public void RandomWalkTest()
{
Console.WriteLine("Random Walk test begin...");
var filePath = @"../../../../Data/aucs.mpx";
var networkName = "AUCS";
var mnet = io.ReadMultilayerAsync(filePath, networkName);
var measures = new Measures.Measures();
double[][] transitions = new double[5][];
transitions[0] = new double[] { 0.40, 0.15, 0.15, 0.15, 0.15 };
transitions[1] = new double[] { 0.15, 0.40, 0.15, 0.15, 0.15 };
transitions[2] = new double[] { 0.15, 0.15, 0.40, 0.15, 0.15 };
transitions[3] = new double[] { 0.15, 0.15, 0.15, 0.40, 0.15 };
transitions[4] = new double[] { 0.15, 0.15, 0.15, 0.15, 0.40 };
//var closeness = measures.RandomWalkCloseness(mnet, 0.2, transitions);
//var betweenness = measures.RandomWalkBetweenness(mnet, 0.2, transitions);
var st = 10;
}
public void MeasuresTest()
{
Console.WriteLine("Measures test begin...");
var measures = new Measures.Measures();
var transform = new Transformation.Transformation();
//var filePath = @"../../../../Data/aucs.mpx";
//var networkName = "AUCS";
//var mnet = IO.ReadMultilayer(filePath, networkName);
//var f1 = transform.FlattenUnweighted(mnet, "Flattened", mnet.Layers, false, false);
//var edges = mnet.EdgesByLayerPair[f1.Id][f1.Id];
Console.WriteLine("Creating the network...");
var mnet = new MultilayerNetwork("Transformation Test");
var byactor = mnet.NodesByActor;
var a1 = mnet.AddActor("a1");
var a2 = mnet.AddActor("a2");
var a3 = mnet.AddActor("a3");
var a4 = mnet.AddActor("a4");
var a5 = mnet.AddActor("a5");
var a6 = mnet.AddActor("a6");
var i1 = mnet.AddActor("I1");
var i2 = mnet.AddActor("I2");
var i3 = mnet.AddActor("I3");
var L1 = mnet.AddLayer("People 1", EdgeDirectionality.Undirected);
var L2 = mnet.AddLayer("People 2", EdgeDirectionality.Undirected);
var people = new HashSet <Layer> {
L1, L2
};
var L3 = mnet.AddLayer("Institutions", EdgeDirectionality.Undirected);
var a1l1 = mnet.AddNode(a1, L1);
var a2l1 = mnet.AddNode(a2, L1);
var a3l1 = mnet.AddNode(a3, L1);
var a4l1 = mnet.AddNode(a4, L1);
var a5l1 = mnet.AddNode(a5, L1);
var a1l2 = mnet.AddNode(a1, L2);
var a2l2 = mnet.AddNode(a2, L2);
var a3l2 = mnet.AddNode(a3, L2);
var a4l2 = mnet.AddNode(a4, L2);
var a5l2 = mnet.AddNode(a5, L2);
var i1l3 = mnet.AddNode(i1, L3);
var i2l3 = mnet.AddNode(i2, L3);
var i3l3 = mnet.AddNode(i3, L3);
mnet.AddEdge(a1l1, a2l1);
mnet.AddEdge(a1l1, a3l1);
mnet.AddEdge(a1l2, a2l2);
mnet.AddEdge(a3l2, a4l2);
mnet.AddEdge(a1l2, i1l3);
mnet.AddEdge(a2l2, i1l3);
mnet.AddEdge(a2l2, i2l3);
mnet.AddEdge(a3l2, i2l3);
mnet.AddEdge(a4l2, i2l3);
mnet.AddEdge(a5l2, i3l3);
Console.WriteLine("Creating network end.");
Console.WriteLine("Adjaceny matrices test start...");
var adj = mnet.ToAdjacencyMatrix();
Console.WriteLine("Adjancency matrices test end.");
//foreach (var layer in mnet.Layers)
//{
// var nodes = mnet.NodesByLayer[layer.Id];
// //Console.WriteLine("{0}\t{1}\t{2}\t{3}\t", layer.Name, nodes.Count, measures.Density(mnet, layer), measures.AverageClusteringCoefficient(mnet, layer));
// Console.WriteLine("{0}\t{1}\t{2}\t{3}\t", layer.Name, nodes.Count, measures., measures.AverageClusteringCoefficient(mnet, layer));
//}
//var actor = mnet.GetActor("a1");
//var nodes = mnet.GetNodes(actor);
//Console.WriteLine("Actor: {0}\t Degree: {1},\t Neighborhood: {2},\t Connective Redundancy: {3},\t Exclusive Neighborhood: {4}", actor.Name,measures.Degree(mnet, actor, mnet.GetLayers(), EdgeMode.InOut),
// measures.NeighborhoodCentrality(mnet, actor, mnet.GetLayers(), EdgeMode.InOut),
// measures.ConnectiveRedundancy(mnet, actor, mnet.GetLayers(), EdgeMode.InOut),
// measures.ExclusiveNeighborhood(mnet, actor, mnet.GetLayers(), EdgeMode.InOut));
Console.WriteLine("Done! " + mnet.ToString());
Console.WriteLine("Measures test end.");
}
