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bellman-ford

Bellman Ford algorithm for node.js

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bellman-ford

bellman-ford allows you to run the bellman ford algorithm in node.js.

It is written in C++ and ported to node.js. It uses a directed graph as it's underlying data structure.

Install

npm install bellman-ford

Examples

Create Graph

var graph = new bellman-ford();

Add Nodes

graph.add_node("a");
graph.add_node("b");
graph.add_node("c");
graph.add_node("d");
graph.add_node("e");

Add Edges

graph.add_edge("a", "b", -0.1);
graph.add_edge("b", "a", 0.2);
graph.add_edge("a", "c", 0.9);
graph.add_edge("c", "e", -0.1);
graph.add_edge("e", "c", 0.2);
graph.add_edge("e", "d", 0.2);
graph.add_edge("d", "e", 0.1);
graph.add_edge("d", "a", 0.4);
graph.add_edge("b", "d", 0.3);

Run Bellman-Ford

console.log(graph.bellmanford("c"));

which will output

[ [ 'a', '0.5' ],
  [ 'b', '0.4' ],
  [ 'd', '0.1' ],
  [ 'e', '-0.1' ],
  [ 'c', '0' ] ]

where each subarray contains a value in the graph say a and the distance to the source node c whcich in this case is 0.5

Functions

add_node

This function adds a node to directed graph. It takes one parameter add_node(node_name) If a node with node_name already exists then nothing wil happen

add_edge

This function adds edges to directed graph. It takes three parameters add_edge(node_from, node_to, edge_weight) If node_from or node_to has not yet beed added to the graph then the function call will fail

update_edge

This function updates edge weights between nodes It takes three parameters update_edge(node_from, node_to, edge_weight)

print

This function prints out the current graph

graph.print();

for the given example will output

a:
	weight: -0.1 to: b
	weight: 0.9 to: c
b:
	weight: 0.2 to: a
	weight: 0.3 to: d
d:
	weight: 0.1 to: e
	weight: 0.4 to: a
e:
	weight: 0.2 to: c
	weight: 0.2 to: d
c:
	weight: -0.1 to: e

trim

This function removes all nodes with less then two edges as well as removing all associated edges.

bellmanford

This is the main function which will run the bellman ford algorithm on the current graph. It will return a 2d array of the form [node_name, distance_from_source]

If the graph contains negative weight cycles then it will return an empty array

Compiling from Source

To compile the code from source you must have python gcc and node-gyp installed on your machine.

Then run

node-gyp configure

and

node-gyp build

Notes

So fare I have only tested this on OS X. I would appricate any and all feedback and suggestions on how this could be improved.

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Package last updated on 20 Nov 2013

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