upphiminn · mef · Jun 12, 2016 · Jun 12, 2016 · Jun 12, 2016 · Jun 12, 2016
diff --git a/README.md b/README.md
@@ -1,36 +1,47 @@
 # jLouvain 
+
 **Corneliu S.**
 
----
 ## Description
 
-Formally, a community detection aims to partition a graph’s vertices in subsets, such that there are many edges connecting between vertices of the same sub-set compared to vertices of different sub-sets; in essence, a community has many more ties between each constituent part than with outsiders. There are numerous algorithms present in the literature for solving this problem, a complete survey can be found in [1].  One of the popular community detection algorithms is presented in [2]. This algorithm separates the network in communities by optimizing greedily a modularity score after trying various grouping operations on the network. By using this simple greedy approach the algorithm is computationally very efficient.
-[1] Fortunato, Santo. "Community detection in graphs." Physics Reports 486, no. 3-5 (2010).
-[2] V.D. Blondel, J.-L. Guillaume, R. Lambiotte, E. Lefebvre. "Fast unfolding of communities in large networks." J. Stat. Mech., 2008: 1008.
+Formally, a community detection aims to partition a graph’s vertices in subsets, such that there are many edges connecting between vertices of the same sub-set compared to vertices of different sub-sets; in essence, a community has many more ties between each constituent part than with outsiders. There are numerous algorithms present in the literature for solving this problem, a complete survey can be found in [1].  
 
-##Usage
-1. Import the script.
+One of the popular community detection algorithms is presented in [2]. This algorithm separates the network in communities by optimizing greedily a modularity score after trying various grouping operations on the network. By using this simple greedy approach the algorithm is computationally very efficient.
+
+[1] Fortunato, Santo. "Community detection in graphs." Physics Reports 486, no. 3-5 (2010).
 
+[2] V.D. Blondel, J.-L. Guillaume, R. Lambiotte, E. Lefebvre. "Fast unfolding of communities in large networks." J. Stat. Mech., 2008: 1008.
+
+## Usage
+1. Import the script.
+#### Client-side:
 		<script type="text/javascript" src="jLouvain.js"></script>
-
+#### Or server-side (node.js):
+		var jLouvain = require('./jLouvain')
+
 2. Sample Data Format
-####Node Data
+#### Node Data
 		var node_data = ['id1', 'id2', 'id3']; // any type of string can be used as id
-####Edge Data
+#### Edge Data
 		var edge_data = [{source: 'id1', target:'id2', weight: 10.0}, 
 						 {source: 'id2', target:'id3', weight: 20.0},
 						 {source: 'id3', target:'id1', weight: 30.0}];
-####(Optional) Partition Data
+#### (Optional) Partition Data
 		var init_part = {'id1':0, 'id2':0, 'id3': 1}; 
 		// Object with ids of nodes as properties and community number assigned as value.
 
 3. Run the Algorithm on your node and edge set by chaining the **nodes** and **edges** methods, optionally you can provide an intermediary community partition assignement with the **partition_init** method. [ **Order of chaining is important** ]
 
 		var community = jLouvain().nodes(node_data).edges(edge_data).partition_init(init_part);
-    	var result  = community();##Example
+    	var result  = community();
+
+
+## Example
 See **example.html**, use the console to view the raw input data and raw output.
 
 Initial input graph for community detection.
-![](example/default.png)
-####After Community Detection
-We can see the partitioned graph vertices with the help of color coding.![](example/communities.png)
+
+![](example/default.png)
+#### After Community Detection
+We can see the partitioned graph vertices with the help of color coding.
+![](example/communities.png)
diff --git a/example/example.html b/example/example.html
@@ -3,7 +3,7 @@
   <head>
     <meta charset="utf-8">
     <title>jLouvain Example</title>
-    <script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script>
+    <script src="//d3js.org/d3.v3.min.js" charset="utf-8"></script>
     <script type="text/javascript" src="../jLouvain.js"></script>
 
 

diff --git a/example/serverSide.js b/example/serverSide.js
@@ -0,0 +1,18 @@
+/* 
+ Example of jLouvain used from node.js
+
+ */
+var jLouvain = require('../jLouvain')
+
+var node_data = ['id1', 'id2', 'id3', 'id4']
+	, edge_data = [
+		{source: 'id1', target:'id2', weight: 10.0}
+		, {source: 'id2', target:'id3', weight: 20.0}
+		, {source: 'id3', target:'id1', weight: 30.0}
+	]
+	, init_part = {'id1':0, 'id2':0, 'id3': 1}
+
+var community = jLouvain().nodes(node_data).edges(edge_data).partition_init(init_part)
+	, result  = community()
+
+console.log('result is:', result)
diff --git a/jLouvain.js b/jLouvain.js
@@ -6,8 +6,25 @@
  Based on https://bitbucket.org/taynaud/python-louvain/overview
 
  */
-(function () {
-	jLouvain = function () {
+(function (root, factory) {
+    if (typeof define === 'function' && define.amd) {
+        // AMD. Register as an anonymous module.
+        define([], factory);
+    } else if (typeof module === 'object' && module.exports) {
+        // Node. Does not work with strict CommonJS, but
+        // only CommonJS-like environments that support module.exports,
+        // like Node.
+        module.exports = factory();
+    } else {
+        // Browser globals (root is window)
+        root.jLouvain = factory();
+  }
+}(this, function () {
+
+    // Just return a value to define the module export.
+    // This example returns an object, but the module
+    // can return a function as the exported value.
+    return function () {
 		//Constants
 		var __PASS_MAX = -1;
 		var __MIN = 0.0000001;
@@ -397,4 +414,4 @@
 
 		return core;
 	}
-})();
+}));
diff --git a/package.json b/package.json
@@ -0,0 +1,23 @@
+{
+  "name": "jLouvain",
+  "version": "1.0.0",
+  "description": "**Corneliu S.**",
+  "main": "jLouvain.js",
+  "directories": {
+    "example": "example"
+  },
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/Mango-information-systems/jLouvain.git"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "bugs": {
+    "url": "https://github.com/Mango-information-systems/jLouvain/issues"
+  },
+  "homepage": "https://github.com/Mango-information-systems/jLouvain#readme"
+}