Extremely simple implementation of a network graph library

graph.js

function node(inid,inname) {
  return {
    id : inid,
    name : inname
  };
}

function edge(node1,node2) {
  return {
    source : node1,
    target : node2
  };
}

function binomialCoefficient(n,choose) {
  // http://stackoverflow.com/questions/12983731/algorithm-for-calculating-binomial-coefficient
   var r = 1;
   var d;
   if (choose > n) return 0;
   for (d = 1; d <= choose; d++)
   {
      r *= n--;
      r /= d;
   }
   return r;
}

function graph(nods,edgs) {
  return {
    nodes : nods,
    edges : edgs,
    density : function () {
      return 2*binomialCoefficient(n,2) / (nods.length)*(nods.length-1);
    },
    size : function () {
      return {"nodes" : nods.length, "edges" : edgs.length};
    },
    averageDegree : function() {
      return 2*binomialCoefficient(n,2) / n;
    }
  };
}

function randomGraph(numberNodes,numberEdges) {
  var nodes = [];
  var edges = [];

  for (n = 0; n < numberNodes; n++) {
    nodes.push(node(n,n.toString()));
  }

  for (e = 0; e < numberEdges; e++) {
    var rand1 = Math.floor(Math.random() * (nodes.length-0));
    var rand2 = Math.floor(Math.random() * (nodes.length-0));
    if (rand1 !== rand2) {
      edges.push(edge(nodes[rand1],nodes[rand2]));
    }
  }
  return graph(nodes,edges);
}

g = randomGraph(10,12);