/// <summary>
/// Compute the partition block size distribution.
/// </summary>
/// <param name="graph"></param>
/// <param name="labels"></param>
/// <param name="k"></param>
/// <returns></returns>
public static Experiment PartitionBlockDistribution <TNode, TLabel>(MultiDirectedGraph <TNode, TLabel> graph)
{
var partitioner = new GraphPartitioner <TNode, TLabel>(graph);
var partitions = partitioner.MultilevelExactBisimulationReduction();
int k_max = partitions.Count - 1;
var sizes = Utils.Distribution(partitions[k_max].Values).Values.ToArray();
Array.Sort(sizes);
Array.Reverse(sizes);
var experiment = new Experiment(2)
{
Labels = new string[] { "Partition block", "Number of nodes" },
Meta = new string[] { "Blocks", graph.Name, },
F = i =>
{
int index = Convert.ToInt32(i);
int size = sizes[index];
return(new double[] { index + 1, size });
},
};
experiment.Run(0, sizes.Length - 1, 1, 1);
return(experiment);
}
/// <summary>
/// Count the number of partition blocks in a graph.
/// </summary>
/// <typeparam name="TNode"></typeparam>
/// <typeparam name="TLabel"></typeparam>
/// <param name="graph"></param>
/// <param name="labels"></param>
/// <returns></returns>
public static Experiment BisimulationPartitionSize <TNode, TLabel>(MultiDirectedGraph <TNode, TLabel> graph)
{
var partitioner = new GraphPartitioner <TNode, TLabel>(graph);
var partitions = partitioner.MultilevelExactBisimulationReduction();
Experiment experiment = new Experiment(2)
{
Labels = new string[] { "k", "Number of blocks" },
Meta = new string[] { "Partition-size", graph.Name },
F = i =>
{
var k = Convert.ToInt32(i);
var partitionCount = partitions[k].Values.Distinct().Count();
return(new double[] { k, partitionCount });
},
};
experiment.Run(0, partitions.Count - 1, 1, 1);
return(experiment);
// experiment.Save(@"..\..\..\..\Analytics\BisimBlocks-" + graph.Name.ToLower() + ".tsv");
}
/// <summary>
/// Entry point.
/// </summary>
/// <param name="args"></param>
public static void Main(string[] args)
{
//*
Dummy.Fix();
return;
//*/
/*
* AllPerformanceExperiments();
* return;
* //*/
//*
AllAnalyticsExperiments("Petrinet_no_labels");
return;
//*/
// Ask for graph file
string path = Input("Please enter the path to the graph file", string.Copy);
string outPath = Path.GetDirectoryName(path) + @"\..\Results";
// Load graph and labels
var graph = GraphLoader.LoadGraphML(path, int.Parse, int.Parse);
/*
* var partitioner = new GraphPartitioner<int, int>(graph);
* var distributedPartitioner = new DistributedGraphPartitioner<int, int>(1, graph);
* //*/
/*
* var estim = GraphGenerator.ReducedGraph(graph, distributedPartitioner.ExactBisimulationReduction);
* var exact = GraphGenerator.ReducedGraph(graph, partitioner.EstimateBisimulationReduction);
* //*/
//*
// GraphConverter.SaveToGraphML(estim, Path.GetDirectoryName(path) + @"\" + graph.Name + "_estim.xml");
// GraphConverter.SaveToGraphML(exact, Path.GetDirectoryName(path) + @"\" + graph.Name + "_exact.xml");
// GraphConverter.SaveToGraphML(coarse, Path.GetDirectoryName(path) + @"\" + graph.Name + "_coarse.xml");
//*/
// Samplers
var samplers = new Func <double, MultiDirectedGraph <int, int> >[]
{
//* Normal samplers
p => graph.Induce(graph.RN((int)(p * graph.NumNodes))),
p => graph.Induce(graph.RE((int)(p * graph.NumEdges))),
// p => graph.Induce(graph.LowDegreeFirst((int)(p * graph.NumNodes))),
// p => graph.Induce(graph.GreedyLabels((int)(p * graph.NumNodes))),
p => graph.Induce(graph.DistinctLabelsSB((int)(p * graph.NumNodes))),
p => graph.Induce(graph.QueuedSampler <int, int, FifoQueue <int> >((int)(p * graph.NumNodes))),
// p => graph.Induce(graph.QueuedSampler<int, int, LifoQueue<int>>((int)(p * graph.NumNodes))),
// p => graph.Induce(graph.QueuedSampler<int, int, AiroQueue<int>>((int)(p * graph.NumNodes))),
p => graph.Induce(graph.RandomWalkTeleport((int)(p * graph.NumNodes), 0.1)),
//*/
/* Approximation samplers
* p => estim.Induce(estim.RN((int)(p * graph.NumNodes))),
* p => estim.Induce(estim.RE((int)(p * graph.NumEdges))),
* // p => estim.Induce(estim.LowDegreeFirst((int)(p * graph.NumNodes))),
* // p => estim.Induce(estim.GreedyLabels((int)(p * graph.NumNodes))),
* p => estim.Induce(estim.DistinctLabelsSB((int)(p * graph.NumNodes))),
* p => estim.Induce(estim.QueuedSampler<int, int, FifoQueue<int>>((int)(p * graph.NumNodes))),
* // p => estim.Induce(estim.QueuedSampler<int, int, LifoQueue<int>>((int)(p * graph.NumNodes))),
* // p => estim.Induce(estim.QueuedSampler<int, int, AiroQueue<int>>((int)(p * graph.NumNodes))),
* p => estim.Induce(estim.RandomWalkTeleport((int)(p * graph.NumNodes), 0.1)),
* //*/
};
// Sampler names
var samplerNames = new string[]
{
"RN",
"RE",
// "LDF",
// "GL",
"DLSB",
"BFS",
// "DFS",
// "RFS",
"RWT",
};
//*/
//* Run many bisimulation experiments in batch
var partitioner = new GraphPartitioner <int, int>(graph);
var k_max = partitioner.MultilevelExactBisimulationReduction().Count - 1;
for (int k = 0; k <= k_max; k++)
{
for (int i = 0; i < samplers.Length; i++)
{
var sampler = samplers[i];
var samplerName = samplerNames[i];
// var experiment = Experiments.StandardBisimulationMetrics(graph, samplerName, sampler, k);
// Experiment.SaveSVG(outPath + @"\" + string.Join("_", experiment.Meta) + ".svg", experiment.Plot(0.0, 1.0));
// experiment.SaveTSV(outPath + @"\" + string.Join("_", experiment.Meta) + ".tsv");
var experiment = Experiments.WeightedBisimulationMetrics(graph, samplerName, sampler, k);
Experiment.SaveSVG(outPath + @"\" + string.Join("_", experiment.Meta) + ".svg", experiment.Plot(0.0, 1.0));
experiment.SaveTSV(outPath + @"\" + string.Join("_", experiment.Meta) + ".tsv");
Console.WriteLine("[" + DateTime.Now.ToString("HH:mm:ss") + "] k=" + k + " sampler=" + samplerName);
}
;
}
//*/
/*
* // var experiment = Analytics.ReachabilityProbabilityMassFunction(graph);
* // var experiment = Experiments.BisimulationPartitionBlockCounts(graph, labels);
* // var experiment = Experiments.FindKMax(graph, labels);
* // var experiment = Experiments.TreeGeneratorPartitionSize(1, 20);
* PlotForm plotForm = new PlotForm();
* plotForm.Display(experiment.Plot(double.NaN, double.NaN));
* plotForm.ShowDialog();
* //*/
/* Get k
* int k = Input("Please enter a value for k in k-bisimulation", int.Parse);
* //*/
/*
* var experiment = Experiments.DistanceProbabilityMassFunction(graph);
* Experiment.SaveSVG(outPath + @"\" + string.Join("_", experiment.Meta) + ".svg", experiment.Plot(0, double.NaN));
* experiment.SaveTSV(outPath + @"\" + string.Join("_", experiment.Meta) + ".tsv");
* //*/
/* Run bisimulation experiment
* var experiment = Experiments.StandardBisimulationMetrics(graph, labels, () => GraphSampler.Funny(graph, labels));
* Experiment.SaveSVG(outPath + @"\" + string.Join("_", experiment.Meta) + ".svg", experiment.Plot(0.0, 1.0));
* experiment.SaveTSV(outPath + @"\" + string.Join("_", experiment.Meta) + ".tsv");
* //*/
/*
* var experiment = Experiments.BisimulationPartitionSize(graph, labels);
* // var experiment = Experiments.PartitionBlockDistribution(graph, labels);
* Experiment.SaveSVG(outPath + @"\" + string.Join("_", experiment.Meta) + ".svg", experiment.Plot(double.NaN, double.NaN));
* experiment.SaveTSV(outPath + @"\" + string.Join("_", experiment.Meta) + ".tsv");
* //*/
/*
* PlotForm plotForm = new PlotForm();
* plotForm.Display(experiment.Plot(0, double.NaN));
* plotForm.ShowDialog();
* //*/
}