(2, 4);
g.addEdge(2, 3);
g.addEdge(1, 2);
g.addEdge(0, 1);
g.addEdge(3, 4);
g.addEdge(3, 5);
g.addEdge(0, 2);
var s = 0;
var dfs = new jsgraphs.DepthFirstSearch(g, s);


for(var v=0; v < g.V; ++v) {
 if(dfs.hasPathTo(v)) {
    console.log(s + " is connected to " + v);
    console.log("path: " + dfs.pathTo(v));
 } else {
     console.log('No path from ' + s + ' to ' + v);
 }
}

Connected Components

The sample code below show how to obtain the number of connected components in an undirected graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');

var g = new jsgraphs.Graph(13);
g.addEdge(0, 5);
g.addEdge(4, 3);
g.addEdge(0, 1);
g.addEdge(9, 12);
g.addEdge(6, 4);
g.addEdge(5, 4);
g.addEdge(0, 2);
g.addEdge(11, 12);
g.addEdge(9,10);
g.addEdge(0, 6);
g.addEdge(7, 8);
g.addEdge(9, 11);
g.addEdge(5, 3); 

var cc = new jsgraphs.ConnectedComponents(g);
console.log(cc.componentCount()); // display 3
for (var v = 0; v < g.V; ++v) {
    console.log('id[' + v + ']: ' + cc.componentId(v));
}

Topological Sort

The sample code below show how to obtain the reverse post order of a topological sort in a directed acyclic graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');

var dag = new jsgraphs.DiGraph(7); // must be directed acyclic graph

dag.addEdge(0, 5);
dag.addEdge(0, 2);
dag.addEdge(0, 1);
dag.addEdge(3, 6);
dag.addEdge(3, 5);
dag.addEdge(3, 4);
dag.addEdge(5, 4);
dag.addEdge(6, 4);
dag.addEdge(6, 0);
dag.addEdge(3, 2);
dag.addEdge(1, 4);

var ts = new jsgraphs.TopologicalSort(dag);

var order = ts.order();
console.log(order); // display array which is the topological sort order

Strongly Connected Components for Directed Graph

The sample code below show how to obtain the strongly connected components from a directed graph (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');

var graph = new jsgraphs.DiGraph(13);
graph.addEdge(4, 2);
graph.addEdge(2, 3);
graph.addEdge(3, 2);
graph.addEdge(6, 0);
graph.addEdge(0, 1);
graph.addEdge(2, 0);
graph.addEdge(11, 12);
graph.addEdge(12, 9);
graph.addEdge(9, 10);
graph.addEdge(9, 11);
graph.addEdge(8, 9);
graph.addEdge(10, 12);
graph.addEdge(11, 4);
graph.addEdge(4, 3);
graph.addEdge(3, 5);
graph.addEdge(7, 8);
graph.addEdge(8, 7);
graph.addEdge(5, 4);
graph.addEdge(0, 5);
graph.addEdge(6, 4);
graph.addEdge(6, 9);
graph.addEdge(7, 6);
var scc = new jsgraphs.StronglyConnectedComponents(graph);
console.log(scc.componentCount()); // display 5
for (var v = 0; v < graph.V; ++v) {
    console.log('id[' + v + ']: ' + scc.componentId(v));
}

Use Kruskal algorithm to find the minimum spanning tree of a weighted graph

The sample code below show how to obtain the minimum spanning tree from a weighted graph using Kruskal algorithm (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedGraph(8);

g.addEdge(new jsgraphs.Edge(0, 7, 0.16));
g.addEdge(new jsgraphs.Edge(2, 3, 0.17));
g.addEdge(new jsgraphs.Edge(1, 7, 0.19));
g.addEdge(new jsgraphs.Edge(0, 2, 0.26));
g.addEdge(new jsgraphs.Edge(5, 7, 0.28));
g.addEdge(new jsgraphs.Edge(1, 3, 0.29));
g.addEdge(new jsgraphs.Edge(1, 5, 0.32));
g.addEdge(new jsgraphs.Edge(2, 7, 0.34));
g.addEdge(new jsgraphs.Edge(4, 5, 0.35));
g.addEdge(new jsgraphs.Edge(1, 2, 0.36));
g.addEdge(new jsgraphs.Edge(4, 7, 0.37));
g.addEdge(new jsgraphs.Edge(0, 4, 0.38));
g.addEdge(new jsgraphs.Edge(6, 2, 0.4));
g.addEdge(new jsgraphs.Edge(3, 6, 0.52));
g.addEdge(new jsgraphs.Edge(6, 0, 0.58));
g.addEdge(new jsgraphs.Edge(6, 4, 0.93));

var kruskal = new jsgraphs.KruskalMST(g); 
var mst = kruskal.mst;
for(var i=0; i < mst.length; ++i) {
    var e = mst[i];
    var v = e.either();
    var w = e.other(v);
    console.log('(' + v + ', ' + w + '): ' + e.weight);
}

Use Lazy Prim algorithm to find the minimum spanning tree of a weighted graph

The sample code below show how to obtain the minimum spanning tree from a weighted graph using Lazy Prim algorithm (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedGraph(8);

g.addEdge(new jsgraphs.Edge(0, 7, 0.16));
g.addEdge(new jsgraphs.Edge(2, 3, 0.17));
g.addEdge(new jsgraphs.Edge(1, 7, 0.19));
g.addEdge(new jsgraphs.Edge(0, 2, 0.26));
g.addEdge(new jsgraphs.Edge(5, 7, 0.28));
g.addEdge(new jsgraphs.Edge(1, 3, 0.29));
g.addEdge(new jsgraphs.Edge(1, 5, 0.32));
g.addEdge(new jsgraphs.Edge(2, 7, 0.34));
g.addEdge(new jsgraphs.Edge(4, 5, 0.35));
g.addEdge(new jsgraphs.Edge(1, 2, 0.36));
g.addEdge(new jsgraphs.Edge(4, 7, 0.37));
g.addEdge(new jsgraphs.Edge(0, 4, 0.38));
g.addEdge(new jsgraphs.Edge(6, 2, 0.4));
g.addEdge(new jsgraphs.Edge(3, 6, 0.52));
g.addEdge(new jsgraphs.Edge(6, 0, 0.58));
g.addEdge(new jsgraphs.Edge(6, 4, 0.93));

var prim = new jsgraphs.LazyPrimMST(g); 
var mst = prim.mst;
for(var i=0; i < mst.length; ++i) {
    var e = mst[i];
    var v = e.either();
    var w = e.other(v);
    console.log('(' + v + ', ' + w + '): ' + e.weight);
}

Use Eager Prim algorithm to find the minimum spanning tree of a weighted graph

The sample code below show how to obtain the minimum spanning tree from a weighted graph using Eager Prim algorithm (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedGraph(8);

g.addEdge(new jsgraphs.Edge(0, 7, 0.16));
g.addEdge(new jsgraphs.Edge(2, 3, 0.17));
g.addEdge(new jsgraphs.Edge(1, 7, 0.19));
g.addEdge(new jsgraphs.Edge(0, 2, 0.26));
g.addEdge(new jsgraphs.Edge(5, 7, 0.28));
g.addEdge(new jsgraphs.Edge(1, 3, 0.29));
g.addEdge(new jsgraphs.Edge(1, 5, 0.32));
g.addEdge(new jsgraphs.Edge(2, 7, 0.34));
g.addEdge(new jsgraphs.Edge(4, 5, 0.35));
g.addEdge(new jsgraphs.Edge(1, 2, 0.36));
g.addEdge(new jsgraphs.Edge(4, 7, 0.37));
g.addEdge(new jsgraphs.Edge(0, 4, 0.38));
g.addEdge(new jsgraphs.Edge(6, 2, 0.4));
g.addEdge(new jsgraphs.Edge(3, 6, 0.52));
g.addEdge(new jsgraphs.Edge(6, 0, 0.58));
g.addEdge(new jsgraphs.Edge(6, 4, 0.93));

var prim = new jsgraphs.EagerPrimMST(g); 
var mst = prim.mst;
for(var i=0; i < mst.length; ++i) {
    var e = mst[i];
    var v = e.either();
    var w = e.other(v);
    console.log('(' + v + ', ' + w + '): ' + e.weight);
}

Find the shortest paths using Dijkstra

The sample code below show how to obtain the shortest paths from a starting point 0 on a weighted directed graph using Dijkstra (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedDiGraph(8);
g.addEdge(new jsgraphs.Edge(0, 1, 5.0));
g.addEdge(new jsgraphs.Edge(0, 4, 9.0));
g.addEdge(new jsgraphs.Edge(0, 7, 8.0));
g.addEdge(new jsgraphs.Edge(1, 2, 12.0));
g.addEdge(new jsgraphs.Edge(1, 3, 15.0));
g.addEdge(new jsgraphs.Edge(1, 7, 4.0));
g.addEdge(new jsgraphs.Edge(2, 3, 3.0));
g.addEdge(new jsgraphs.Edge(2, 6, 11.0));
g.addEdge(new jsgraphs.Edge(3, 6, 9.0));
g.addEdge(new jsgraphs.Edge(4, 5, 5.0));
g.addEdge(new jsgraphs.Edge(4, 6, 20.0));
g.addEdge(new jsgraphs.Edge(4, 7, 5.0));
g.addEdge(new jsgraphs.Edge(5, 2, 1.0));
g.addEdge(new jsgraphs.Edge(5, 6, 13.0));
g.addEdge(new jsgraphs.Edge(7, 5, 6.0));
g.addEdge(new jsgraphs.Edge(7, 2, 7.0));  


var dijkstra = new jsgraphs.Dijkstra(g, 0);

for(var v = 1; v < g.V; ++v){
    if(dijkstra.hasPathTo(v)){
        var path = dijkstra.pathTo(v);
        console.log('=====path from 0 to ' + v + ' start==========');
        for(var i = 0; i < path.length; ++i) {
            var e = path[i];
            console.log(e.from() + ' => ' + e.to() + ': ' + e.weight);
        }
        console.log('=====path from 0 to ' + v + ' end==========');
        console.log('=====distance: '  + dijkstra.distanceTo(v) + '=========');
    }
}

Find the shortest paths using Bellman-Ford

The sample code below show how to obtain the shortest paths from a starting point 0 on a weighted directed graph using Bellman-Ford:

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedDiGraph(8);
g.addEdge(new jsgraphs.Edge(0, 1, 5.0));
g.addEdge(new jsgraphs.Edge(0, 4, 9.0));
g.addEdge(new jsgraphs.Edge(0, 7, 8.0));
g.addEdge(new jsgraphs.Edge(1, 2, 12.0));
g.addEdge(new jsgraphs.Edge(1, 3, 15.0));
g.addEdge(new jsgraphs.Edge(1, 7, 4.0));
g.addEdge(new jsgraphs.Edge(2, 3, 3.0));
g.addEdge(new jsgraphs.Edge(2, 6, 11.0));
g.addEdge(new jsgraphs.Edge(3, 6, 9.0));
g.addEdge(new jsgraphs.Edge(4, 5, 5.0));
g.addEdge(new jsgraphs.Edge(4, 6, 20.0));
g.addEdge(new jsgraphs.Edge(4, 7, 5.0));
g.addEdge(new jsgraphs.Edge(5, 2, 1.0));
g.addEdge(new jsgraphs.Edge(5, 6, 13.0));
g.addEdge(new jsgraphs.Edge(7, 5, 6.0));
g.addEdge(new jsgraphs.Edge(7, 2, 7.0));  


var bf = new jsgraphs.BellmanFord(g, 0);

for(var v = 1; v < g.V; ++v){
    if(bf.hasPathTo(v)){
        var path = bf.pathTo(v);
        console.log('=====path from 0 to ' + v + ' start==========');
        for(var i = 0; i < path.length; ++i) {
            var e = path[i];
            console.log(e.from() + ' => ' + e.to() + ': ' + e.weight);
        }
        console.log('=====path from 0 to ' + v + ' end==========');
        console.log('=====distance: '  + bf.distanceTo(v) + '=========');
    }
}

Find the shortest paths using Topological Sort Shortest Paths

The sample code below show how to obtain the shortest paths from a starting point 0 on a weighted directed acylic graph using Topological Sort:

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.WeightedDiGraph(8);
g.addEdge(new jsgraphs.Edge(0, 1, 5.0));
g.addEdge(new jsgraphs.Edge(0, 4, 9.0));
g.addEdge(new jsgraphs.Edge(0, 7, 8.0));
g.addEdge(new jsgraphs.Edge(1, 2, 12.0));
g.addEdge(new jsgraphs.Edge(1, 3, 15.0));
g.addEdge(new jsgraphs.Edge(1, 7, 4.0));
g.addEdge(new jsgraphs.Edge(2, 3, 3.0));
g.addEdge(new jsgraphs.Edge(2, 6, 11.0));
g.addEdge(new jsgraphs.Edge(3, 6, 9.0));
g.addEdge(new jsgraphs.Edge(4, 5, 5.0));
g.addEdge(new jsgraphs.Edge(4, 6, 20.0));
g.addEdge(new jsgraphs.Edge(4, 7, 5.0));
g.addEdge(new jsgraphs.Edge(5, 2, 1.0));
g.addEdge(new jsgraphs.Edge(5, 6, 13.0));
g.addEdge(new jsgraphs.Edge(7, 5, 6.0));
g.addEdge(new jsgraphs.Edge(7, 2, 7.0));  


var bf = new jsgraphs.TopologicalSortShortestPaths(g, 0);

for(var v = 1; v < g.V; ++v){
    if(bf.hasPathTo(v)){
        var path = bf.pathTo(v);
        console.log('=====path from 0 to ' + v + ' start==========');
        for(var i = 0; i < path.length; ++i) {
            var e = path[i];
            console.log(e.from() + ' => ' + e.to() + ': ' + e.weight);
        }
        console.log('=====path from 0 to ' + v + ' end==========');
        console.log('=====distance: '  + bf.distanceTo(v) + '=========');
    }
}

Find the MaxFlow-MinCut using Ford-Fulkerson algorithm

The sample code below show how to obtain the MaxFlow-MinCut of a directed weighted graph using ford-fulkerson algorithm (Link: HTML DEMO):

var jsgraphs = require('js-graph-algorithms');
var g = new jsgraphs.FlowNetwork(8);
g.addEdge(new jsgraphs.FlowEdge(0, 1, 10));
g.addEdge(new jsgraphs.FlowEdge(0, 2, 5));
g.addEdge(new jsgraphs.FlowEdge(0, 3, 15));
g.addEdge(new jsgraphs.FlowEdge(1, 4, 9));
g.addEdge(new jsgraphs.FlowEdge(1, 5, 15));
g.addEdge(new jsgraphs.FlowEdge(1, 2, 4));
g.addEdge(new jsgraphs.FlowEdge(2, 5, 8));
g.addEdge(new jsgraphs.FlowEdge(2, 3, 4));
g.addEdge(new jsgraphs.FlowEdge(3, 6, 16));
g.addEdge(new jsgraphs.FlowEdge(4, 5, 15));
g.addEdge(new jsgraphs.FlowEdge(4, 7, 10));
g.addEdge(new jsgraphs.FlowEdge(5, 7, 10));
g.addEdge(new jsgraphs.FlowEdge(5, 6, 15));
g.addEdge(new jsgraphs.FlowEdge(6, 2, 6));
g.addEdge(new jsgraphs.FlowEdge(6, 7, 10)); 

g.node(2).label = 'Hello';
g.edge(0, 1).label = 'World';

var source = 0;
var target = 7;
var ff = new jsgraphs.FordFulkerson(g, source, target);
console.log('max-flow: ' + ff.value);

var minCut = ff.minCut(g);

for(var i = 0; i < minCut.length; ++i) {
    var e = minCut[i];
    console.log('min-cut: (' + e.from() + ", " + e.to() + ')');
}

About

Package provides javascript implementation of algorithms for graph processing

Topics

mincut dijkstra topological-sort breadth-first-search minimum-spanning-trees depth-first-search maxflow kruskal-algorithm prim-algorithm connected-components strongly-connected-components dijkstra-shortest-path bellman-ford-algorithm

Resources

Readme

License

MIT license
Activity

Stars

147 stars

Watchers

7 watching

Forks

39 forks
Report repository

Releases

No releases published

Packages

No packages published

Contributors 2

Languages