public Graph(Graph g)
{
this.AdjacencyMatrix = new Dictionary<int, Dictionary<int, double>>();
foreach (var ilist in g.AdjacencyMatrix) {
this.AdjacencyMatrix[ilist.Key] = new Dictionary<int, double>(ilist.Value);
}
this.NumEdges = g.NumEdges;
this.CurrSize = g.CurrSize;
}
static void Main(string[] args)
{
Graph g = new Graph();
//test network
int edgecounter = 0;
using (StreamReader sr = new StreamReader("testnetwork.csv"))
{
string line = null;
while ((line = sr.ReadLine()) != null)
{
line=line.Trim();
if (line==""){continue;}
string[] d = line.Split(',');
int agent = Int32.Parse(d[0]);
for (int i = 1; i < d.Length; i++)
{
int friends = Int32.Parse(d[i]);
g.AddEdge(agent, friends, 1);
edgecounter++;
}
}
}
Console.WriteLine("{0} edges added",edgecounter);
Stopwatch stopwatch = new Stopwatch();
stopwatch.Restart();
Dictionary<int, int> partition = Community.BestPartition(g);
Console.WriteLine("BestPartition: {0}", stopwatch.Elapsed);
var communities = new Dictionary<int, List<int>>();
foreach (var kvp in partition)
{
List<int> nodeset;
if (!communities.TryGetValue(kvp.Value, out nodeset)) {
nodeset = communities[kvp.Value] = new List<int>();
}
nodeset.Add(kvp.Key);
}
Console.WriteLine("{0} communities found", communities.Count);
int counter = 0;
foreach (var kvp in communities)
{
Console.WriteLine("community {0}: {1} people",counter,kvp.Value.Count);
counter++;
}
Console.ReadLine();
}
/// <summary>
/// Creates a
/// </summary>
/// <returns></returns>
public Graph RandomizedNodes(Random random)
{
Graph g = new Graph();
List<int> nodes = this.Nodes.ToList();
for (int i = nodes.Count - 1; i >= 1; i--) {
int j = random.Next(i + 1);
int v = nodes[i];
nodes[i] = nodes[j];
nodes[j] = v;
}
Dictionary<int, int> remapping = new Dictionary<int,int>();
for (int i = 0; i < nodes.Count; i++) {
remapping[nodes[i]] = i;
}
List<Edge> edges = this.Edges.ToList();
for (int i = edges.Count - 1; i >= 1; i--) {
int j = random.Next(i + 1);
Edge v = edges[i];
edges[i] = edges[j];
edges[j] = v;
}
foreach (var edge in edges) {
g.AddEdge(remapping[edge.FromNode], remapping[edge.ToNode], edge.Weight);
}
return g;
}
/// <summary>
/// Produces the induced graph from the quotient described by the partition. The partition is a dictionary from nodes to communities.
/// The produced graph has nodes which are communities, and there is a link of weight w between communities if the sum of the weights of the links
/// between their elements is w.
/// </summary>
/// <param name="partition">A dictionary where keys are graph nodes and values are the community to which the node belongs.</param>
/// <returns>The quotient graph.</returns>
public Graph Quotient(Dictionary<int, int> partition)
{
Graph ret = new Graph();
foreach (int com in partition.Values) {
ret.AddNode(com);
}
foreach (var edge in this.Edges) {
ret.AddEdge(partition[edge.FromNode], partition[edge.ToNode], edge.Weight);
}
return ret;
}
