static void Main(string[] args)
{
/// Create a simple temporal network consisting of 11 repeated two-paths (this network corresponds two Fig. 2 (right part) in the paper)
TemporalNetwork temporal_net = new TemporalNetwork();
int k = 0;
for (int i = 0; i < 100; i++)
{
// Add edges according to two paths
temporal_net.AddTemporalEdge(k++, "c", "e");
temporal_net.AddTemporalEdge(k++, "e", "f");
temporal_net.AddTemporalEdge(k++, "a", "e");
temporal_net.AddTemporalEdge(k++, "e", "g");
temporal_net.AddTemporalEdge(k++, "c", "e");
temporal_net.AddTemporalEdge(k++, "e", "f");
temporal_net.AddTemporalEdge(k++, "a", "e");
temporal_net.AddTemporalEdge(k++, "e", "g");
temporal_net.AddTemporalEdge(k++, "c", "e");
temporal_net.AddTemporalEdge(k++, "e", "f");
// Note that the next added edge additionally continues a two-path e -> f -> e
temporal_net.AddTemporalEdge(k++, "f", "e");
temporal_net.AddTemporalEdge(k++, "e", "b");
// An additional edge that should be filtered during preprocessing ...
temporal_net.AddTemporalEdge(k++, "e", "b");
// And one case where we have multiple edges in a single time step
temporal_net.AddTemporalEdge(k, "g", "e");
temporal_net.AddTemporalEdge(k++, "c", "e");
temporal_net.AddTemporalEdge(k++, "e", "f");
temporal_net.AddTemporalEdge(k++, "b", "e");
temporal_net.AddTemporalEdge(k++, "e", "g");
temporal_net.AddTemporalEdge(k++, "c", "e");
temporal_net.AddTemporalEdge(k++, "e", "f");
temporal_net.AddTemporalEdge(k++, "c", "e");
temporal_net.AddTemporalEdge(k++, "e", "f");
}
// Preprocess two-paths and the aggregate network of the temporal network, if this is skipped it will be done automatically when the aggregate network is computed for the first time
Console.Write("Preparing temporal network...");
temporal_net.ReduceToTwoPaths();
Console.WriteLine(" done.");
// Aggregate the temporal network
WeightedNetwork aggregate_net = temporal_net.AggregateNetwork;
// Compute and output betweenness preference of v
Console.WriteLine("Betw. pref. of e in empirical network = \t\t{0:0.00000}",
BetweennessPref.GetBetweennessPref(temporal_net, "e"));
// Create a random temporal network which only preserves the aggregate network (and destroys bet. pref.)
TemporalNetwork microstate_random = TemporalNetworkEnsemble.ShuffleEdges(temporal_net, temporal_net.Length);
microstate_random.ReduceToTwoPaths();
// Create a random temporal network that preserves both the aggregate network and betw. pref.
TemporalNetwork microstate_betweennessPref = TemporalNetworkEnsemble.ShuffleTwoPaths(temporal_net, temporal_net.Length);
microstate_betweennessPref.ReduceToTwoPaths();
// Compute and output betweenness preference of v in random temporal network
Console.WriteLine("Betw. pref. of e with shuffled edges = \t\t\t{0:0.00000}",
BetweennessPref.GetBetweennessPref(microstate_random, "e"));
// Compute and output betweenness preference of v in temporal network preserving betw. pref.
Console.WriteLine("Betw. pref. of e with shuffled two paths = \t\t{0:0.00000}",
BetweennessPref.GetBetweennessPref(microstate_betweennessPref, "e"));
// Compute the betweenness preference matrices of the networks
Dictionary <string, int> ind_pred;
Dictionary <string, int> ind_succ;
double[,] m1 = BetweennessPref.GetBetweennessPrefMatrix(temporal_net, "e", out ind_pred, out ind_succ, normalized: false);
double[,] m2 = BetweennessPref.GetBetweennessPrefMatrix(microstate_betweennessPref, "e", out ind_pred, out ind_succ, normalized: false);
// Get the betweenness preference distribution
IEnumerable <double> dist = BetweennessPref.GetBetweennessPrefDist(temporal_net);
}
/// <summary>
/// Creates randomized temporal networks based on a shuffling of edges or two-paths
/// </summary>
/// <param name="args"></param>
public static void Run(string[] args)
{
if (args.Length < 4)
{
Console.WriteLine("Usage: TempNet shuffle [what] [original_net_file] [output_file] [undirected=false] [length=0]");
Console.WriteLine("... where [what] is ...");
Console.WriteLine("\t 'twopaths' \t Shuffle the two-paths in the original network. Preserves the aggregate network and the betweenness preference distribution.");
Console.WriteLine("\t 'edges' \t Shuffles the edges in the original network. Preserves the aggregate network only.");
Console.WriteLine("");
return;
}
string shuffling = args[1];
string out_file = args[3];
if (!CmdlTools.PromptExistingFile(out_file))
{
Console.WriteLine("User opted to exit.");
return;
}
bool undirected = false;
if (args.Length >= 5)
{
undirected = bool.Parse(args[4]);
}
int length = 0;
if (args.Length == 6)
{
length = int.Parse(args[5]);
}
TemporalNetwork output = null;
Console.Write("Reading temporal network as {0} network...", undirected ? "undirected" : "directed");
TemporalNetwork temp_net = TemporalNetwork.ReadFromFile(args[2], undirected: undirected);
Console.WriteLine(" done.");
Console.Write("Extracting two paths and building aggregate network...");
temp_net.ReduceToTwoPaths();
Console.WriteLine(" done.");
if (shuffling == "twopaths")
{
Console.Write("Shuffling two paths ...");
output = TemporalNetworkEnsemble.ShuffleTwoPaths(temp_net, length);
Console.WriteLine(" done.");
}
else if (shuffling == "edges")
{
Console.Write("Shuffling edges ...");
output = TemporalNetworkEnsemble.ShuffleEdges(temp_net, length);
Console.WriteLine(" done.");
}
else
{
Console.WriteLine("{0} is not a valid parameter!", shuffling);
}
if (output != null)
{
Console.Write("Saving temporal network to {0}...", out_file);
TemporalNetwork.SaveToFile(out_file, output);
Console.WriteLine(" done.");
}
}
